ResNet Comparison for Garbage Image Classification with PyTorch - models trained on GPU, then pickled for analysis on CPU
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Updated
Sep 29, 2022 - Jupyter Notebook
ResNet Comparison for Garbage Image Classification with PyTorch - models trained on GPU, then pickled for analysis on CPU
Handwritten Bangla Numeric Digits Classification using ResNet-34. The work uses a subset of the BanglaLekha-Isolated dataset. For details, read the README file.
A CLI tool that utilizes a ResNet convolutional neural network to recognize content in images and sort them into classes.
This notebook was curated as a part of Severstal Steel Detection Challenge by Kaggle . It gives an starter code for coding multiclass classifier using Pytorch
A deep learning approach to classify alphabets of the American Sign Language
Convolutional Neural Network written with PyTorch to diagnostic COVID19 based on recorded coughs.
ResNet-34 gender classification implemented with PyTorch
Sorry, This repository has become a tmp. See <MyResNet> Repo. [Jan 19 2024]
This repo contains my attempt of applying various CV techniques and algorithms
This was a simple deep learning image classification project. The dataset was taken from Kaggle and trained using the ResNet 9 model (Build from Scratch) and ResNet 34 model (using Transfer Learning).
Trained the ResNet50 model from scratch on the imagewoof dataset. Reached 83% accuracy
Plant Disease Classification using ResNet
A light-hearted production ready image classifier trained using a convolutional neural network with resnet-34 architecture on 150 images returned by Bing Image Search API queries of bears.
Traffic-sign images classification using ResNet-34 CNN
A streamlined image classifier using to accurately identify distinct sports ball.
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