Transforming 2D images into 3D semantically segmented scenes using innovative CNN architecture and COLMAP reconstruction.

心律失常检测/ECG信号分类

Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"

HAM10000 Skin Lesion Classification

A comparative analysis of deep learning algorithms for multi label image classification using microscopic images.

Neuroimaging Informatics Technology Initiative (NIfTI) RM (T1w & T2-FLAIR) segmentation of epilectic seizures using YOLOv8

This is a warehouse for DLinear-Pytorch-model, can be used to train your text dataset for time series forecasting tasks.

Development for peak detection at CXLS/CXFEL. Mainly focusing on deep learning CNN networks.

The third phase of the 'Deep Learning' course I took on Udemy.

Custom deep learning architectures for Sentiment Analysis and Image Classfication

Profile Face Recognition project

A suite of Python scripts allowing the end-user to use Deep Learning to detect objects in georeferenced raster images.

Diagnosing ‘silent’ heart attack using ECG waveforms (A Nightingale Open Science dataset)

This project utilizes various computer vision techniques to track two tennis players, a court's key-points, and a tennis ball. It also measures the players' ball shot speed, movement speed and number of shots that they have taken.

Convolutional Neural Network(CNN) image classification models developed using the PyTorch library of Python!

Analyzing and predicting the demand for bikes using a Spatio-Temporal Graph Convolutional Network (STGCN) model.

Automate handwritten multiple-choice test grading with HMC-Grad, using a CNN trained in PyTorch on the EMNIST dataset and OpenCV for image processing. Input the correction key and the images of the answer sheets to receive each one's correctness and score, along with item and score analysis, in CSV and XLSX formats, and the annotated images as JPG.

CNN for predicting crop yield

Dock2D: Synthetic datasets for the molecular recognition problem

Unsupervised video summarization with deep(GAN) reinforcement learning