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Speech Emotion Recognition Based on Multiple Acoustic Features and Deep Convolutional Neural Network

https://doi.org/10.3390/electronics12040839

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What this work says

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

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Speech Emotion Recognition: A Review

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Attention and Feature Selection for Automatic Speech Emotion Recognition Using Utterance and Syllable-Level Prosodic Features

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Enhancement in speaker recognition for optimized speech features using GMM, SVM and 1-D CNN

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A review on speech processing using machine learning paradigm

inferredcites →https://doi.org/10.1007/s11042-020-09874-7openalex-snapshot

Deep learning approaches for speech emotion recognition: state of the art and research challenges

inferredcites →https://doi.org/10.1007/s11277-022-09640-yopenalex-snapshot

Survey of Deep Learning Paradigms for Speech Processing

inferredcites →https://doi.org/10.1016/j.apacoust.2018.11.028openalex-snapshot

A novel feature selection method for speech emotion recognition

inferredcites →https://doi.org/10.1016/j.apacoust.2021.108260openalex-snapshot

Attention guided 3D CNN-LSTM model for accurate speech based emotion recognition

inferredcites →https://doi.org/10.1016/j.bspc.2018.08.035openalex-snapshot

Speech emotion recognition using deep 1D & 2D CNN LSTM networks

inferredcites →https://doi.org/10.1016/j.dsp.2020.102951openalex-snapshot

A survey of speech emotion recognition in natural environment

inferredcites →https://doi.org/10.1016/j.eswa.2020.114177openalex-snapshot

MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach

inferredcites →https://doi.org/10.1016/j.specom.2019.12.001openalex-snapshot

Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers

inferredcites →https://doi.org/10.1049/iet-spr.2017.0320openalex-snapshot

Learning deep features to recognise speech emotion using merged deep CNN

inferredcites →https://doi.org/10.1109/79.911197openalex-snapshot

Emotion recognition in human-computer interaction

inferredcites →https://doi.org/10.1109/access.2019.2936124openalex-snapshot

Speech Emotion Recognition Using Deep Learning Techniques: A Review

inferredcites →https://doi.org/10.1109/access.2019.2938007openalex-snapshot

Speech Emotion Recognition From 3D Log-Mel Spectrograms With Deep Learning Network

inferredcites →https://doi.org/10.1109/access.2020.2984368openalex-snapshot

Multimodal Approach of Speech Emotion Recognition Using Multi-Level Multi-Head Fusion Attention-Based Recurrent Neural Network

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Analysis of Linguistic and Prosodic Features of Bilingual Arabic–English Speakers for Speech Emotion Recognition

inferredcites →https://doi.org/10.1109/access.2020.2990405openalex-snapshot

Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM

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Emotion Recognition From Speech Using Wavelet Packet Transform Cochlear Filter Bank and Random Forest Classifier

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A Novel Approach for Classification of Speech Emotions Based on Deep and Acoustic Features

inferredcites →https://doi.org/10.1109/access.2021.3068045openalex-snapshot

A Comprehensive Review of Speech Emotion Recognition Systems

inferredcites →https://doi.org/10.1109/confluence.2016.7508171openalex-snapshot

LPC and LPCC method of feature extraction in Speech Recognition System

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Emotion recognition in Romanian language using LPC features

inferredcites →https://doi.org/10.1109/iccceee.2018.8515821openalex-snapshot

A Comparative Study of MFCC and LPCC Features For Speech Activity Detection Using Deep Belief Network

inferredcites →https://doi.org/10.1109/iccpct.2017.8074220openalex-snapshot

Speech based emotion recognition in Tamil and Telugu using LPCC and hurst parameters — A comparitive study using KNN and ANN classifiers

inferredcites →https://doi.org/10.1109/icomicon.2017.8279046openalex-snapshot

Sound based human emotion recognition using MFCC & multiple SVM

inferredcites →https://doi.org/10.1109/lsp.2018.2860246openalex-snapshot

3-D Convolutional Recurrent Neural Networks With Attention Model for Speech Emotion Recognition

inferredcites →https://doi.org/10.1109/netact.2017.8076811openalex-snapshot

Significance of teo slope feature in speech emotion recognition

inferredcites →https://doi.org/10.1109/proc.1975.9792openalex-snapshot

Linear prediction: A tutorial review

inferredcites →https://doi.org/10.1109/tsa.2002.800560openalex-snapshot

Musical genre classification of audio signals

inferredcites →https://doi.org/10.1109/wispnet.2017.8299916openalex-snapshot

Emotion recognition using prosodie and spectral features of speech and Naïve Bayes Classifier

inferredcites →https://doi.org/10.1109/wispnet.2017.8300161openalex-snapshot

Speech based human emotion recognition using MFCC

inferredcites →https://doi.org/10.1371/journal.pone.0196391openalex-snapshot

The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English

inferredcites →https://doi.org/10.17743/jaes.2019.0043openalex-snapshot

Continuous Speech Emotion Recognition with Convolutional Neural Networks

inferredcites →https://doi.org/10.21437/interspeech.2005-446openalex-snapshot

A database of German emotional speech

inferredcites →https://doi.org/10.21437/interspeech.2017-200openalex-snapshot

Efficient Emotion Recognition from Speech Using Deep Learning on Spectrograms

inferredcites →https://doi.org/10.21437/interspeech.2021-718openalex-snapshot

A Speech Emotion Recognition Framework for Better Discrimination of Confusions

inferredcites →https://doi.org/10.32604/cmc.2021.015070openalex-snapshot

1D-CNN: Speech Emotion Recognition System Using a Stacked Network with Dilated CNN Features

inferredcites →https://doi.org/10.3390/computation5020026openalex-snapshot

Deep Visual Attributes vs. Hand-Crafted Audio Features on Multidomain Speech Emotion Recognition

inferredcites →https://doi.org/10.3390/electronics10101163openalex-snapshot

A Review on Speech Emotion Recognition Using Deep Learning and Attention Mechanism

inferredcites →https://doi.org/10.3390/electronics10232891openalex-snapshot

Multi-Layer Hybrid Fuzzy Classification Based on SVM and Improved PSO for Speech Emotion Recognition

inferredcites →https://doi.org/10.3390/electronics11233943openalex-snapshot

Speech Emotion Recognition Using Audio Matching

inferredcites →https://doi.org/10.3390/electronics11234047openalex-snapshot

Modeling Speech Emotion Recognition via Attention-Oriented Parallel CNN Encoders

inferredcites →https://doi.org/10.3390/electronics9101725openalex-snapshot

A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces

inferredcites →https://doi.org/10.3390/s20010183openalex-snapshot

A CNN-Assisted Enhanced Audio Signal Processing for Speech Emotion Recognition

inferredcites →https://doi.org/10.3390/s20216008openalex-snapshot

Impact of Feature Selection Algorithm on Speech Emotion Recognition Using Deep Convolutional Neural Network

inferredcites →https://doi.org/10.4304/jcp.6.5.989-998openalex-snapshot

Speech Emotion Recognition Using Novel HHT-TEO Based Features

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inferred← citeshttps://doi.org/10.1007/978-3-031-48309-7_10openalex-snapshot

Linear Frequency Residual Cepstral Coefficients for Speech Emotion Recognition

inferred← citeshttps://doi.org/10.1007/978-3-031-95955-4_17openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-032-09572-5_8openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-032-13419-6_23openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-032-20322-9_32openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-032-20603-9_32openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-032-25809-0_9openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-032-25955-4_34openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-981-96-9191-3_24openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-981-97-9619-9_2openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-981-99-8438-1_18openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s00034-025-03230-6openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s00034-026-03602-6openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s00521-024-10389-7openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s00521-025-10996-yopenalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s10772-024-10123-7openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s10772-024-10138-0openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s10772-026-10287-4openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s10791-026-09914-0openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-024-19674-yopenalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-024-20507-1openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-025-20833-yopenalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-025-21057-wopenalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-026-21252-3openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-026-21280-zopenalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-026-21375-7openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-026-21395-3openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-026-21463-8openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-026-21848-9openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11042-026-21969-1openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s11760-025-04271-9openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s12559-025-10484-4openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s40031-023-00907-xopenalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s40031-026-01343-3openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s41060-025-00822-yopenalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s41060-026-01305-4openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.apacoust.2023.109613openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.apacoust.2025.110615openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.apacoust.2025.110905openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.bspc.2023.105876openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.bspc.2024.106201openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.compbiomed.2024.108841openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.compeleceng.2026.111462openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.engappai.2024.108339openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.engappai.2026.115233openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.eswa.2025.131021openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.iswa.2025.200593openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.jfca.2025.108496openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.jocn.2026.112257openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.measurement.2025.118165openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.neunet.2025.107362openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.pes.2025.100172openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.specom.2024.103102openalex-snapshot

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inferred← citeshttps://doi.org/10.1038/s41598-024-63776-4openalex-snapshot

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inferred← citeshttps://doi.org/10.1038/s41598-025-11989-6openalex-snapshot

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inferred← citeshttps://doi.org/10.1038/s41598-025-28766-0openalex-snapshot

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inferred← citeshttps://doi.org/10.1038/s41598-025-95734-zopenalex-snapshot

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inferred← citeshttps://doi.org/10.1038/s41598-025-99357-2openalex-snapshot

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inferred← citeshttps://doi.org/10.1049/wss2.70025openalex-snapshot

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inferred← citeshttps://doi.org/10.1063/5.0272425openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/3ict64318.2024.10824482openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/access.2024.3474553openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/aicconf69182.2026.11600676openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/asiancon66527.2025.11280694openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/cei60616.2023.10527889openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/comsnets67989.2026.11418141openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/conit59222.2023.10205770openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/cw58918.2023.00051openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/eiecs67708.2025.11283247openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/ic3it66137.2025.11341537openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/ic3se62002.2024.10593399openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icacc63692.2024.10845528openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icaect63952.2025.10958874openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icbds67396.2025.11376913openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icbme68496.2025.11392474openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/iccasit66611.2025.11348840openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icccnt61001.2024.10725674openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icec2nt65402.2025.11380143openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icia64617.2025.11277829openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icicacs68679.2026.11578882openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icscna63714.2024.10863993openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icseiet58677.2023.10303464openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/icsft66733.2026.11507009openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/incet64471.2025.11140902openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/iscslp63861.2024.10800413openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/lsp.2025.3568357openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/percomworkshops65533.2025.00161openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/sustained63638.2024.11074081openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/waie60568.2023.00022openalex-snapshot

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inferred← citeshttps://doi.org/10.1142/s0218348x25400225openalex-snapshot

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inferred← citeshttps://doi.org/10.11591/eei.v13i3.6049openalex-snapshot

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inferred← citeshttps://doi.org/10.11591/ijict.v12i3.pp242-250openalex-snapshot

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inferred← citeshttps://doi.org/10.1186/s13634-025-01213-yopenalex-snapshot

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inferred← citeshttps://doi.org/10.1186/s40537-025-01090-0openalex-snapshot

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inferred← citeshttps://doi.org/10.17762/ijritcc.v11i5.6613openalex-snapshot

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inferred← citeshttps://doi.org/10.17762/ijritcc.v11i9s.7743openalex-snapshot

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inferred← citeshttps://doi.org/10.18280/ria.380318openalex-snapshot

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inferred← citeshttps://doi.org/10.19139/soic-2310-5070-2521openalex-snapshot

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inferred← citeshttps://doi.org/10.21203/rs.3.rs-4018342/v1openalex-snapshot

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inferred← citeshttps://doi.org/10.21203/rs.3.rs-5035263/v1openalex-snapshot

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inferred← citeshttps://doi.org/10.21203/rs.3.rs-9302881/v1openalex-snapshot

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inferred← citeshttps://doi.org/10.2139/ssrn.5366338openalex-snapshot

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inferred← citeshttps://doi.org/10.23919/indiacom70271.2026.11525839openalex-snapshot

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inferred← citeshttps://doi.org/10.26599/air.2024.9150040openalex-snapshot

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inferred← citeshttps://doi.org/10.2991/978-94-6463-242-2_53openalex-snapshot

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inferred← citeshttps://doi.org/10.32604/cmc.2023.044466openalex-snapshot

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inferred← citeshttps://doi.org/10.32985/ijeces.16.1.6openalex-snapshot

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inferred← citeshttps://doi.org/10.3389/frai.2024.1467051openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/app14125227openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/app142311342openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/app15136958openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/brainsci15080835openalex-snapshot

A Novel Optimized Hybrid Deep Learning Framework for Mental Stress Detection Using Electroencephalography

inferred← citeshttps://doi.org/10.3390/electronics12112512openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/electronics12132795openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/electronics12234859openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/electronics14051025openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/electronics14081491openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/info15110677openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/s23146640openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/sci6010010openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/signals7040069openalex-snapshot

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inferred← citeshttps://doi.org/10.4018/979-8-3373-6516-9.ch006openalex-snapshot

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inferred← citeshttps://doi.org/10.4018/ijitsa.385939openalex-snapshot

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inferred← citeshttps://doi.org/10.48047/nq.2022.20.1.nq22423openalex-snapshot

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inferred← citeshttps://doi.org/10.48084/etasr.9067openalex-snapshot

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inferred← citeshttps://doi.org/10.53479/44665openalex-snapshot

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inferred← citeshttps://doi.org/10.55041/ijsrem32388openalex-snapshot

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inferred← citeshttps://doi.org/10.55041/ijsrem32584openalex-snapshot

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inferred← citeshttps://doi.org/10.55056/ceur-ws.org/vol-3702/paper29.pdfopenalex-snapshot

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