imskyszy

imskyszy's Stars

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook15.3k1124201.4k

• mamoe/mirai

  高效率 QQ 机器人支持库

  Language:Kotlin14.6k1352k2.5k

• ShiArthur03/ShiArthur03

  Language:MATLAB10.3k321.4k1.9k

• nonebot/nonebot

  基于 OneBot 标准的 Python 异步 QQ 机器人框架 / Asynchronous QQ robot framework based on OneBot for Python

  Language:Python2.1k34215338

• AberHu/Knowledge-Distillation-Zoo

  Pytorch implementation of various Knowledge Distillation (KD) methods.

  Language:Python1.6k2317269

• qiuqiangkong/audioset_tagging_cnn

  Language:Python1.4k1469259

• LetheSec/HuggingFace-Download-Accelerator

  利用HuggingFace的官方下载工具从镜像网站进行高速下载。

  Language:Python91033183

• pengzhiliang/Conformer

  Official code for Conformer: Local Features Coupling Global Representations for Visual Recognition

  Language:Jupyter Notebook55774188

• harritaylor/torchvggish

  Pytorch port of Google Research's VGGish model used for extracting audio features.

  Language:Python37982368

• fschmid56/EfficientAT

  This repository aims at providing efficient CNNs for Audio Tagging. We provide AudioSet pre-trained models ready for downstream training and extraction of audio embeddings.

  Language:Python24953144

• RoyChao19477/SEMamba

  This is the official implementation of the SEMamba paper. (Accepted to IEEE SLT 2024)

  Language:Python157122015

• JusperLee/SPMamba

  Language:Python14332119

• kaistmm/Audio-Mamba-AuM

  Official Implementation of the work "Audio Mamba: Bidirectional State Space Model for Audio Representation Learning"

  Language:Python1187413

• Thvnvtos/SNN-delays

  Official implementation of "Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings" [ICLR2024]

  Language:Python51417

• umbertocappellazzo/PETL_AST

  This is the official repository of the papers "Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers" and "Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of Adapters".

  Language:Python37613

• judiebig/DR-DiffuSE

  Revisiting Denoising Diffusion Probabilistic Models for Speech Enhancement: Condition Collapse, Efficiency and Refinement, Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023.

  Language:Python35253

• SarthakYadav/audio-mamba-official

  Official implementation for our paper "Audio Mamba: Selective State Spaces for Self-Supervised Audio Representations"

  Language:Python33200

• Hadryan/TFNet-for-Environmental-Sound-Classification

  Learning discriminative and robust time-frequency representations for environmental sound classification: Convolutional neural networks (CNN) are one of the best-performing neural network architectures for environmental sound classification (ESC). Recently, attention mechanisms have been used in CNN to capture the useful information from the audio signal for sound classification, especially for weakly labelled data where the timing information about the acoustic events is not available in the training data, apart from the availability of sound class labels. In these methods, however, the inherent time-frequency characteristics and variations are not explicitly exploited when obtaining the deep features. In this paper, we propose a new method, called time-frequency enhancement block (TFBlock), which temporal attention and frequency attention are employed to enhance the features from relevant frames and frequency bands. Compared with other attention mechanisms, in our method, parallel branches are constructed which allow the temporal and frequency features to be attended respectively in order to mitigate interference from the sections where no sound events happened in the acoustic environments. The experiments on three benchmark ESC datasets show that our method improves the classification performance and also exhibits robustness to noise.

  Language:Python28304

• SY-Xuan/DSCL

  AAAI-24 Decoupled Contrastive Learning for Long-Tailed Recognition

  Language:Python23240

• stanfordmlgroup/selfsupervised-lungandheartsounds

  Language:Python17714

• kaen2891/bts

  (INTERSPEECH 2024) Official Implementation of "BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification"

  Language:Python15340

• kaen2891/stethoscope-guided_supervised_contrastive_learning

  (ICASSP 2024) Official Implementation of "Stethoscope-guided Supervised Contrastive Learning for Cross-domin Adaptation on Respiratory Sound Classification"

  Language:Python12230

• ChihchengHsieh/multimodal-abnormalities-detection

  Language:Jupyter Notebook11401

• MichaelLynn1996/AAT

  Language:Python8110

• ta012/DTFAT

  DTFAT code and pre-trained weights

  Language:Python8020

• ta012/MaxAST

  MaxAST code

  Language:Python8102

• PLAN-Lab/uamix-MAE

  6200

• fatetail/MetaNet

  ISBI2020

  Language:Python4110

• danelee2601/SpecMix_torch

  (not official) pytorch implementation of SpecMix, an augmentation method

  Language:Python3200

• jczhang02/VGG_audiovisual_torch

  Pytorch implemention of VGG16 and VGGish models

  Language:Python2100