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a-pytorch-tutorial-to-object-detection

SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection

abnormality-detection-in-mammography

aidenfather.github.io

Chris Blog

awesome-semantic-understanding-for-aerial-scene

A curated list of awesome resources for semantic understanding of aerial scene

bbavectors-oriented-object-detection

[WACV2021] Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

beautiful-jekyll

✨ Build a beautiful and simple website in literally minutes. Demo at https://beautifuljekyll.com

codes

cugraph

cuGraph - RAPIDS Graph Analytics Library

deep-learning-with-googlecolab

Deep Learning Applications (Darknet - YOLOv3, YOLOv4 | DeOldify - Image Colorization, Video Colorization | Face-Recognition) with Google Colaboratory - on the free Tesla K80/Tesla T4/Tesla P100 GPU - using Keras, Tensorflow and PyTorch.

deepsegmentor

A Pytorch implementation of DeepCrack and RoadNet projects.

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

faster_rcnn_for_dota

Code used for training Faster R-CNN on DOTA

forecastcovid19fatalities

ARIMA model to predict Covid19 Fatalities in US

gmic

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

image_segmentation_japan

This small tutorial is targeted at researchers that have basic machine learning and Python programming skills that want to implement instance image segmentation for further use in their models.

laneextraction

machine-learning-project_ames-house-price-prediction

map

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

mask-rcnn-pytorch

A PyTorch version of mask-rcnn based on torchvision model with VOC dataset format.

mask_rcnn

prediction using Mask RCNN

mean_average_precision

Mean Average Precision for Object Detection

mganet

[ICIP2021] The official PyTorch implementation of MASK GUIDED ATTENTION FOR FINE-GRAINED PATCHY IMAGE CLASSIFICATION

non-max-suppression

Function to perform Non Max Suppression

pixel_level_land_classification

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

present

Code from Jeff Heaton's YouTube videos, articles, and conference presentations.

pretrained-models.pytorch

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

pytorch-image-classification

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

pytorch-simple-maskrcnn

A PyTorch implementation of simple Mask R-CNN

pytorch_image_classification

PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet

pytorchcnn

Implementing CNN in PyTorch with Custom Dataset and Transfer Learning