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Stars
Repository for collecting and categorizing papers outlined in our survey paper: "Large Language Models on Tabular Data -- A Survey".
A PyTorch Library for Multi-Task Learning
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
一键修改cursor 设备ID，解除设备锁定状态，为什么会有这个工具。。。因为我的设备被锁了。。。。
解决Cursor在免费订阅期间出现以下提示的问题: Your request has been blocked as our system has detected suspicious activity / You've reached your trial request limit. / Too many free trial accounts used on this machine.
A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis.
CloudMoe Windows 10/11 Activation Toolkit get digital license, the best open source Win 10/11 activator in GitHub. GitHub 上最棒的开源 Win10/Win11 数字权利（数字许可证）激活工具！
improve performance of skeleton data from kinect v2 body tracking sdk using unscented kalman filter
Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
A curated, public list of resources for biomechanics and human motion analysis: datasets, processing tools, software for simulation, educational videos, lectures, etc.
Information of public available data sets for biomechanics.
Import Neuracle data and event files in BDF format
Python library to run Kinect Azure DK SDK functions
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
Transformer: PyTorch Implementation of "Attention Is All You Need"
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
RepViT: Revisiting Mobile CNN From ViT Perspective [CVPR 2024] and RepViT-SAM: Towards Real-Time Segmenting Anything
code and trained models for "Attentional Feature Fusion"
isolated & continuous sign language recognition using CNN+LSTM/3D CNN/GCN/Encoder-Decoder
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
A long-term multi-subject sEMG dataset