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This dataset is a port of the "Animal Image Dataset" that you can find on Kaggle. The dataset contains 60 pictures for 90 types of animals, with various image sizes.

The goal was to test the effectiveness of SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation. The version with the variational auto-encoder was very bad and basically …

Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Flexible Data Ingestion.

Formally, image segmentation refers to the process of partitioning an image into a set of pixels that we desire to identify (our target) and the background. Specifically, in this tutorial we...

Oct 6, 2023 · Image segmentation refers to the ability of computers (or more accurately models stored on computers) to take an image and assign each pixel in the image to a corresponding category.

May 19, 2020 · Hopefully, this article gave you some background into image segmentation tips and tricks and given you some tools and frameworks that you can use to start competing.

This project demonstrates an end-to-end image classification task using 2 different Convolutional Neural Networks (CNN) models. The goal of this project is to classify 10 different animals based on images.

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Jun 27, 2023 · In this 4-part series, we’ll implement image segmentation step by step from scratch using deep learning techniques in PyTorch. We’ll start the series with the basic concepts and ideas needed …