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Emotion Recognition

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하위 태스크: 12
평가표: 10
보존된 평가 기록: 18

Emotion Recognition is an important area of research to enable effective human-computer interaction. Human emotions can be detected using speech signal, facial expressions, body language, and electroencephalography (EEG). Source: Using Deep Autoencoders for Facial Expression Recognition

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/msplabresearch/MSP-Podcast_Challenge

https://github.com/msramalho/election-watch

High-level Approaches to Detect Malicious Political Activity on Twitter

https://github.com/mtzcorporations/nlp_teamjodka

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/musixmatchresearch/umberto

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/mwydmuch/extremeText

Bag of Tricks for Efficient Text Classification

https://github.com/myamamoto555/tf-bert

Attention Is All You Need

https://github.com/nachiketaa/BERT-pytorch

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/nachiketaa/bert

Attention Is All You Need

https://github.com/nafiuny/Optimized_TumorClassifierResNetSD

Deep Learning-based Type Identification of Volumetric MRI Sequences

https://github.com/nageshsinghc4/deepwrap

Bag of Tricks for Efficient Text Classification

https://github.com/nalbarr/coursera-ai4med-course3

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/nameoverflow/neuro-cangjie

Attention Is All You Need

https://github.com/nataliemaus/joco_icml24

Bayesian Optimization with High-Dimensional Outputs

https://github.com/natel9178/transformer-refork

Attention Is All You Need

https://github.com/nav74neet/ddpg4biped

Continuous control with deep reinforcement learning

https://github.com/nav74neet/ddpg_biped

Continuous control with deep reinforcement learning

https://github.com/nav74neet/rl4biped

Continuous control with deep reinforcement learning

https://github.com/nealav/resources

A high-bias, low-variance introduction to Machine Learning for physicists

https://github.com/neburseni/NLP

Attention Is All You Need

https://github.com/neqkir/attention-mechanism

Attention Is All You Need

https://github.com/nerdimite/bert-finetuning-webinar

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/nestle1993/SE16-Task6-Stance-Detection

Convolutional Neural Networks for Sentence Classification

https://github.com/ngocphucck/BERT-questions-classification

Attention Is All You Need

https://github.com/ngonthier/multiresolution_texture

High resolution neural texture synthesis with long range constraints

https://github.com/ngushchin/entropicotbenchmark

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

https://github.com/niccolot/ENG-ITA_NMT

Attention Is All You Need

https://github.com/nicholasbao/nlp_job

Attention Is All You Need

https://github.com/nicolashernandez/readi-lrec22

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/nietao2/DeepSpeechRecognition

Attention Is All You Need

https://github.com/nikhilsu/SuperPixel

High-Quality Face Image SR Using Conditional Generative Adversarial Networks

https://github.com/nithishkaviyan/Sentiment-Analysis-of-Yelp-Reviews

Convolutional Neural Networks for Sentence Classification

https://github.com/nkcr/overlap-ml

Breaking the Softmax Bottleneck: A High-Rank RNN Language Model

https://github.com/nku-zhichengzhang/wecl

https://github.com/nlinc1905/dsilt-tsa

Attention Is All You Need

https://github.com/nmfisher/bert-modified

Attention Is All You Need

https://github.com/nmichlo/experiment-normalized-activations

High-Performance Large-Scale Image Recognition Without Normalization

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.