ODIR-2019. Ocular Disease Intelligent Recognition Through Deep Learning Architectures
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Updated
Mar 5, 2023 - Jupyter Notebook
ODIR-2019. Ocular Disease Intelligent Recognition Through Deep Learning Architectures
Implementation of the model-agnostic meta-learning framework on CWRU bearing fault dataset to address cross-domain few-shot fault diagnosis problem.
Thesis work, University of Groningen : Lifelong 3D Object Recognition and Grasp Synthesis using Dual Memory Recurrent Self-Organization Networks
A machine learning tool built with TensorFlow and the VGG16 model. It classifies waste items from images, assisting in efficient recycling. Users upload waste images, and the system identifies the waste type.
Göz görüntülerinde diyabetik retinopati belirtilerinin tespiti
Incremental Learning using MobileNetV2 of Logo Dataset
Classifying various food using transfer learning.
An image classifier developed for ImageNet dataset
An end-to-end CNN Image Classification Model which identifies the food in your image
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