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Student Network Learning via Evolutionary Knowledge Distillation

https://doi.org/10.1109/tcsvt.2021.3090902

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-01252-6_17openalex-snapshot

Learning Deep Representations with Probabilistic Knowledge Transfer

inferredcites →https://doi.org/10.1007/978-3-030-01264-9_8openalex-snapshot

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

inferredcites →https://doi.org/10.1007/978-3-642-35289-8_25openalex-snapshot

Stochastic Gradient Descent Tricks

inferredcites →https://doi.org/10.1007/s10479-011-0841-3openalex-snapshot

Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms

inferredcites →https://doi.org/10.1007/s11263-021-01453-zopenalex-snapshot

Knowledge Distillation: A Survey

inferredcites →https://doi.org/10.1109/btas.2017.8272731openalex-snapshot

UMDFaces: An annotated face dataset for training deep networks

inferredcites →https://doi.org/10.1109/btas.2017.8272759openalex-snapshot

Unconstrained Face Detection and Open-Set Face Recognition Challenge

inferredcites →https://doi.org/10.1109/btas46853.2019.9186009openalex-snapshot

Attribute-Guided Coupled GAN for Cross-Resolution Face Recognition

inferredcites →https://doi.org/10.1109/cvpr.2016.518openalex-snapshot

Studying Very Low Resolution Recognition Using Deep Networks

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.713openalex-snapshot

SphereFace: Deep Hypersphere Embedding for Face Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.754openalex-snapshot

A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning

inferredcites →https://doi.org/10.1109/cvpr.2018.00454openalex-snapshot

Deep Mutual Learning

inferredcites →https://doi.org/10.1109/cvpr.2018.00455openalex-snapshot

Coupled End-to-End Transfer Learning with Generalized Fisher Information

inferredcites →https://doi.org/10.1109/cvpr.2018.00552openalex-snapshot

CosFace: Large Margin Cosine Loss for Deep Face Recognition

inferredcites →https://doi.org/10.1109/cvpr.2018.00716openalex-snapshot

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

inferredcites →https://doi.org/10.1109/cvpr.2019.00271openalex-snapshot

Structured Knowledge Distillation for Semantic Segmentation

inferredcites →https://doi.org/10.1109/cvpr.2019.00297openalex-snapshot

Snapshot Distillation: Teacher-Student Optimization in One Generation

inferredcites →https://doi.org/10.1109/cvpr.2019.00409openalex-snapshot

Relational Knowledge Distillation

inferredcites →https://doi.org/10.1109/cvpr.2019.00482openalex-snapshot

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

inferredcites →https://doi.org/10.1109/cvpr.2019.00726openalex-snapshot

Knowledge Distillation via Instance Relationship Graph

inferredcites →https://doi.org/10.1109/cvpr.2019.00938openalex-snapshot

Variational Information Distillation for Knowledge Transfer

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00165openalex-snapshot

GhostNet: More Features From Cheap Operations

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00241openalex-snapshot

Heterogeneous Knowledge Distillation Using Information Flow Modeling

inferredcites →https://doi.org/10.1109/cvpr42600.2020.01294openalex-snapshot

Explaining Knowledge Distillation by Quantifying the Knowledge

inferredcites →https://doi.org/10.1109/cvpr42600.2020.01389openalex-snapshot

Regularizing Class-Wise Predictions via Self-Knowledge Distillation

inferredcites →https://doi.org/10.1109/fg.2018.00020openalex-snapshot

VGGFace2: A Dataset for Recognising Faces across Pose and Age

inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

inferredcites →https://doi.org/10.1109/iccv.2019.00143openalex-snapshot

Knowledge Distillation via Route Constrained Optimization

inferredcites →https://doi.org/10.1109/iccv.2019.00145openalex-snapshot

Similarity-Preserving Knowledge Distillation

inferredcites →https://doi.org/10.1109/iccv.2019.00381openalex-snapshot

Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation

inferredcites →https://doi.org/10.1109/iccv.2019.00511openalex-snapshot

Correlation Congruence for Knowledge Distillation

inferredcites →https://doi.org/10.1109/tcsvt.2017.2770319openalex-snapshot

Pixelwise Deep Sequence Learning for Moving Object Detection

inferredcites →https://doi.org/10.1109/tcsvt.2019.2935128openalex-snapshot

Data Augmentation Using Random Image Cropping and Patching for Deep CNNs

inferredcites →https://doi.org/10.1109/tcsvt.2020.2973301openalex-snapshot

Graph Interaction Networks for Relation Transfer in Human Activity Videos

inferredcites →https://doi.org/10.1109/tcsvt.2020.3037661openalex-snapshot

Improving Cross-Modal Image-Text Retrieval With Teacher-Student Learning

inferredcites →https://doi.org/10.1109/tcsvt.2021.3060162openalex-snapshot

Deep Cross-Modal Representation Learning and Distillation for Illumination-Invariant Pedestrian Detection

inferredcites →https://doi.org/10.1109/tifs.2018.2890812openalex-snapshot

On Low-Resolution Face Recognition in the Wild: Comparisons and New Techniques

inferredcites →https://doi.org/10.1109/tip.2018.2883743openalex-snapshot

Low-Resolution Face Recognition in the Wild via Selective Knowledge Distillation

inferredcites →https://doi.org/10.1109/tip.2021.3066051openalex-snapshot

ResKD: Residual-Guided Knowledge Distillation

inferredcites →https://doi.org/10.1109/tnnls.2020.2970494openalex-snapshot

Learning Student Networks via Feature Embedding

inferredcites →https://doi.org/10.1145/1150402.1150464openalex-snapshot

Model compression

inferredcites →https://doi.org/10.1145/3097983.3098135openalex-snapshot

Learning from Multiple Teacher Networks

inferredcites →https://doi.org/10.1145/3329784openalex-snapshot

Understanding Deep Learning Techniques for Image Segmentation

inferredcites →https://doi.org/10.13140/rg.2.2.24831.10403openalex-snapshot

Recent Advances in Deep Learning: An Overview

inferredcites →https://doi.org/10.1609/aaai.v33i01.33013779openalex-snapshot

Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons

inferredcites →https://doi.org/10.1609/aaai.v33i01.33014886openalex-snapshot

MEAL: Multi-Model Ensemble via Adversarial Learning

inferredcites →https://doi.org/10.1609/aaai.v34i04.5746openalex-snapshot

Online Knowledge Distillation with Diverse Peers

inferredcites →https://doi.org/10.1609/aaai.v34i04.5963openalex-snapshot

Improved Knowledge Distillation via Teacher Assistant

inferredcites →https://doi.org/10.1609/aaai.v34i07.6715openalex-snapshot

Look One and More: Distilling Hybrid Order Relational Knowledge for Cross-Resolution Image Recognition

inferredcites →https://doi.org/10.1609/aaai.v35i9.16969openalex-snapshot

Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching

inferredcites →https://doi.org/10.48550/arxiv.1702.02052openalex-snapshot

Knowledge Adaptation: Teaching to Adapt

inferredcites →https://doi.org/10.48550/arxiv.1802.04977openalex-snapshot

Paraphrasing Complex Network: Network Compression via Factor Transfer

inferredcites →https://doi.org/10.48550/arxiv.1805.05551openalex-snapshot

Knowledge Distillation in Generations: More Tolerant Teachers Educate Better Students

inferredcites →https://doi.org/10.48550/arxiv.2009.08453openalex-snapshot

MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks

inferredcites →https://doi.org/10.5244/c.30.87openalex-snapshot

Wide Residual Networks

inferredcites →https://doi.org/10.57702/zp44cu3gopenalex-snapshot

Learning Multiple Layers of Features from Tiny Images

What points at this work

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

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Evolutionary Computation for Explainable Deep Learning

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Self-knowledge distillation enhanced binary neural networks derived from underutilized information

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Explainable CNN filter pruning based on shapley value approximation in view of game theory

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Decomposition and replacement: Spatial knowledge distillation for monocular depth estimation

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Generative Denoise Distillation: Simple stochastic noises induce efficient knowledge transfer for dense prediction

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Trustworthy knowledge distillation via anchor-guided distribution learning

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Online knowledge distillation optimization based on Multi-Student model Multi-Task collaborative learning

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High-compressed deepfake video detection with contrastive spatiotemporal distillation

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RectMamba: Exploring state space models with entropy-divergence framework for noisy label rectification

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Channel-level Matching Knowledge Distillation for object detectors via MSE

inferred← citeshttps://doi.org/10.1016/j.sysarc.2023.102912openalex-snapshot

Ability-aware knowledge distillation for resource-constrained embedded devices

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Stepwise self-knowledge distillation for skin lesion image classification

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Crowd counting at the edge using weighted knowledge distillation

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Robust Semantic Segmentation With Multi-Teacher Knowledge Distillation

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Self-Supervised Visual Representation Learning via Residual Momentum

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Adaptive Video Anomaly Detection by Attention-Based Relational Knowledge Distillation

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ICSD: An Improved Approach for Clean-Sample-Guided Self-Knowledge Distillation With Data Augmentation

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Selective-Supervised Contrastive Learning with Noisy Labels

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Difference-Adaptive Knowledge Distillation for Resource-Constrained Embedded Devices

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Multi-Part Knowledge Distillation for the Efficient Classification of Colorectal Cancer Histology Images

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SSCD-Net: Semi-supervised Skin Cancer Diagnostical Network Combined with Curriculum Learning, Disease Relation and Clinical Information

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Low-Resolution Face Recognition via Adaptable Instance-Relation Distillation

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Balancing Performance, Efficiency and Robustness in Open-World Machine Learning via Evolutionary Multi-objective Model Compression

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Augmenting Knowledge Distillation with Peer-to-Peer Mutual Learning for Model Compression

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Cooperative Knowledge-Distillation-Based Tiny DNN for UAV-Assisted Mobile-Edge Network

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Diversity Knowledge Distillation for LiDAR-Based 3-D Object Detection

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The Multimodal Scene Recognition Method Based on Self-Attention and Distillation

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DiReDi: Distillation and Reverse Distillation for AIoT Applications

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A Review on Transferability Estimation in Deep Transfer Learning

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Weight-Dependent Gates for Network Pruning

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Deep Cross-Layer Collaborative Learning Network for Online Knowledge Distillation

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Skill-Transferring Knowledge Distillation Method

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Skeleton Neural Networks via Low-Rank Guided Filter Pruning

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Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation

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Boosting Knowledge Distillation via Intra-Class Logit Distribution Smoothing

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Multiple-Level Distillation for Video Fine-Grained Accident Detection

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SD-FSOD: Self-Distillation Paradigm via Distribution Calibration for Few-Shot Object Detection

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Collaborative Knowledge Distillation

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Self-Distillation With Augmentation in Feature Space

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Adaptive Face Recognition for Multi-Type Occlusions

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RCNet: Dual-Network Resonance Collaboration via Mutual Learning for RGB-D Road Defect Detection

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Prototype Decoupled Knowledge Distillation

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Monotonic Rank Knowledge Distillation via Kendall Correlation

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Bi-Stream Coteaching Network for Weakly-Supervised Deepfake Localization in Videos

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Feature Map Distillation of Thin Nets for Low-Resolution Object Recognition

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Efficient Neural Network Compression Inspired by Compressive Sensing

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Knowledge Distillation Using Hierarchical Self-Supervision Augmented Distribution

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Covert Task Embedding: Turning a DNN Into an Insider Agent Leaking Out Private Information

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Heterogeneous Mutual Knowledge Distillation for Wearable Human Activity Recognition

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Hierarchical Multi-Attention Transfer for Knowledge Distillation

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Research on RDE-pose football player foul recognition and pose estimation based on the improved model of YOLOv8

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RSODNet: Lightweight Remote Sensing Image Object Detection Combined with BCDNS Compression Algorithm

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Federated Privacy-Preserving Strategy for Generalizing Soft-Failure Localization in Multi-Carrier Optical Networks

inferred← citeshttps://doi.org/10.3390/app13063816openalex-snapshot

Point–Line-Aware Heterogeneous Graph Attention Network for Visual SLAM System

inferred← citeshttps://doi.org/10.3390/app14167022openalex-snapshot

Class-Center-Based Self-Knowledge Distillation: A Simple Method to Reduce Intra-Class Variance

inferred← citeshttps://doi.org/10.3390/electronics11244080openalex-snapshot

Semi-Supervised Portrait Matting via the Collaboration of Teacher–Student Network and Adaptive Strategies

inferred← citeshttps://doi.org/10.3390/electronics15153351openalex-snapshot

Hierarchical Neuron Energy Feature Decoupled Distillation for Low-Resolution Face Recognition

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