First, the difference image (DI) of the bitemporal hyperspectral images (Bi-HSIs) is obtained through pixel-by-pixel and band-by-band subtraction operations. Then, the LRSR model is designed as a deep ...

Weather image classification is a critical component of the vision systems in autonomous driving systems (ADSs), facilitating accurate decision-making across diverse driving conditions. Adverse ...

High-resolution remote sensing image (HRSI) scene classification often faces challenges; for example, the intraclass similarity is low, but the interclass similarity is high due to complex backgrounds ...

The basis of image forensics is passive image forgery detection. Passive forgeries such as image splicing, copy-move, and retouching are often used techniques that compromise the authenticity of an ...

In recent years, convolutional neural networks (CNNs) have been impressive due to their excellent feature representation abilities, but it is difficult to learn long-distance spatial structures ...

One of the known computer vision tasks is image recognition and classification. Computer vision - a field that automates tasks and works with multi - dimensional data, when combined with the power of ...

The classification of human actions has become an important topics in recent researches. Typically the function of recognition human action is converted to the function of classifying the image that ...

The study of computer systems and software that can recognize and understand scenes and images is known as computer vision. Image recognition, object detection, image synthesis, image super resolution ...

Machine learning and deep learning techniques are used in image classification. The execution of a classification system is based on the quality of extracted image features. This paper deals with the ...

Recently, contrastive learning (CL) has shown excellent performance in the hyperspectral image (HSI) classification. However, existing CL-based methods face two specific challenges: 1) multiview ...

This article introduces a novel automatic multiple vehicle detection and tracking framework that combines successfully computer vision to partial differential equation (PDE) - based models. Its ...

In this paper, three types of convolution operations in convolutional neural networks (CNNs) are studied including regular convolution, separable convolution and group convolution. For regular ...