Face recognition technology is a biometric technology, which is based on the identification
of facial features of a person. People collect the face images, and the recognition equipment …

Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

Facial emotion recognition (FER) is a computer vision process aimed at detecting and
classifying human emotional expressions. FER systems are currently used in a vast range of …

The human face is considered the prime entity in recognizing a person's identity in our
society. Henceforth, the importance of face recognition systems is growing higher for many …

To deal with the issue of human face recognition on small original dataset, a new approach
combining convolutional neural network (CNN) with augmented dataset is developed in this …

Real-world face recognition applications often deal with suboptimal image quality or
resolution due to different capturing conditions such as various subject-to-camera distances …

Abstract Convolutional Neural Network models have reached extremely high performance
on the Face Recognition task. Mostly used datasets, such as VGGFace2, focus on gender …

Prostate cancer is one of the most identified cancers and second most prevalent among
cancer-related deaths of men worldwide. Early diagnosis and treatment are substantial to …

With the development of deep convolutional neural networks, the high-resolution image
classification has achieved excellent classification results. However, in natural scenes, low …