Image classification done with Mindspore technology
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Updated
Jan 24, 2021 - Python
Image classification done with Mindspore technology
Automatic Detection of Trypanosomosis in Thick Blood Smears Using Image Pre-processing and Deep Learning
Convert Pytorch model to Tensorflow lite model
First capstone project I worked on as part of the 'Programming in Python for AI' nanodegree at Udacity.
It is the image classification task to classify Diabetic-Retinopathy category using ResNet18, ResNet50 pretrained model. which is related to kaggle competition. The kaggle competition link can found below. https://www.kaggle.com/c/diabetic-retinopathy-detection#description
Dogs Image Classifier classifies pet images to dogs and not dogs and identify the breeds of the classified dogs using transfer learning via PyTorch pretrained models.
🔪 Elimination based Lightweight Neural Net with Pretrained Weights
detectron2 backbone: resnet18, efficientnet, hrnet, mobilenet v2, resnest, bifpn
A Python command line application that trains an image classifier on a given dataset and then using the trained model to predict new images.
This is a clean, opinionated and minimalist implementation of the training and evaluation protocols for a fancy new self supervised learning (SSL) method called maximum manifold capacity representations.
Training neural nets with quantized weights on arbitrarily specified bit-depth
Gender detection using gender classification model
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