https://github.com/2023-MindSpore-4/Code-5/tree/main/ibnnet
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
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://github.com/2023-MindSpore-4/Code-5/tree/main/lite-hrnet
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-4/Code12/tree/main/d2l/chapter_12_computational-performance
https://github.com/2023-MindSpore-4/Code6/tree/main/PyramidBox
PyramidBox++: High Performance Detector for Finding Tiny Face
https://github.com/2023-MindSpore-4/Code6/tree/main/RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/2023-MindSpore-4/Code8/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/2023-MindSpore-4/Code8/tree/main/AttentionCluster
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/audio_spectrogram_transformer
https://github.com/2024-MindSpore-1/Code3/tree/main/scBERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2024-MindSpore-1/Code5/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/2miatran/Natural-Language-Processing
https://github.com/ABaldrati/MT-BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AGiannoutsos/COVID19-document-retrieval-with-BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AIwithSwift/TFWorld2019-SwiftIn3Hours
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
https://github.com/ANIME305/Anime-GAN
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/ANIME305/Anime-GAN-tensorflow
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/AbdalaDiasse/Video-classification-for-oil-quality-estimation
https://github.com/Abdoulaye-Koroko/natural-gradients
https://github.com/AbhishekD15/Sentiment-Analysis_BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AdamStein97/Semi-Supervised-BERT-NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AgrawalAmey/safe-explorer
https://github.com/AhmedYounes94/Semi-supervised-BERT-NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Akanni96/feng-hirst-rst-parser
Two-pass Discourse Segmentation with Pairing and Global Features
https://github.com/AlCorreia/FABIR
https://github.com/AlexVerine/PrecisionRecallGan
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/AlexandraFilimokhina/MountainCarConrinious_DDPG
https://github.com/AlexeiKaplenko/FaceShifter_mine
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/AlexiaJM/Deep-learning-with-cats
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/AlexisAyme/estimateurs-robustes
Robust Estimators in High Dimensions without the Computational Intractability
https://github.com/AlextheEngineer/Ego2Hands
Ego2Hands: A Dataset for Egocentric Two-hand Segmentation and Detection
https://github.com/Alibaba-MIIL/TResNet
https://github.com/Alien9427/SAR_specific_models
Classification of Large-Scale High-Resolution SAR Images with Deep Transfer Learning
https://github.com/Alihassan7726/Fine-tuning-BERT-for-semantic-sentence-pairs-classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Alihassan7726/Multi-Class-classification-using-BERT-
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AmirSh15/FECNet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.