Jeju Machine Learning Camp 2018
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Updated
Nov 14, 2018
Jeju Machine Learning Camp 2018
Building a model for predicting food images using the famous FOOD-101 dataset.
This GitHub repository contains instructions for downloading and utilizing the AI4Food-NutritionDB food image database, as well as different food recognition systems based on Xception and EfficientNetV2 architectures.
Food object detection with base Faster R-CNN TensorFlow model with k-fold cross validation, resulting in volume estimation and producing caloric data.
Image-based food segmentation for Deep Learning class at @unibo
Food Recognition using Generative Adversarial Networks
This android app takes food item image as input ,recognises the food item and calculates the nutrition value on the food , calories to be burned.
Food recognition using streamlit with inception v3 backend
AICrowd Food Recognition Challenge - Semantic Segmentation
Predict food (Fruits and Vegetables) images using Python
Creation of a model in DeepLearning for a detection and classification using Bounding Box. Using Keras and Tensorflow
Neural Network for recognising food items from its picture.
AI allergen detector using images, LogMeal API, and Firebase DB
FatLogger, an advanced Android application, has been developed to cater to the needs of users seeking precise nutritional information regarding their meals.
Automatically recognizing pictured dishes.
Fruit recognition backend. A part of https://github.com/Meshkat-Shadik/NutritionAppBackend for Nutrition APP.
Thesis Topic: Transfer Learning Based Food Item Recognition and Estimation of an Attributes.
Indonesian food recognition
Recognition of Russian food through deep learning
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