Abstract: This paper proposes an effective infrared and visible image fusion method based on a texture conditional generative adversarial network (TC-GAN). The constructed TC-GAN generates a combined ...

Abstract: Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question ...

Abstract: Object 3D reconstruction from a single-view image is an ill-posed problem. Inferring the self-occluded part of an object makes 3D reconstruction a challenging and ambiguous task. In this ...

Abstract: In this paper, we propose a just noticeable distortion (JND)-based perceptual rate control method for high efficiency video coding (HEVC). First, the JND factor of a coding unit has been ...

Abstract: The system frequency response (SFR) model describes the average network frequency response after a disturbance and has been applied to a wide variety of dynamic studies. However, the ...

Abstract: Due to the current structure of digital factory, it is necessary to build the smart factory to upgrade the manufacturing industry. Smart factory adopts the combination of physical technology ...

Abstract: A robust output regulation of a control system aims at disturbance rejection and reference tracking in the presence of uncertainties. Technically, the control design contains two mechanisms: ...

Abstract: We develop an efficient general-purpose blind/no-reference image quality assessment (IQA) algorithm using a natural scene statistics (NSS) model of discrete cosine transform (DCT) ...

Abstract: This article investigates the problem of event-triggered secure path tracking control of autonomous ground vehicles (AGVs) under deception attacks. To relieve the burden of the shareable ...

Abstract: We review both widely used methods and new techniques proposed in the recent literature. The basic concepts, categories, open issues, and challenges related to CD in HS images are discussed ...

Abstract: This survey presents a comprehensive overview of machine learning methods for cybersecurity intrusion detection systems, with a specific focus on recent approaches based on deep learning (DL ...

Abstract: Due to the artificial division of a machine performance state and unpredictable external working conditions, the performance and state transition strength of multistate machines (that is, ...