Face recognition (FR) is one of the most popular and long-standing topics in computer
vision. With the recent development of deep learning techniques and large-scale datasets …

One of the main challenges in feature learning using Deep Convolutional Neural Networks
(DCNNs) for large-scale face recognition is the design of appropriate loss functions that can …

In recent years, the enormous demand for computing resources resulting from massive data
and complex network models has become the limitation of deep learning. In the large-scale …

Recent years witnessed the breakthrough of face recognition with deep convolutional neural
networks. Dozens of papers in the field of FR are published every year. Some of them were …

Camera calibration involves estimating camera parameters to infer geometric features from
captured sequences, which is crucial for computer vision and robotics. However …

Pathologists use biopsies and microscopic examination to accurately diagnose breast
cancer. This process is time-consuming, labor-intensive, and costly. Convolutional neural …

Federated Learning (FL), which has been employed to train machine learning models on the
data with a distributed manner, could enhance the immersive user experience for the human …

The face detection technique has obtained significant development with the huge
application of convolutional neural networks. However, various types of occlusion are …

Undercarriage device is one of the essential parts of an aeroplane, and accurate detection
of whether the aeroplane undercarriage is operating normally can effectively avoid …

Rotation-Invariant Face Detection (RIPD) has been widely used in practical applications;
however, the problem of the adjusting of the rotation-in-plane (RIP) angle of the human face …