On the public citation graph

Image based Static Facial Expression Recognition with Multiple Deep Network Learning

0 signed · 618 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-10599-4_8openalex-snapshot

Joint Cascade Face Detection and Alignment

inferredcites →https://doi.org/10.1007/978-3-319-16817-3_10openalex-snapshot

Deeply Learning Deformable Facial Action Parts Model for Dynamic Expression Analysis

inferredcites →https://doi.org/10.1007/978-3-540-69905-7_27openalex-snapshot

Blur Insensitive Texture Classification Using Local Phase Quantization

inferredcites →https://doi.org/10.1007/978-3-642-42051-1_16openalex-snapshot

Challenges in Representation Learning: A Report on Three Machine Learning Contests

inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot

ImageNet Large Scale Visual Recognition Challenge

inferredcites →https://doi.org/10.1016/j.imavis.2009.08.002openalex-snapshot

Multi-PIE

inferredcites →https://doi.org/10.1109/cvpr.2012.6248014openalex-snapshot

Face detection, pose estimation, and landmark localization in the wild

inferredcites →https://doi.org/10.1109/cvpr.2014.226openalex-snapshot

Learning Expressionlets on Spatio-temporal Manifold for Dynamic Facial Expression Recognition

inferredcites →https://doi.org/10.1109/cvpr.2014.233openalex-snapshot

Facial Expression Recognition via a Boosted Deep Belief Network

inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot

Going deeper with convolutions

inferredcites →https://doi.org/10.1109/cvprw.2010.5543262openalex-snapshot

The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression

inferredcites →https://doi.org/10.1109/iccvw.2011.6130508openalex-snapshot

Static facial expression analysis in tough conditions: Data, evaluation protocol and benchmark

inferredcites →https://doi.org/10.1109/icme.2005.1521424openalex-snapshot

Web-Based Database for Facial Expression Analysis

inferredcites →https://doi.org/10.1109/icme.2010.5583006openalex-snapshot

The SEMAINE corpus of emotionally coloured character interactions

inferredcites →https://doi.org/10.1109/mmul.2012.26openalex-snapshot

Collecting Large, Richly Annotated Facial-Expression Databases from Movies

inferredcites →https://doi.org/10.1109/tpami.2005.90openalex-snapshot

A video database of moving faces and people

inferredcites →https://doi.org/10.1109/tpami.2007.1110openalex-snapshot

Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions

inferredcites →https://doi.org/10.1109/tpami.2008.52openalex-snapshot

A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions

inferredcites →https://doi.org/10.1109/wacv.2014.6835990openalex-snapshot

Improving multiview face detection with multi-task deep convolutional neural networks

inferredcites →https://doi.org/10.1145/1282280.1282340openalex-snapshot

Representing shape with a spatial pyramid kernel

inferredcites →https://doi.org/10.1145/2522848.2531738openalex-snapshot

Partial least squares regression on grassmannian manifold for emotion recognition

inferredcites →https://doi.org/10.1145/2522848.2531739openalex-snapshot

Emotion recognition in the wild challenge 2013

inferredcites →https://doi.org/10.1145/2522848.2531741openalex-snapshot

Multiple kernel learning for emotion recognition in the wild

inferredcites →https://doi.org/10.1145/2522848.2531745openalex-snapshot

Combining modality specific deep neural networks for emotion recognition in video

inferredcites →https://doi.org/10.1145/2663204.2666272openalex-snapshot

Combining Multimodal Features with Hierarchical Classifier Fusion for Emotion Recognition in the Wild

inferredcites →https://doi.org/10.1145/2663204.2666274openalex-snapshot

Combining Multiple Kernel Methods on Riemannian Manifold for Emotion Recognition in the Wild

inferredcites →https://doi.org/10.1145/2663204.2666275openalex-snapshot

Emotion Recognition In The Wild Challenge 2014

inferredcites →https://doi.org/10.1145/2663204.2666277openalex-snapshot

Emotion Recognition in the Wild with Feature Fusion and Multiple Kernel Learning

inferredcites →https://doi.org/10.1145/3065386openalex-snapshot

ImageNet classification with deep convolutional neural networks

inferredcites →https://doi.org/10.4304/jmm.1.6.22-35openalex-snapshot

Automatic Recognition of Facial Actions in Spontaneous Expressions

inferredcites →https://doi.org/10.48550/arxiv.1301.3557openalex-snapshot

Stochastic Pooling for Regularization of Deep Convolutional Neural Networks

inferredcites →https://doi.org/10.48550/arxiv.1306.0239openalex-snapshot

Deep Learning using Linear Support Vector Machines

inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot

Very Deep Convolutional Networks for Large-Scale Image Recognition

inferredcites →https://doi.org/10.5555/1953048.2021068openalex-snapshot

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3394683openalex-extracted

An Extensive Overview of Techniques for Facial Recognition System

inferred← citeshttps://doi.org/10.2139/ssrn.3524350openalex-extracted

Understanding Videos at Scale: How to Extract Insights for Business Research

inferred← citeshttps://doi.org/10.2139/ssrn.4220699openalex-extracted

Face Expression Recognition Based on Improved Mobilenext

inferred← citeshttps://doi.org/10.2139/ssrn.4395579openalex-extracted

Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation

inferred← citeshttps://doi.org/10.2139/ssrn.4505113openalex-extracted

Leveraging One-Class Classification with Resnet18 and Cbam for Enhanced Facial Expression Recognition

inferred← citeshttps://doi.org/10.5281/zenodo.3944681openalex-extracted

Facial Expression Recognition with Gender Identification

inferred← citeshttps://doi.org/10.1002/9781119751991.ch5openalex-snapshot

Disentanglement For Discriminative Visual Recognition

inferred← citeshttps://doi.org/10.1002/9781119752134.ch5openalex-snapshot

Facial Expression Recognition in Real Time Using Convolutional Neural Network

inferred← citeshttps://doi.org/10.1002/cpe.7137openalex-snapshot

Fused deep learning based Facial Expression Recognition of students in online learning mode

inferred← citeshttps://doi.org/10.1002/smj.3067openalex-snapshot

Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles

inferred← citeshttps://doi.org/10.1002/spe.2866openalex-snapshot

Data fusion analysis for attention‐deficit hyperactivity disorder emotion recognition with thermal image and Internet of Things devices

inferred← citeshttps://doi.org/10.1007/978-3-030-00063-9_19openalex-snapshot

Automatic Extraction of Affective Metadata from Videos Through Emotion Recognition Algorithms

inferred← citeshttps://doi.org/10.1007/978-3-030-00767-6_3openalex-snapshot

Enhancing Feature Correlation for Bi-Modal Group Emotion Recognition

inferred← citeshttps://doi.org/10.1007/978-3-030-01174-1_47openalex-snapshot

EyeHope

inferred← citeshttps://doi.org/10.1007/978-3-030-01418-6_73openalex-snapshot

Improving Ensemble Learning Performance with Complementary Neural Networks for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-3-030-01418-6_74openalex-snapshot

Automatic Beautification for Group-Photo Facial Expressions Using Novel Bayesian GANs

inferred← citeshttps://doi.org/10.1007/978-3-030-02840-4_17openalex-snapshot

Emotion Recognition Using a Convolutional Neural Network

inferred← citeshttps://doi.org/10.1007/978-3-030-03335-4_19openalex-snapshot

Dynamic Facial Expression Recognition Based on Trained Convolutional Neural Networks

inferred← citeshttps://doi.org/10.1007/978-3-030-10925-7_14openalex-snapshot

Face-Cap: Image Captioning Using Facial Expression Analysis

inferred← citeshttps://doi.org/10.1007/978-3-030-12385-7_5openalex-snapshot

Facial Expression Recognition and Analysis of Interclass False Positives Using CNN

inferred← citeshttps://doi.org/10.1007/978-3-030-15887-3_32openalex-snapshot

Deep Neural Networks for Human Behavior Understanding

inferred← citeshttps://doi.org/10.1007/978-3-030-23207-8_14openalex-snapshot

Developing a Deep Learning-Based Affect Recognition System for Young Children

inferred← citeshttps://doi.org/10.1007/978-3-030-23887-2_24openalex-snapshot

Multi-view Cooperative Deep Convolutional Network for Facial Recognition with Small Samples Learning

inferred← citeshttps://doi.org/10.1007/978-3-030-26756-8_18openalex-snapshot

Effective Facial Expression Recognition Through Multimodal Imaging for Traumatic Brain Injured Patient’s Rehabilitation

inferred← citeshttps://doi.org/10.1007/978-3-030-34869-4_27openalex-snapshot

Multichannel CNN for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-3-030-36808-1_70openalex-snapshot

Recognizing Facial Expressions of Occluded Faces Using Convolutional Neural Networks

inferred← citeshttps://doi.org/10.1007/978-3-030-37734-2_9openalex-snapshot

Face Tells Detailed Expression: Generating Comprehensive Facial Expression Sentence Through Facial Action Units

inferred← citeshttps://doi.org/10.1007/978-3-030-46133-1_17openalex-snapshot

Automatic Recognition of Student Engagement Using Deep Learning and Facial Expression

inferred← citeshttps://doi.org/10.1007/978-3-030-63820-7_45openalex-snapshot

EMOTIONCAPS - Facial Emotion Recognition Using Capsules

inferred← citeshttps://doi.org/10.1007/978-3-030-64556-4_39openalex-snapshot

Face Reenactment Based Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-3-030-68133-3_16openalex-snapshot

A Development Framework for Automated Facial Expression Recognition Systems

inferred← citeshttps://doi.org/10.1007/978-3-030-68590-4_9openalex-snapshot

Contactless Human Emotion Analysis Across Different Modalities

inferred← citeshttps://doi.org/10.1007/978-3-030-69538-5_35openalex-snapshot

Emotional Landscape Image Generation Using Generative Adversarial Networks

inferred← citeshttps://doi.org/10.1007/978-3-030-72792-5_16openalex-snapshot

A Bi-directional Residual Network for Image Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-3-030-82565-2_26openalex-snapshot

Expression Recognition Algorithm Based on Infrared Image

inferred← citeshttps://doi.org/10.1007/978-3-030-87178-9_1openalex-snapshot

Image-Based Facial Emotion Recognition Using Convolutional Neural Networks and Transfer Learning

inferred← citeshttps://doi.org/10.1007/978-3-031-13835-5_49openalex-snapshot

ResNet-BiGRU-Attention Based Facial Expression Analysis Model for a Humanoid Robot

inferred← citeshttps://doi.org/10.1007/978-3-031-21671-8_3openalex-snapshot

Constructivist Approaches for Computational Emotions: A Systematic Survey

inferred← citeshttps://doi.org/10.1007/978-3-031-23236-7_55openalex-snapshot

Classification of Facial Expressions Under Partial Occlusion for VR Games

inferred← citeshttps://doi.org/10.1007/978-3-031-35644-5_23openalex-snapshot

Prediction of Face Emotion with Labelled Selective Transfer Machine as a Generalized Emotion Classifier

inferred← citeshttps://doi.org/10.1007/978-3-031-35989-7_38openalex-snapshot

Study on Different Methods for Recognition of Facial Expressions from the Data Generated by Modern HMDs

inferred← citeshttps://doi.org/10.1007/978-3-031-46491-1_33openalex-snapshot

Real-Time Facial Emotion Recognition Using Haar-Cascade Classifier and MobileNet in Smart Cities

inferred← citeshttps://doi.org/10.1007/978-3-031-66705-3_6openalex-snapshot

Automatic Emotion Analysis in Movies: Matteo Garrone’s Dogman as a Case Study

inferred← citeshttps://doi.org/10.1007/978-3-031-75329-9_25openalex-snapshot

Facial Emotion Recognition Using Deep Learning Models Based on Transfer Learning Techniques with Classifier

inferred← citeshttps://doi.org/10.1007/978-3-031-90318-2_5openalex-snapshot

Detection of Facial Emotion with Deep Learning Models and Contribution of Inception-V3

inferred← citeshttps://doi.org/10.1007/978-3-031-94442-0_10openalex-snapshot

Improving Face Recognition from a Single Image

inferred← citeshttps://doi.org/10.1007/978-3-032-16808-5_7openalex-snapshot

Improving the Performance of the Ada-DF Framework on Regular and Small Datasets

inferred← citeshttps://doi.org/10.1007/978-3-319-46475-6_27openalex-snapshot

Peak-Piloted Deep Network for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-3-319-46654-5_55openalex-snapshot

Facial Expression Recognition Based on Multi-scale CNNs

inferred← citeshttps://doi.org/10.1007/978-3-319-46654-5_56openalex-snapshot

Facial Expression Recognition Based on Ensemble of Mulitple CNNs

inferred← citeshttps://doi.org/10.1007/978-3-319-48890-5_37openalex-snapshot

Facial Expression Recognition with Multi-scale Convolution Neural Network

inferred← citeshttps://doi.org/10.1007/978-3-319-52277-7_62openalex-snapshot

How Deep Can We Rely on Emotion Recognition

inferred← citeshttps://doi.org/10.1007/978-3-319-54184-6_9openalex-snapshot

Modeling Stylized Character Expressions via Deep Learning

inferred← citeshttps://doi.org/10.1007/978-3-319-56687-0_13openalex-snapshot

Spatio-temporal Pain Recognition in CNN-Based Super-Resolved Facial Images

inferred← citeshttps://doi.org/10.1007/978-3-319-56687-0_8openalex-snapshot

End to End Deep Learning for Single Step Real-Time Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-3-319-63859-1_3openalex-snapshot

Automatic Facial Age Estimate Based on Convolution Neural Network

inferred← citeshttps://doi.org/10.1007/978-3-319-69456-6_12openalex-snapshot

Facial Expression Recognition Using a Hybrid CNN–SIFT Aggregator

inferred← citeshttps://doi.org/10.1007/978-3-319-71607-7_19openalex-snapshot

Deep Convolutional Neural Network for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-3-319-93040-4_28openalex-snapshot

Emotion Classification with Data Augmentation Using Generative Adversarial Networks

inferred← citeshttps://doi.org/10.1007/978-3-319-93846-2_84openalex-snapshot

Smart Learning Partner: An Interactive Robot for Education

inferred← citeshttps://doi.org/10.1007/978-3-319-94544-6_8openalex-snapshot

Shape and Appearance Based Sequenced Convnets to Detect Real-Time Face Attributes on Mobile Devices

inferred← citeshttps://doi.org/10.1007/978-981-10-3005-5_57openalex-snapshot

Audio Visual Recognition of Spontaneous Emotions In-the-Wild

inferred← citeshttps://doi.org/10.1007/978-981-10-3005-5_58openalex-snapshot

The SYSU System for CCPR 2016 Multimodal Emotion Recognition Challenge

inferred← citeshttps://doi.org/10.1007/978-981-10-7302-1_4openalex-snapshot

Combination of Pyramid CNN Representation and Spatial-Temporal Representation for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-981-15-0626-0_29openalex-snapshot

Literature Survey on Emotion Recognition for Social Signal Processing

inferred← citeshttps://doi.org/10.1007/978-981-15-5345-5_28openalex-snapshot

Facial Expression Recognition Using Improved Local Binary Pattern and Min-Max Similarity with Nearest Neighbor Algorithm

inferred← citeshttps://doi.org/10.1007/978-981-15-8599-9_63openalex-snapshot

Research on Real-Time Expression Recognition of Complex Environment Based on Attention Mechanism

inferred← citeshttps://doi.org/10.1007/978-981-16-7597-3_40openalex-snapshot

A Deep Learning Approach with Data Augmentation to Recognize Facial Expressions in Real Time

inferred← citeshttps://doi.org/10.1007/978-981-16-8512-5_30openalex-snapshot

Virtual Assistant Based on Facial Emotions Using Convolution Neural Networks

inferred← citeshttps://doi.org/10.1007/978-981-16-8664-1_2openalex-snapshot

Leveraging Transfer Learning for Effective Recognition of Emotions from Images: A Review

inferred← citeshttps://doi.org/10.1007/978-981-19-6634-7_36openalex-snapshot

Optimization of Spatial Pyramid Pooling Module Placement for Micro-expression Recognition

inferred← citeshttps://doi.org/10.1007/978-981-19-9858-4_1openalex-snapshot

A CNN-Based Approach for Facial Emotion Detection

inferred← citeshttps://doi.org/10.1007/978-981-33-6176-8_10openalex-snapshot

Facial Expression Detection Model of Seven Expression Types Using Hybrid Feature Selection and Deep CNN

inferred← citeshttps://doi.org/10.1007/978-981-95-5676-2_37openalex-snapshot

DDANet: A Dual-Path Direction-Aware Network with Cross-Direction Attention for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/978-981-97-7831-7_1openalex-snapshot

Facial Emotions Recognition System Using Hybrid Convolutional Neural Network Model

inferred← citeshttps://doi.org/10.1007/978-981-99-3982-4_3openalex-snapshot

A Deep Learning Technique to Recommend Music Based on Facial and Speech Emotions

inferred← citeshttps://doi.org/10.1007/978-981-99-7862-5_14openalex-snapshot

A Deep Learning Model for Automatic Recognition of Facial Expressions Using Haar Cascade Images

inferred← citeshttps://doi.org/10.1007/s00138-021-01270-xopenalex-snapshot

Teacher–student training and triplet loss to reduce the effect of drastic face occlusion

inferred← citeshttps://doi.org/10.1007/s00138-023-01490-3openalex-snapshot

Normalized margin loss for action unit detection

inferred← citeshttps://doi.org/10.1007/s00371-017-1443-0openalex-snapshot

Deeper cascaded peak-piloted network for weak expression recognition

inferred← citeshttps://doi.org/10.1007/s00371-018-1585-8openalex-snapshot

Fast facial expression recognition using local binary features and shallow neural networks

inferred← citeshttps://doi.org/10.1007/s00371-019-01635-4openalex-snapshot

Facial expression recognition algorithm based on parameter adaptive initialization of CNN and LSTM

inferred← citeshttps://doi.org/10.1007/s00371-019-01636-3openalex-snapshot

Deep convolutional BiLSTM fusion network for facial expression recognition

inferred← citeshttps://doi.org/10.1007/s00371-019-01660-3openalex-snapshot

Dual-modality spatiotemporal feature learning for spontaneous facial expression recognition in e-learning using hybrid deep neural network

inferred← citeshttps://doi.org/10.1007/s00371-020-01859-9openalex-snapshot

Review of automated emotion-based quantification of facial expression in Parkinson’s patients

inferred← citeshttps://doi.org/10.1007/s00500-019-03870-2openalex-snapshot

Video analytics-based intelligent surveillance system for smart buildings

inferred← citeshttps://doi.org/10.1007/s00500-019-04387-4openalex-snapshot

Hyperparameter optimization in CNN for learning-centered emotion recognition for intelligent tutoring systems

inferred← citeshttps://doi.org/10.1007/s00500-019-04530-1openalex-snapshot

Weakly supervised facial expression recognition via transferred DAL-CNN and active incremental learning

inferred← citeshttps://doi.org/10.1007/s00500-023-09199-1openalex-snapshot

Facial expression recognition based on multi-channel fusion and lightweight neural network

inferred← citeshttps://doi.org/10.1007/s00521-020-05676-yopenalex-snapshot

FER-net: facial expression recognition using deep neural net

inferred← citeshttps://doi.org/10.1007/s00521-021-06045-zopenalex-snapshot

Discriminative attention-augmented feature learning for facial expression recognition in the wild

inferred← citeshttps://doi.org/10.1007/s00521-021-06613-3openalex-snapshot

Deep learning inspired intelligent embedded system for haptic rendering of facial emotions to the blind

inferred← citeshttps://doi.org/10.1007/s00521-022-07016-8openalex-snapshot

Effective attention feature reconstruction loss for facial expression recognition in the wild

inferred← citeshttps://doi.org/10.1007/s00530-023-01062-5openalex-snapshot

CSLSEP: an ensemble pruning algorithm based on clustering soft label and sorting for facial expression recognition

inferred← citeshttps://doi.org/10.1007/s10044-021-00988-8openalex-snapshot

Deep transfer learning in human–robot interaction for cognitive and physical rehabilitation purposes

inferred← citeshttps://doi.org/10.1007/s10115-018-1176-zopenalex-snapshot

RTCRelief-F: an effective clustering and ordering-based ensemble pruning algorithm for facial expression recognition

inferred← citeshttps://doi.org/10.1007/s10489-019-01491-8openalex-snapshot

Facial expression recognition sensing the complexity of testing samples

inferred← citeshttps://doi.org/10.1007/s10489-022-03200-4openalex-snapshot

Three-dimensional DenseNet self-attention neural network for automatic detection of student’s engagement

inferred← citeshttps://doi.org/10.1007/s10489-022-03553-wopenalex-snapshot

PERSIST: Improving micro-expression spotting using better feature encodings and multi-scale Gaussian TCN

inferred← citeshttps://doi.org/10.1007/s10489-024-05999-6openalex-snapshot

Reliability-aware label distribution learning with attention-rectified for facial expression recognition

inferred← citeshttps://doi.org/10.1007/s10772-022-09981-wopenalex-snapshot

A multi-modal deep learning system for Arabic emotion recognition

inferred← citeshttps://doi.org/10.1007/s11036-019-01366-9openalex-snapshot

Human Behavior Understanding in Big Multimedia Data Using CNN based Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/s11042-017-5158-zopenalex-snapshot

Expression recognition using semantic information and local texture features

inferred← citeshttps://doi.org/10.1007/s11042-017-5489-9openalex-snapshot

Facial expression recognition based on dual-feature fusion and improved random forest classifier

inferred← citeshttps://doi.org/10.1007/s11042-019-08397-0openalex-snapshot

PRATIT: a CNN-based emotion recognition system using histogram equalization and data augmentation

inferred← citeshttps://doi.org/10.1007/s11042-019-7530-7openalex-snapshot

Multi-stream CNN for facial expression recognition in limited training data

inferred← citeshttps://doi.org/10.1007/s11042-020-08681-4openalex-snapshot

Recognition of facial expressions based on CNN features

inferred← citeshttps://doi.org/10.1007/s11042-020-09268-9openalex-snapshot

Static facial expression recognition using convolutional neural networks based on transfer learning and hyperparameter optimization

inferred← citeshttps://doi.org/10.1007/s11042-020-09566-2openalex-snapshot

Rapid facial expression recognition under part occlusion based on symmetric SURF and heterogeneous soft partition network

inferred← citeshttps://doi.org/10.1007/s11042-020-10332-7openalex-snapshot

Multi-facial patches aggregation network for facial expression recognition and facial regions contributions to emotion display

inferred← citeshttps://doi.org/10.1007/s11042-022-12790-7openalex-snapshot

Benchmarking deep networks for facial emotion recognition in the wild

inferred← citeshttps://doi.org/10.1007/s11042-022-13940-7openalex-snapshot

An ensemble approach using a frequency-based and stacking classifiers for effective facial expression recognition

inferred← citeshttps://doi.org/10.1007/s11042-023-15570-zopenalex-snapshot

Facial emotion recognition based on deep transfer learning approach

inferred← citeshttps://doi.org/10.1007/s11042-023-16433-3openalex-snapshot

CC-CNN: A cross connected convolutional neural network using feature level fusion for facial expression recognition

inferred← citeshttps://doi.org/10.1007/s11042-023-17904-3openalex-snapshot

Leveraging facial expressions as emotional context in image captioning

inferred← citeshttps://doi.org/10.1007/s11227-021-03690-yopenalex-snapshot

Deep neural network-based fusion model for emotion recognition using visual data

inferred← citeshttps://doi.org/10.1007/s11227-023-05864-2openalex-snapshot

Multi-strategy text data augmentation for enhanced aspect-based sentiment analysis in resource-limited scenarios

inferred← citeshttps://doi.org/10.1007/s11263-017-1055-1openalex-snapshot

From Facial Expression Recognition to Interpersonal Relation Prediction

inferred← citeshttps://doi.org/10.1007/s11263-018-1131-1openalex-snapshot

Blended Emotion in-the-Wild: Multi-label Facial Expression Recognition Using Crowdsourced Annotations and Deep Locality Feature Learning

inferred← citeshttps://doi.org/10.1007/s11263-021-01556-7openalex-snapshot

Adaptive Deep Disturbance-Disentangled Learning for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/s11276-021-02665-4openalex-snapshot

RETRACTED ARTICLE: A mixed depthwise separation residual network for image feature extraction

inferred← citeshttps://doi.org/10.1007/s11554-021-01123-wopenalex-snapshot

Two-pathway attention network for real-time facial expression recognition

inferred← citeshttps://doi.org/10.1007/s11760-019-01547-9openalex-snapshot

Effective curvelet-based facial expression recognition using graph signal processing

inferred← citeshttps://doi.org/10.1007/s11760-022-02339-4openalex-snapshot

ARM: a lightweight module to amend facial expression representation

inferred← citeshttps://doi.org/10.1007/s11760-023-02490-6openalex-snapshot

DTL-I-ResNet18: facial emotion recognition based on deep transfer learning and improved ResNet18

inferred← citeshttps://doi.org/10.1007/s12193-015-0209-0openalex-snapshot

Hierarchical committee of deep convolutional neural networks for robust facial expression recognition

inferred← citeshttps://doi.org/10.1007/s12193-019-00308-9openalex-snapshot

Multi-modal facial expression feature based on deep-neural networks

inferred← citeshttps://doi.org/10.1007/s12530-026-09845-7openalex-snapshot

MPA-Net: a multiscale and permute attention network for occlusion and pose robust facial expression recognition in the wild

inferred← citeshttps://doi.org/10.1007/s12626-019-00059-9openalex-snapshot

An Algorithm of Recommending Apposite ID Photos

inferred← citeshttps://doi.org/10.1007/s12652-017-0473-9openalex-snapshot

Modified dimensionality reduced local directional pattern for facial analysis

inferred← citeshttps://doi.org/10.1007/s12652-020-02311-5openalex-snapshot

Graph based feature extraction and hybrid classification approach for facial expression recognition

inferred← citeshttps://doi.org/10.1007/s12652-022-03843-8openalex-snapshot

Visual attention based composite dense neural network for facial expression recognition

inferred← citeshttps://doi.org/10.1007/s13042-024-02508-6openalex-snapshot

RLGA-FER: reinforcement learning based on genetic algorithm for facial expression recognition enhancing

inferred← citeshttps://doi.org/10.1007/s40009-026-01952-yopenalex-snapshot

Fine-Tuning MobileNetV2 for Lightweight Facial Emotion Recognition: FER-2013 and CK+ Datasets

inferred← citeshttps://doi.org/10.1007/s40031-022-00746-2openalex-snapshot

A Deep Learning Framework with Cross Pooled Soft Attention for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1007/s41870-021-00803-xopenalex-snapshot

An efficient CNN approach for facial expression recognition with some measures of overfitting

inferred← citeshttps://doi.org/10.1007/s41870-023-01183-0openalex-snapshot

Facial expression recognition in videos using hybrid CNN & ConvLSTM

inferred← citeshttps://doi.org/10.1016/j.aej.2023.01.017openalex-snapshot

A comprehensive survey on deep facial expression recognition: challenges, applications, and future guidelines

inferred← citeshttps://doi.org/10.1016/j.artmed.2019.06.004openalex-snapshot

Labeling images with facial emotion and the potential for pediatric healthcare

inferred← citeshttps://doi.org/10.1016/j.bspc.2021.102743openalex-snapshot

Leveraging spatial-temporal convolutional features for EEG-based emotion recognition

inferred← citeshttps://doi.org/10.1016/j.cities.2020.102719openalex-snapshot

Quantifying the bias in place emotion extracted from photos on social networking sites: A case study on a university campus

inferred← citeshttps://doi.org/10.1016/j.cogsys.2018.06.017openalex-snapshot

Wild facial expression recognition based on incremental active learning

inferred← citeshttps://doi.org/10.1016/j.compeleceng.2021.107196openalex-snapshot

Intelligent interaction model for battleship control based on the fusion of target intention and operator emotion

inferred← citeshttps://doi.org/10.1016/j.csda.2024.108073openalex-snapshot

Multi-model subset selection

inferred← citeshttps://doi.org/10.1016/j.displa.2022.102330openalex-snapshot

The decadal perspective of facial emotion processing and Recognition: A survey

inferred← citeshttps://doi.org/10.1016/j.dsp.2021.103121openalex-snapshot

Latent sparse transfer subspace learning for cross-corpus facial expression recognition

inferred← citeshttps://doi.org/10.1016/j.engappai.2022.105651openalex-snapshot

Multi-task learning on the edge for effective gender, age, ethnicity and emotion recognition

inferred← citeshttps://doi.org/10.1016/j.eswa.2020.113460openalex-snapshot

Modeling adaptive E-Learning environment using facial expressions and fuzzy logic

inferred← citeshttps://doi.org/10.1016/j.ijinfomgt.2024.102801openalex-snapshot

Towards AI-based thumbnail design for fostering consumption on digital media platforms

inferred← citeshttps://doi.org/10.1016/j.image.2019.03.010openalex-snapshot

Feature augmentation for imbalanced classification with conditional mixture WGANs

inferred← citeshttps://doi.org/10.1016/j.imavis.2017.01.012openalex-snapshot

Video-based emotion recognition in the wild using deep transfer learning and score fusion

inferred← citeshttps://doi.org/10.1016/j.imavis.2020.104038openalex-snapshot

Expression recognition with deep features extracted from holistic and part-based models

inferred← citeshttps://doi.org/10.1016/j.inffus.2019.06.019openalex-snapshot

A snapshot research and implementation of multimodal information fusion for data-driven emotion recognition

inferred← citeshttps://doi.org/10.1016/j.ins.2020.02.047openalex-snapshot

A ROI-guided deep architecture for robust facial expressions recognition

inferred← citeshttps://doi.org/10.1016/j.ins.2020.10.065openalex-snapshot

New framework for person-independent facial expression recognition combining textural and shape analysis through new feature extraction approach

inferred← citeshttps://doi.org/10.1016/j.ins.2021.10.005openalex-snapshot

A survey on facial emotion recognition techniques: A state-of-the-art literature review

inferred← citeshttps://doi.org/10.1016/j.jbusres.2020.09.059openalex-snapshot

Understanding videos at scale: How to extract insights for business research

inferred← citeshttps://doi.org/10.1016/j.jer.2024.03.021openalex-snapshot

A multimodal emotion recognition system using deep convolution neural networks

inferred← citeshttps://doi.org/10.1016/j.jksuci.2018.09.011openalex-snapshot

MAFONN-EP: A Minimal Angular Feature Oriented Neural Network based Emotion Prediction system in image processing

inferred← citeshttps://doi.org/10.1016/j.knosys.2022.109304openalex-snapshot

Four-player GroupGAN for weak expression recognition via latent expression magnification

inferred← citeshttps://doi.org/10.1016/j.matpr.2020.08.501openalex-snapshot

A CNN based facial expression recognizer

inferred← citeshttps://doi.org/10.1016/j.matpr.2020.12.1137openalex-snapshot

WITHDRAWN: Predicting class and pose for a face recognition application with simple and efficient reconstruction technique

inferred← citeshttps://doi.org/10.1016/j.neucom.2018.07.003openalex-snapshot

Unsupervised facial expression recognition using domain adaptation based dictionary learning approach

inferred← citeshttps://doi.org/10.1016/j.neucom.2018.07.028openalex-snapshot

Spatio-temporal convolutional features with nested LSTM for facial expression recognition

inferred← citeshttps://doi.org/10.1016/j.neucom.2020.01.067openalex-snapshot

Fine-grained facial expression analysis using dimensional emotion model

inferred← citeshttps://doi.org/10.1016/j.neucom.2020.12.092openalex-snapshot

Can edges help convolution neural networks in emotion recognition?

inferred← citeshttps://doi.org/10.1016/j.neucom.2023.01.027openalex-snapshot

Triple-BigGAN: Semi-supervised generative adversarial networks for image synthesis and classification on sexual facial expression recognition

inferred← citeshttps://doi.org/10.1016/j.nlp.2024.100077openalex-snapshot

Enhancing aspect-based sentiment analysis with BERT-driven context generation and quality filtering

inferred← citeshttps://doi.org/10.1016/j.patcog.2021.108401openalex-snapshot

Co-attentive multi-task convolutional neural network for facial expression recognition

inferred← citeshttps://doi.org/10.1016/j.patrec.2019.04.002openalex-snapshot

Facial expression recognition boosted by soft label with a diverse ensemble

inferred← citeshttps://doi.org/10.1016/j.patrec.2020.11.002openalex-snapshot

Combined center dispersion loss function for deep facial expression recognition

inferred← citeshttps://doi.org/10.1038/s41598-022-11173-0openalex-snapshot

Four-layer ConvNet to facial emotion recognition with minimal epochs and the significance of data diversity

inferred← citeshttps://doi.org/10.1038/s41598-024-69555-5openalex-snapshot

Using geotagged facial expressions to visualize and characterize different demographic groups’ emotion in theme parks

inferred← citeshttps://doi.org/10.1038/s41598-025-22835-0openalex-snapshot

An improved facial emotion recognition system using convolutional neural network for the optimization of human robot interaction

inferred← citeshttps://doi.org/10.1038/s41598-026-40798-8openalex-snapshot

A novel multi-module neural networks strategy of human emotion recognition in the human-robot interaction

inferred← citeshttps://doi.org/10.1049/el.2018.7871openalex-snapshot

FER‐Net: facial expression recognition using densely connected convolutional network

inferred← citeshttps://doi.org/10.1049/iet-cvi.2018.5127openalex-snapshot

Self‐adaptive weighted synthesised local directional pattern integrating with sparse autoencoder for expression recognition based on improved multiple kernel learning strategy

inferred← citeshttps://doi.org/10.1049/iet-ipr.2019.1188openalex-snapshot

Novel deep learning model for facial expression recognition based on maximum boosted CNN and LSTM

inferred← citeshttps://doi.org/10.1049/iet-spr.2018.5087openalex-snapshot

Facial expression recognition using the spectral graph wavelet

inferred← citeshttps://doi.org/10.1049/ipr2.12817openalex-snapshot

DLSANet: Facial expression recognition with double‐code LBP‐layer spatial‐attention network

inferred← citeshttps://doi.org/10.1049/joe.2020.0183openalex-snapshot

Novel multi‐scale deep residual attention network for facial expression recognition

inferred← citeshttps://doi.org/10.1051/itmconf/20224403058openalex-snapshot

Deep Learning based Facial Emotion Recognition

inferred← citeshttps://doi.org/10.1051/itmconf/20258001012openalex-snapshot

DCM-Net: A deep composite micro-tuning network for enhancing feature generalization in low-resolution facial expression recognition

inferred← citeshttps://doi.org/10.1063/5.0112473openalex-snapshot

A systematic analysis of machine learning algorithms for human emotion detection using facial expression

inferred← citeshttps://doi.org/10.1063/5.0133760openalex-snapshot

Multi-modal emotions detection service using deep learning techniques

inferred← citeshttps://doi.org/10.1063/5.0259128openalex-snapshot

Recognizing facial expressions using deep belief network and comparing the accuracy over multi-layer perceptron algorithm

inferred← citeshttps://doi.org/10.1063/5.0286667openalex-snapshot

An extensive investigation of deep learning models for recognizing face emotions

inferred← citeshttps://doi.org/10.1080/10584587.2021.1911313openalex-snapshot

The Facial Expression Recognition Method Based on Image Fusion and CNN

inferred← citeshttps://doi.org/10.1080/23080477.2025.2460837openalex-snapshot

Recent advancements in facial emotion recognition using conventional and deep neural network: a comprehensive review

inferred← citeshttps://doi.org/10.1088/1757-899x/928/3/032036openalex-snapshot

Classifying Facial Expression using Convolution Neural Network

inferred← citeshttps://doi.org/10.1098/rsta.2022.0047openalex-snapshot

Emotion prediction as computation over a generative theory of mind

inferred← citeshttps://doi.org/10.1108/itse-01-2024-0015openalex-snapshot

Examining learners’ cognitive processes and learning emotions in digital game-based vocabulary learning: evidence from eye-tracking technology and facial emotion recognition

inferred← citeshttps://doi.org/10.1109/access.2017.2777003openalex-snapshot

Facial Expression Recognition Using Salient Features and Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/access.2017.2784096openalex-snapshot

Facial Expression Recognition Using Weighted Mixture Deep Neural Network Based on Double-Channel Facial Images

inferred← citeshttps://doi.org/10.1109/access.2018.2870063openalex-snapshot

Physiological Inspired Deep Neural Networks for Emotion Recognition

inferred← citeshttps://doi.org/10.1109/access.2019.2899024openalex-snapshot

Facial Expression Recognition Using Fusion Features Based on Center-Symmetric Local Octonary Pattern

inferred← citeshttps://doi.org/10.1109/access.2019.2907271openalex-snapshot

A Deep Spatial and Temporal Aggregation Framework for Video-Based Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/access.2019.2917266openalex-snapshot

Local Learning With Deep and Handcrafted Features for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/access.2019.2923530openalex-snapshot

Data Augmentation and Second-Order Pooling for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/access.2019.2926040openalex-snapshot

MIT Advanced Vehicle Technology Study: Large-Scale Naturalistic Driving Study of Driver Behavior and Interaction With Automation

showing the first 200 of 584

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.