An end-to-end CNN Image Classification Model which identifies the food in your image
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Updated
Jul 17, 2024 - Jupyter Notebook
An end-to-end CNN Image Classification Model which identifies the food in your image
A neural network that can identify 101 different foods from an image. The "Final Model" section contains model weights for EfficientNetB2 + a classifier block that gives a top-1 accuracy of 73.2% and a top-5 accuracy of 91.2%. The models are all trained on the Food101 dataset.
An implementation of one personal project to gain experience with Generative Adversarial Network models and in particular on Wasserstrein GAN with gradient penalty. The final application's purpose is to generate synthetic images given a food category.
(Pattern Recognition Letters 2023) PyTorch implementation of "Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer"
Food 101 Classification Model
CNN Image Classification Model which identifies the food in your image
a web App and Mobile app to classify food dishes and then to display recipe of that food
Deep Food Image Recognition Project
Gives the solution of Food101 Kaggle problem
A Food image classification of 101 classes with EfficientNetB0 and streamlit
An example of Chainer software that use Food-101 dataset
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