Abstract: We analyze the stability properties of stochastic linear systems in closed-loop with an optimal policy that minimizes a discounted quadratic cost in expectation. In particular, the linear ...

Abstract: With the expansive deployment of ground base stations, low Earth orbit (LEO) satellites, and aerial platforms such as unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs), the ...

Abstract: Remote sensing image fusion aims to generate a high-resolution multi/hyper-spectral image by combining a high-resolution image with limited spectral data and a low-resolution image rich in ...

Abstract: Integration of complementary information from different modalities and efficient computation is crucial in remote sensing (RS) image classification applications. Convolutional neural ...

Abstract: Time series classification is an important task in time series data mining, and has attracted great interests and tremendous efforts during last decades. However, it remains a challenging ...

Abstract: Multimodal federated learning (FL) targets the intersection of two promising research directions in Internet of Things (IoT) scenarios: 1) leveraging complementary multimodal information to ...

Abstract: Offset-based representation has emerged as a promising approach for modeling semantic relations between pixels and object motion, demonstrating efficacy across various computer vision tasks.

Abstract: Remote sensing change detection (RSCD) recognizes pixel-level change regions between images, while remote sensing change captioning (RSCC) describes the nature and properties of these ...

Abstract: Recently, Optimal Transport has been proposed as a probabilistic framework in Machine Learning for comparing and manipulating probability distributions. This is rooted in its rich history ...

Abstract: The joint optimization of production scheduling and resource constraints is critical to modern manufacturing systems. The number of auxiliary resources (fixtures) is usually insufficient in ...

Abstract: This study explores the potential of digital light processing to 3D print radioactive phantoms for high-resolution positron emission tomography (PET). Using a slightly modified desktop 3D ...