This paper delves into the innovative application of quantum computing to solve complex multi-die FPGA (FieldProgrammable Gate Array) routing challenges. Leveraging the Quantum Approximate Optimization Algorithm (QAOA...
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Software project management (SPM) is an important process in the software development (SD) industry, that involves the planning, organizing, and overseeing software application development. Kanban agile (KA) methodolo...
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In response to a growing demand for autonomous in-orbit operations and the pressing need for these operations to take place in an ever-widening set of environmental conditions, significant advancements have been made ...
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ISBN:
(纸本)9798350384529;9798350384512
In response to a growing demand for autonomous in-orbit operations and the pressing need for these operations to take place in an ever-widening set of environmental conditions, significant advancements have been made in the miniaturization and improvement of space-qualified sensing instrumentation. Yet, the effectiveness of vision-driven autonomous operations relies heavily on cameras with superior low-light performance and dynamic range, for which an optimal solution is yet to be found. Single-Photon Avalanche Diode (SPAD) sensors emerge as a potential solution, offering high light sensitivity and dynamic range even with diminutive pixel sizes. However, their high bandwidth and efficient integration with single-board computers requires bespoke interfaces and real-time processing power, typically enabled by Field Programmable Gate Arrays (FPGAs). This paper presents a dynamically reconfigurable onboard computer designed for efficient data processing and seamless integration into the first space-qualified camera leveraging a 1-megapixel SPAD sensor. Future endeavors entail developing a demonstrator capable of acquiring exceptionally sharp and high dynamic range imagery under some of the most complex illumination conditions found in space. This paper outlines the technological advancements and a roadmap toward revolutionizing spacecraft imaging capabilities, paving the way for enhanced image acquisition and data processing in time-sensitive, autonomous space operations.
multi-agent reinforcement learning (MARL) has demonstrated to be an attractive approach for addressing the challenge of multi-agent collaboration. Numerous existing MARL algorithms require hand-craft setting of explor...
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Score-based generative models like the diffusion model have been testified to be effective in modeling multi-modal data from image generation to reinforcement learning (RL). However, the inference process of diffusion...
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Direction of Arrival (DOA) estimation for the distributed array is a vital research direction in the field of array signal processing. However, as the distributed array become larger, the utilization of High-Precision...
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A real-time system that can decipher sign language from a live webcam stream is presented by the Sign Language Conversion Project. By using the Media Pipe library's landmark identification capabilities, the projec...
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Self-supervised deep learning has been widely exploited in seismic data denoising. However, most of the current methods take a single seismic profile to reconstruct two new similar profiles by sampling. Then, the two ...
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In order to enhance patient outcomes, rapid and precise detection approaches are needed for cardiovascular diseases (CVDs), which are among the top causes of death globally. By examining a wide range of demographic an...
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This research addresses the basic concern of inconsistency location in control frameworks through an in-depth investigation of time arrangement examination procedures, with a particular centre on the application of Lo...
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