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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/open-edge-platform/training_extensions

Lite-HRNet: A Lightweight High-Resolution Network

https://github.com/open-mmlab/mmclassification

Attention Is All You Need

https://github.com/open-mmlab/mmdetection

Cascade R-CNN: Delving into High Quality Object Detection

https://github.com/open-mmlab/mmgeneration

Large Scale GAN Training for High Fidelity Natural Image Synthesis

https://github.com/open-mmlab/mmpose

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/open-mmlab/mmsegmentation

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/opennmt/ctranslate2

Attention Is All You Need

https://github.com/ortec/euro-neurips-vrp-2022-quickstart

PILS: Exploring high-order neighborhoods by pattern mining and injection

https://github.com/osmr/imgclsmob

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

https://github.com/overfitter/biobert_embedding

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

https://github.com/owainwest/uniprot_bert

Attention Is All You Need

https://github.com/owj0421/DeepFashion

Learning Type-Aware Embeddings for Fashion Compatibility

https://github.com/owj0421/csa-net

Learning Type-Aware Embeddings for Fashion Compatibility

https://github.com/oylz/FDSSTTest

High-Speed Tracking with Kernelized Correlation Filters

https://github.com/paolanu/BERT_epitope

Attention Is All You Need

https://github.com/paper-cat/Sentence-Classifications

Convolutional Neural Networks for Sentence Classification

https://github.com/parcorelab/comscribe

Attention Is All You Need

https://github.com/parilo/rl-server

Continuous control with deep reinforcement learning

https://github.com/parsa-abbasi/IUST-Pattern-Recognition

UTSig: A Persian Offline Signature Dataset

https://github.com/pat-coady/trpo

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/patrickhart/jaxdl

Attention Is All You Need

https://github.com/paulskeie/stadnamn

Attention Is All You Need

https://github.com/paulwarkentin/pytorch-neural-doodle

Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks

https://github.com/pengming617/bert_classification

Attention Is All You Need

https://github.com/pengshuyuan/Bert

Attention Is All You Need

https://github.com/penny9287/sockeye

Attention Is All You Need

https://github.com/pennylaneai/generative-quantum-states

Attention Is All You Need

https://github.com/petsol/ContinuousControl_UnityAgent_DDPG_Udacity

Continuous control with deep reinforcement learning

https://github.com/pfecht/bert-exploration

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

https://github.com/phohenecker/pytorch-transformer

Attention Is All You Need

https://github.com/piegu/language-models

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

https://github.com/pikabite/segmentations_tf2

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/pingheng001/Cnn-Bert

Attention Is All You Need

https://github.com/pipidog/CNLP

Convolutional Neural Networks for Sentence Classification

https://github.com/pipidog/QNLP

Convolutional Neural Networks for Sentence Classification

https://github.com/piquil/rydberggpt

Attention Is All You Need

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