Papers with Code 아카이브
Emotion Recognition
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- 하위 태스크
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- 평가표
- 10
- 보존된 평가 기록
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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/Mind23-2/MindCode-133
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Mind23-2/MindCode-144
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Mind23-2/MindCode-3/tree/main/HDR-Transformer
Ghost-free High Dynamic Range Imaging with Context-aware Transformer
https://github.com/Mind23-2/MindCode-3/tree/main/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/Mind23-2/MindCode-3/tree/main/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/Mind23-2/MindCode-3/tree/main/ICNet
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
https://github.com/Mind23-2/MindCode-3/tree/main/ibnnet
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/Mind23-2/MindCode-3/tree/main/lite-hrnet
https://github.com/Mind23-2/MindCode-4/tree/main/hrnet
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/Mind23-2/MindCode-41
https://github.com/Mind23-2/MindCode-5/tree/main/Pix2PixHD
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/Mind23-2/MindCode-5/tree/main/PyramidBox
PyramidBox++: High Performance Detector for Finding Tiny Face
https://github.com/Mind23-2/MindCode-52
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/Mind23-2/MindCode-53
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
https://github.com/MindCode-4/code-12/tree/main/GAN-master
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/MindCode-4/code-5/tree/main/transformer
https://github.com/MindCode-4/code-5/tree/main/wav2vec2_bert
Multi-level Fusion of Wav2vec 2.0 and BERT for Multimodal Emotion Recognition
https://github.com/MindCode-4/code-7/tree/main/GAN-master
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/MindCode-4/code-7/tree/main/light-head
https://github.com/MindSpore-paper-code-2/code2/tree/main/PyramidBox
PyramidBox++: High Performance Detector for Finding Tiny Face
https://github.com/MindSpore-paper-code-3/code1/tree/main/AttGAN
High Resolution Face Editing with Masked GAN Latent Code Optimization
https://github.com/MindSpore-paper-code-3/code2/tree/main/dcgan
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/MindSpore-paper-code-3/code5/tree/main/RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/MindSpore-paper-code-3/code6/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/MindSpore-paper-code-3/code7/tree/main/faceboxes
https://github.com/MindSpore-paper-code-3/code9/tree/main/dialogxl
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition
https://github.com/MindSpore-paper-code-3/code9/tree/main/soft_masked_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MindSpore-scientific-2/code-14/tree/main/marian
Marian: Cost-effective High-Quality Neural Machine Translation in C++
https://github.com/MindSpore-scientific-2/code-8/tree/main/RGNN
LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface
https://github.com/MindSpore-scientific/code-1/tree/main/TSA_mindspore
TSAM: A Two-Stream Attention Model for Causal Emotion Entailment
https://github.com/MindSpore-scientific/code-11/tree/main/Super-Resolution-for-Root-Imaging
High-Resolution Image Synthesis with Latent Diffusion Models
https://github.com/MindSpore-scientific/code-11/tree/main/Translation-Invariant/model
https://github.com/MindSpore-scientific/code-2/tree/main/Two-Layer-ReLU-Network-Analytically
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent
https://github.com/MindSpore-scientific/code-7/tree/main/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MindSpore-scientific/code-8/tree/main/RGNN
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.