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/thomasslloyd/FitSpatial

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/thoughtmachines/Human-Pose-Estimation-using-HRNets

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/threelittlemonkeys/cnn-text-classification-pytorch

Convolutional Neural Networks for Sentence Classification

https://github.com/threelittlemonkeys/text-cnn-pytorch

Convolutional Neural Networks for Sentence Classification

https://github.com/thu-keg/omnievent

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

https://github.com/thuml/Transfer-Learning-Library

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

https://github.com/thumt/THUMT

Attention Is All You Need

https://github.com/thunlp-mt/ckd

Attention Is All You Need

https://github.com/thunlp/ReInfoSelect

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

https://github.com/tian-kun/Fly-LSH

Improving Similarity Search with High-dimensional Locality-sensitive Hashing

https://github.com/tianxili/GNC

High-dimensional Gaussian graphical model for network-linked data

https://github.com/tiennhamhd/steganoganhd

SteganoGAN: High Capacity Image Steganography with GANs

https://github.com/tilkb/thermoai

Continuous control with deep reinforcement learning

https://github.com/timerstime/SDG4DA

Convolutional Neural Networks for Sentence Classification

https://github.com/tjrwlgns1198/ChatBot

Attention Is All You Need

https://github.com/tkuanlun350/Kaggle_Ship_Detection_2018

Cascade R-CNN: Delving into High Quality Object Detection

https://github.com/tmalbonph/tcbert

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

https://github.com/tmelyralab/musev

VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

https://github.com/tobiasemrich/SchafkopfRL

Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass

https://github.com/tobyatgithub/bert_tutorial

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

https://github.com/tomar840/two-stream-fusion-for-action-recognition-in-videos

Convolutional Two-Stream Network Fusion for Video Action Recognition

https://github.com/tomas-gajarsky/facetorch

Pre-training strategies and datasets for facial representation learning

https://github.com/tomdyer10/fake_news

Attention Is All You Need

https://github.com/tommasopuccetti/adversarial_perturbation

MagNet: a Two-Pronged Defense against Adversarial Examples

https://github.com/toni-sm/skrl

Continuous control with deep reinforcement learning

https://github.com/tornermarton/bert-keras

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

https://github.com/toru34/kim_emnlp_2014

Convolutional Neural Networks for Sentence Classification

https://github.com/towhee-io/towhee

HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions

https://github.com/toxtli/AutomEditor

Multimodal Utterance-level Affect Analysis using Visual, Audio and Text Features

https://github.com/tracy6955/IBM_seizure_data

SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

https://github.com/tree-park/bert-pretrainer

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

https://github.com/tree-park/kor-to-eng-translation

Attention Is All You Need

https://github.com/tree-park/transformer_lm

Attention Is All You Need

https://github.com/trietnm2/sent2vec4j

Bag of Tricks for Efficient Text Classification

https://github.com/truclycs/ocr_seq2seq

Attention Is All You Need

https://github.com/tsbiosky/Cascade-point-rcnn

Cascade R-CNN: Delving into High Quality Object Detection

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