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Titlebook: Smart Multimedia; Second International Troy McDaniel,Stefano Berretti,Anup Basu Conference proceedings 2020 Springer Nature Switzerland AG

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发表于 2025-3-25 05:51:35 | 显示全部楼层
Sethuraman Panchanathan,Ramin Tadayon,Troy McDaniel,Vipanchi Chachamscillators, filters, butalso complete transceiver front-ends, are discussed and analyzed in amethodological way, and their modeling and simulation, both at thecircuit level and at the architectural level, are treated. In thisway, the eleven contributions of this book combine in a unique waydesigns with method978-1-4757-8396-4978-0-306-48089-8
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Pedro Ponce,Edgar Omar Lopez,Arturo Molinascillators, filters, butalso complete transceiver front-ends, are discussed and analyzed in amethodological way, and their modeling and simulation, both at thecircuit level and at the architectural level, are treated. In thisway, the eleven contributions of this book combine in a unique waydesigns with method978-1-4757-8396-4978-0-306-48089-8
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Bijan Fakhri,Troy McDaniel,Heni Ben Amor,Hemanth Venkateswara,Abhik Chowdhury,Sethuraman Panchanathascillators, filters, butalso complete transceiver front-ends, are discussed and analyzed in amethodological way, and their modeling and simulation, both at thecircuit level and at the architectural level, are treated. In thisway, the eleven contributions of this book combine in a unique waydesigns with method978-1-4757-8396-4978-0-306-48089-8
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Xuzhan Chen,Youping Chen,Homayoun Najjaranin CMOS SRAMS and DRAMS.. Low-power on-chip voltage down converter design..Numerous advanced CMOS subsystems (e.g. adders, multipliers, datapath, memories, regular structures, phase-locked loops) with severaldesign options trading power, delay and area .. Low-power designmethodology, power estimatio
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Background Subtraction by Difference Clustering time, resulting in a real-time algorithm. Experiments on several videos from standard benchmarks demonstrate that our proposed approach achieves promising results compared to several previous methods.
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Semantic Learning for Image Compression (SLIC)ps are tailored to make the encoder content-aware for a given image. In the proposed work, we present a novel architecture developed specifically for image compression, which generates a semantic map for salient regions so that they can be encoded at higher quality as compared to background regions.
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Background Subtraction Based on Principal Motion for a Freely Moving Cameragy is proposed to integrate the foreground results captured from the angle as well as the magnitude. Experiments based on several videos from standard benchmark datasets illustrate that the proposed method achieves promising performance compared to the state-of-the-art.
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