Abstract: The research is devoted to the development of an automated face recognition system based on a convolutional neural network (CNN). The proposed system uses modern methods of image ...
Abstract: This paper proposes Context-Aware Facial Expression Network (CAFE-Net), a deep learning framework for facial expression recognition. It integrates a Context Enhancement module (CEM) to ...
Abstract: Pose variation in unconstrained settings challenges face recognition, especially for side-view poses, which are affected by asymmetry, self-occlusion, and limited facial features. While deep ...
Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a deep learning algorithm that ...
A few Senate Democrats introduced a bill called the ‘‘ICE Out of Our Faces Act,” which would ban Immigration and Customs Enforcement (ICE) and Customs and Border Protection (CBP) from using facial ...
Federal troops are increasingly turning to high-tech tracking tools that push the boundaries of personal privacy ...
Abstract: Aiming at the problems that the license plate recognition system is susceptible to illumination change, viewing angle tilt and noise interference in complex environments, a collaborative ...
Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is defined by persistent social interaction and communication difficulties, along with limited interests, repetitive ...
Abstract: In India, countless children are reported missing every year, with a significant percentage remaining untraced due to challenges in identification and limited resources. This project ...
Abstract: In today's rapidly advancing era of intelligence and digitalization, gesture recognition, as a natural and efficient interaction method, has become an important research direction in the ...
Abstract: The framework proposed in this study is a Multimodal Biometric Authentication Framework which provides extremely accurate and reliable identification by combining face, hand, and iris traits ...
Abstract: To address the performance degradation of radar modulation recognition under low Signal-to-Noise Ratio (SNR) conditions, this paper proposes a Denoising-Classification MultiTask Learning ...