Food object detection with base Faster R-CNN TensorFlow model with k-fold cross validation, resulting in volume estimation and producing caloric data.
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Updated
Nov 21, 2020 - Python
Food object detection with base Faster R-CNN TensorFlow model with k-fold cross validation, resulting in volume estimation and producing caloric data.
Codebase for "On the relationship between calibrated predictors and unbiased volume estimation" (MICCAI 2021).
Source code of "Network-Wide Routing-Oblivious Heavy Hitters" paper by Ran Ben Basat, Gil Einziger, Shir Landau Feibish, Jalil Moraney, and Danny Raz (ACM/IEEE ANCS 2018).
The final project of "Applying AI to 3D Medical Imaging Data" from "AI for Healthcare" nanodegree - Udacity.
This is a comprehensive application that utilizes advanced machine learning models to estimate the volume of food from images, identify the type of food, and provide a detailed nutritional analysis.
Final year project which deals with object volume estimation from a single 2D image.
Volume Approximation and Design Centering with Lp-Adaption
Byte-Mi is based on the Mask-RCNN model
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