Recognizing Multiple Ingredients in Food Images Using a Single-Ingredient Classification Model

arXiv:2401.14579v3 Announce Type: replace
Abstract: Recognizing food images presents unique challenges due to the variable spatial layout and shape changes of ingredients with different cooking and cutting methods. This study introduces an advanced approach for recognizing ingredients segmented from food images. The method localizes the candidate regions of the ingredients using the locating and sliding window techniques. Then, these regions are assigned into ingredient classes using a CNN (Convolutional Neural Network)-based single-ingredient classification model trained on a dataset of single-ingredient …

abstract advanced arxiv challenges classification classification model cooking cs.cv food images multiple spatial study type