Papers with Code 아카이브
Emotion Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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://zenodo.org/record/8077639
공식 코드Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test
https://bitbucket.org/woalsdnd/codes_and_data
Training Deep Neural Networks on Noisy Labels with Bootstrapping
https://dagshub.com/arnavr.neo/VT-LPR
Vehicle and License Plate Recognition with Novel Dataset for Toll Collection
https://github.com/04RR/SOTA-Vision
https://github.com/0x0f0f0f/Metatheory.jl
https://github.com/163GitHub/AI
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/18XiWenjuan/LMF_Paddle
Efficient Low-rank Multimodal Fusion with Modality-Specific Factors
https://github.com/1wy/bert
https://github.com/2023-MindSpore-1/ms-code-11
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-1/ms-code-12
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-1/ms-code-14/tree/main/Transformer
https://github.com/2023-MindSpore-1/ms-code-150
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/2023-MindSpore-1/ms-code-162
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-192
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/2023-MindSpore-1/ms-code-197
https://github.com/2023-MindSpore-1/ms-code-198
https://github.com/2023-MindSpore-1/ms-code-200
https://github.com/2023-MindSpore-1/ms-code-210/tree/main/DDAG
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FaceDetection
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HMR
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/gan
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/ibnnet
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tsn
TSNAT: Two-Step Non-Autoregressvie Transformer Models for Speech Recognition
https://github.com/2023-MindSpore-1/ms-code-219/tree/main/dialogxl
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/2023-MindSpore-1/ms-code-56
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/Pix2PixHD1
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/cct
CDPA: Common and Distinctive Pattern Analysis between High-dimensional Datasets
https://github.com/2023-MindSpore-1/ms-code-65
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/2023-MindSpore-4/Code-5/tree/main/HDR-Transformer
Ghost-free High Dynamic Range Imaging with Context-aware Transformer
https://github.com/2023-MindSpore-4/Code-5/tree/main/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.