Abstract: This paper addresses unsupervised change detection by proposing a proper framework for a formal definition and a theoretical study of the change vector analysis (CVA) technique. This ...
Abstract: Remaining useful life (RUL) prediction of lithium-ion batteries can assess the battery reliability to determine the advent of failure and mitigate battery risk. The existing RUL prediction ...
Abstract: The Global Precipitation Measurement (GPM) mission is an international satellite mission that uses measurements from an advanced radar/radiometer system on a core observatory as reference ...
Abstract: Mobile edge computing has risen as a promising technology for augmenting the computational capabilities of mobile devices. Meanwhile, in-network caching has become a natural trend of the ...
2023 IEEE/CVF International Conference on Computer Vision (ICCV) Location: Paris, France 2021 IEEE/CVF International Conference on Computer Vision (ICCV) Location: Montreal, QC, Canada 2019 IEEE/CVF ...
Abstract: Melanoma, most threatening type of skin cancer, is on the rise. In this paper an implementation of a deep-learning system on a computer server, equipped with graphic processing unit (GPU), ...
Abstract: This paper proposes a distributed nonlinear consensus delay-dependent control algorithm for a connected vehicle (CV) platoon. In particular, considering that the behavior of the following ...
Abstract: Symmetry is ubiquitous in nature, physics, and mathematics. However, a classical symmetry-agnostic reinforcement learning (RL) approach cannot guarantee to respect symmetry. Researchers have ...
Abstract: The Universal Verification Methodology (UVM) that can improve interoperability, reduce the cost of using intellectual property (IP) for new projects or electronic design automation (EDA) ...
Abstract: The Generative Pre-trained Transformer (GPT) represents a notable breakthrough in the domain of natural language processing, which is propelling us toward the development of machines that ...
Abstract: For hyperspectral image (HSI) classification, two branch networks generally use convolutional neural networks (CNNs) to extract the spatial features and long short-term memory (LSTM) to ...
Abstract: Feature extraction is of significance for hyperspectral image (HSI) classification. Compared with conventional hand-crafted feature extraction, deep learning can automatically learn features ...
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