Automatic Detection of Trypanosomosis in Thick Blood Smears Using Image Pre-processing and Deep Learning
-
Updated
Sep 12, 2021 - Python
Automatic Detection of Trypanosomosis in Thick Blood Smears Using Image Pre-processing and Deep Learning
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.
Convert Pytorch model to Tensorflow lite model
A Python command line application that trains an image classifier on a given dataset and then using the trained model to predict new images.
Gender detection using gender classification model
Training neural nets with quantized weights on arbitrarily specified bit-depth
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.
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
First capstone project I worked on as part of the 'Programming in Python for AI' nanodegree at Udacity.
🔪 Elimination based Lightweight Neural Net with Pretrained Weights
Image classification done with Mindspore technology
detectron2 backbone: resnet18, efficientnet, hrnet, mobilenet v2, resnest, bifpn
Add a description, image, and links to the resnet18 topic page so that developers can more easily learn about it.
To associate your repository with the resnet18 topic, visit your repo's landing page and select "manage topics."