Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...

An estimated 100 million people live with facial differences. As face recognition tech becomes widespread, some say they’re ...

Abstract: The ability to accurately identify and decipher traffic signs is a major obstacle on the road to widespread adoption of autonomous vehicles. While advanced algorithms are constantly evolving ...

Abstract: Recently, cross-domain few-shot facial expression recognition (CF-FER), which identifies novel compound expressions with a few images in the target domain by using the model trained only on ...

Abstract: Face recognition is widely used in Internet of Thingss (IoTs) applications, such as time and attendance systems, security systems, etc. Due to the limited storage and computing power of IoT ...

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Abstract: In recent years, facial recognition technology has seen rapid advancements and is now extensively utilized in security surveillance and financial transactions. The face recognition process ...

Abstract: The Project Attendance System leverages advanced face recognition technology to streamline the process of recording and managing attendance in various settings, such as educational ...

Abstract: Conventional smoke detectors are prone to high false alarm rates, particularly in complex environments such as kitchens, where cooking smoke or water vapor often triggers alarms. This study ...

Doncaster, England (CNN) — Five young women are staring anxiously at a laptop. This is the call they’ve long been waiting for. A flurry of mixed emotions takes over as they each learn they have been ...

Abstract: This paper addresses the continuous Human Activity Recognition (HAR) problem using acoustic sensors, which finds application in aged population health and well-being monitoring. The ...