https://github.com/mindspore-ai/models/blob/master/research/cv/ibnnet
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
Papers with Code 아카이브
Speech Emotion Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 17
- 보존된 평가 기록
- 48
Speech Emotion Recognition is a task of speech processing and computational paralinguistics that aims to recognize and categorize the emotions expressed in spoken language. The goal is to determine the emotional state of a speaker, such as happiness, anger, sadness, or frustration, from their speech patterns, such as prosody, pitch, and rhythm.
For multimodal emotion recognition, please upload your result to Multimodal Emotion Recognition on IEMOCAP
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mindspore-ai/models/tree/master/official/nlp/transformer
https://github.com/mindspore-ai/models/tree/master/research/cv/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/mindspore-ai/models/tree/master/research/cv/ICNet
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
https://github.com/mindspore-ai/models/tree/master/research/cv/NFNet
High-Performance Large-Scale Image Recognition Without Normalization
https://github.com/mindspore-ai/models/tree/master/research/cv/RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/mindspore-ai/models/tree/master/research/hpc/deepbsde
Solving high-dimensional partial differential equations using deep learning
https://github.com/mindspore-courses/Deep-Reinforcement-Learning-Algorithms-with-MindSpore
https://github.com/mindspore-courses/Deep-Tutorials-for-MindSpore
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/PolarizedSelfAttention.py
Polarized Self-Attention: Towards High-quality Pixel-wise Regression
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/SelfAttention.py
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/UFOAttention.py
UFO-ViT: High Performance Linear Vision Transformer without Softmax
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/conv/HorNet.py
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions
https://github.com/mindspore-lab/mindone
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/ming024/FastSpeech2
https://github.com/mingtaoguo/biggan-tensorflow
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/mingyuliutw/UNIT
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/mingzehuang/latentcor
High Dimensional Semiparametric Latent Graphical Model for Mixed Data
https://github.com/minus31/Portrait-segmentation
Boundary-Aware Network for Fast and High-Accuracy Portrait Segmentation
https://github.com/minyoungg/GAN-Transform-and-Project
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/minyoungg/pix2latent
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/mit-han-lab/sparsevit
SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer
https://github.com/mithunpaul08/bert_tensorflow
https://github.com/mitran27/Attention-is-all-you-Need
https://github.com/mks0601/PoseFix_RELEASE
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/mlpc-ucsd/PRTR
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/moabarar/nemar
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/modelscope/FunCodec
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT
https://github.com/moein-shariatnia/Pix2Seq
https://github.com/mohanliu/HRnet-semantic-segmentation-exp
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/monimoyd/NLPEnglishToPythonCodeUsingTransformer
https://github.com/monimoyd/NLPMachineTranslationUsingTransformer
https://github.com/montaserFath/Reinforcement-Learning-for-Prosthetics
https://github.com/moon23k/Scheduled_Sampling
https://github.com/moon23k/Transformer_Anchors
https://github.com/moon23k/Transformer_Archs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.