Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …

The management of daily food intake aids to preserve a healthy body, minimize the risk of
many diseases, and monitor chronic diseases, such as diabetes and heart problems. To …

Purpose In the reduction of food waste and the provision of food to the hungry, food banks
play critical roles. However, as they are generally run by charitable organisations that are …

Most multilayer Moore–Penrose inverse (MPI)-based neural networks, such as deep random
vector functional link (RVFL), are structured with two separate stages: unsupervised feature …

Training neural networks with the Moore–Penrose (MP) inverse has recently gained
attention in view of its noniterative training nature. However, a significant drawback of …

High-frequency surface wave radar (HFSWR) has become the cornerstone of maritime
surveillance because of its low-cost maintenance and coverage of wide area. However …

The multilayer one-class classification (OCC) frameworks have gained great traction in
research on anomaly and outlier detection. However, most multilayer OCC algorithms suffer …

With the rapid development of food production and health management, analyses of food
samples have been essential for preventing diseases and understanding human culture …

Global eating habits cause health issues leading people to mindful eating. This has directed
attention to applying deep learning to food-related data. The proposed work develops a new …

In this article, we present an optimal edge-weighted graph semantic correlation (EWGSC)
framework for multi-view feature representation learning. Different from most existing multi …