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This repo contains implementation of deep learning-based steel surface defect segmentation models.
This research enhances early disease diagnosis by analyzing retinal blood vessels in fundus images using deep learning. It employs eight pre-trained CNN models and Explainable AI techniques.
End-to-end deep learning pipeline to classify images of dogs and humans to determine what breed the human or dog most resembles
A collection of CNN models are trained on Cloud TPU by using PyTorch/XLA
Solutions to the Advanced CNN course by the Lazy Programmer and all CNN Models I've worked on
Appolo's Ear is an ensemble of three music genre classification neural networks, a nginx server, and a demonstrative react frontend. Its backend is glued together with Docker and Docker compose.
An end-to-end CNN Image Classification Model which identifies the bird in your image
Food image recognition using deep learning in climate change issue
CNN - object detection, classification & various model tuning for prediction optimization
This is an image classification project which was carried out during "Applied Machine Learning and Data Science" in Indian Institute of Technology, Kanpur
A wrapper library over several open source cnn models for tensorflow -2.x.
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
A collection of deep learning models for rice classification using PyTorch, torchvision, and scikit-learn, with performance metrics evaluated using Slurm jobs.