Neuroimaging Informatics Technology Initiative (NIfTI) RM (T1w & T2-FLAIR) segmentation of epilectic seizures using YOLOv8
-
Updated
May 19, 2024 - Python
Neuroimaging Informatics Technology Initiative (NIfTI) RM (T1w & T2-FLAIR) segmentation of epilectic seizures using YOLOv8
Diagnosing ‘silent’ heart attack using ECG waveforms (A Nightingale Open Science dataset)
Transforming 2D images into 3D semantically segmented scenes using innovative CNN architecture and COLMAP reconstruction.
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.
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.
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!
Unsupervised video summarization with deep(GAN) reinforcement learning
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
Add a description, image, and links to the cnn-pytorch topic page so that developers can more easily learn about it.
To associate your repository with the cnn-pytorch topic, visit your repo's landing page and select "manage topics."