Papers with Code 아카이브

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/ludwig-ai/ludwig

Ludwig: a type-based declarative deep learning toolbox

https://github.com/luhuiguo/jfasttext

Bag of Tricks for Efficient Text Classification

https://github.com/luiscorujo/HappyHorseMeter

Emotion Recognition in Horses with Convolutional Neural Networks

https://github.com/luke-bhan/TwitterSentimentAnalysisTool

Continuous control with deep reinforcement learning

https://github.com/lukebhan/TwitterSentimentAnalysisTool

Continuous control with deep reinforcement learning

https://github.com/lukemelas/PyTorch-Pretrained-ViT

Attention Is All You Need

https://github.com/lukeoverride/deemotions

Emotion Recognition in the Wild using Deep Neural Networks and Bayesian Classifiers

https://github.com/lumingzzz/tinylic

High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregation

https://github.com/lundalana/Bayesian-ID-Comparison

PyTorch: An Imperative Style, High-Performance Deep Learning Library

https://github.com/luozhilin99/bert

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

https://github.com/luqui/big-sleep

Large Scale GAN Training for High Fidelity Natural Image Synthesis

https://github.com/lvyufeng/Cybertron/blob/master/cybertron/models/bert.py

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

https://github.com/lvyufeng/bert4ms

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

https://github.com/lvyufeng/mindspore-nlp-tutorial

Convolutional Neural Networks for Sentence Classification

https://github.com/lyccol/CodeBERT-based-webshell-detection

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

https://github.com/lyqcom/icnet

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

https://github.com/machine-learning-study-group/movie-sentiment-analysis

Convolutional Neural Networks for Sentence Classification

https://github.com/madhawav/MML

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

https://github.com/madhur-tandon/RL-Project

Continuous control with deep reinforcement learning

https://github.com/madhurchhajed/Facial-Emotion-Recognition

Technical Report for Valence-Arousal Estimation on Affwild2 Dataset

https://github.com/madvn/DDPG

Continuous control with deep reinforcement learning

https://github.com/magahub/songrnn

Attention Is All You Need

https://github.com/magnusja/ppo

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/majercakdavid/gym-virtual-quant-trading

Continuous control with deep reinforcement learning

https://github.com/majing2019/transformer

Attention Is All You Need

https://github.com/makefile/frcnn

Light-Head R-CNN: In Defense of Two-Stage Object Detector

https://github.com/maknotavailable/pytorch-pretrained-bert

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

https://github.com/manastahir/Nvidia--SuperSlowMo-Keras

Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation

https://github.com/manideep2510/siamese-BERT-fake-news-detection-LIAR

Attention Is All You Need

https://github.com/manurare/360monodepth

360MonoDepth: High-Resolution 360° Monocular Depth Estimation

https://github.com/maochf/CMU-MultimodalSDK

Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal Behaviors

https://github.com/marcodeangelis/Area-metric

On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests

https://github.com/marius311/pypico

Computing High Accuracy Power Spectra with Pico

https://github.com/marload/DeepRL-TensorFlow2

Continuous control with deep reinforcement learning

https://github.com/maroxtn/tun-sentiment

Attention Is All You Need

https://github.com/massquantity/DBRL

Continuous control with deep reinforcement learning

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