Oct 2026· American Journal of Public Health· Vol 116 10, pp.
1557-1564
· 0 citations
Medicine
TL;DR
SCANNER Food demonstrates the feasibility and accuracy of using AI to identify food marketing in images and videos and may support surveillance of digital food marketing, evaluation of marketing policies, monitoring of industry compliance, and efforts to protect children and young adults.
Nutriverse is a mobile application designed to assist individuals in monitoring their daily nutritional intake through automated food recognition. The product specifically functions by identifying food items from images and estimating their nutritional composition in real time. The main issue addressed in this research...
Dani Nur Ramadhan Prayogi, R. Sadewa, Praditya Kumala Ari et al.· International Conferences on...· 0 citations
This review systematically compares CNNs, RNNs/LSTMs, Transformers, GNNs, GANs, and hybrid architectures, as well as transfer learning, self-supervised learning, contrastive learning, few-shot learning, lightweight networks, edge computing, and multimodal fusion.
Wei-Hao Wang, Zhi-Dan Jiang, Si-Si Yang et al.· Foods· 0 citations
A structured literature review of CNN-based food image classification studies published between 2020 and 2025 identifies persistent gaps in statistical validation, class imbalance treatment, explainability, reproducibility, public code availability and deployment-oriented evaluation.
Luka Leskovec, A. R. Borges, Fernanda Brito Correia et al.· Signal, Image and Video Proc...· 0 citations
Indonesia produces large volumes of fruits and vegetables yet faces high food loss and waste (FLW), with studies estimating 23-48 million tons of food waste annually. Observations in Grobogan Regency show traders discarding around 30-40% of daily stock, often produce that is edible but visually imperfect (grade B/C). T...
Dita Prameswari, Rheimanda Devin Emmanuel, Mar Atus Solikhah et al.· Edu Komputika Journal· 0 citations
The freshness of meat products is important for food safety and consumer health. Manual inspection methods are subjective and hard to scale, which leads to the need for automated vision-based solutions. This study compares six pretrained convolutional neural network architectures which are MobileNetV2, MobileNetV3, Eff...
Jovan Stefanus, Winsen Cristiano Sun, Maria Louisa Alfianto et al.· International Conferences on...· 0 citations
Modern smart kitchen automation requires reliable vision-based tools to provide user-advisory decision support during domestic culinary processes. However, standard deep learning models utilizing closed-set Softmax classifiers typically misclassify unknown or Out-of-Distribution (OOD) kitchen objects with high confiden...