To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...

Conservation has long wrestled with a deceptively simple question: not whether to act, but where action will matter most. Forest restoration, protected areas, wildlife corridors, and enforcement ...

AI-enhanced optical spectroscopy revolutionizes food quality monitoring with rapid, non-destructive analysis, ensuring safety and reducing waste in production.

In an era where artificial intelligence (AI) and machine learning (ML) are driving unprecedented innovation and efficiency, a ...

Abstract: A device-free methodology is proposed to recognize the human activity in indoor environments using WiFi received signal strength indication (RSSI), and several machine learning (ML) ...

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...

Abstract: In the recent past, recognizing and tracking uncharacteristic behavior in elderly people is essential due to ageing. According to the survey of World Health Organization (WHO), by 2030, 1 in ...

Division of Applied Chemistry, Faculty of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan ...