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Parameter-Efficient Adaptation for Computational Imaging
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Deep learning-based methods provide remarkable performance in a number of computational imaging problems. Examples include end-to-end trained networks that map measurements to unknown signals, plug-and-play (PnP) methods that use pretrained denoisers as image prior, and model-based unrolled networks that train artifact removal blocks.
Nebiyou Yismaw +2 more
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Monomodal registration with adaptive parameter computing
International Journal of Computer Applications in Technology, 2011Most implementations for image registration are produced by defining a similarity measure between two given images, then minimising an energy functional that combines both similarity and regularity measures. The registration result greatly relies on the weight parameter, which usually is given in advance, big or small parameter may produce the ...
Murong Jiang +3 more
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Self-adaptive parameters in genetic algorithms
SPIE Proceedings, 2004Genetic algorithms are powerful search algorithms that can be applied to a wide range of problems. Generally, parameter setting is accomplished prior to running a Genetic Algorithm (GA) and this setting remains unchanged during execution. The problem of interest to us here is the self-adaptive parameters adjustment of a GA. In this research, we propose
Eric Pellerin +2 more
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Adaptive Parameter Estimation in LTI Systems
IEEE Transactions on Automatic Control, 2019An adaptive algorithm solving the on-line parameter estimation problem for a broad class of linear systems is proposed. The approach can be applied to systems with delay, distributed-parameter systems, fractional-order systems, and others that are stable or stabilized by linear feedback.
Mirna N. Kapetina +3 more
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Parallel genetic algorithm with parameter adaptation
Information Processing Letters, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shisanu Tongchim +1 more
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Parameter Adaptation Algorithms
2016Parameter adaptation algorithms are the key step for estimating the parameters of the discrete time dynamic model of the system to be controlled and for building an adaptive active vibration control system. A coverage of the subject is provided from the perspective of the user. Stability and convergence issues are addressed.
Ioan Doré Landau +3 more
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Utility-Based Adaptation of RED Parameters
2006Random Early Detection (RED) is effective in decreasing losses on responsive flows but performs poorly with User Datagram Protocol (UDP) traffic since these do not react to congestion notification. However, it is important to address UDP flows' requirements since UDP traffic forms a considerable part of Internet traffic.
Rachel P. Villacorta +1 more
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Parameter-adaptive Controllers
1981This chapter treats parameter-adaptive controllers which are based on suitable parameter estimation methods, controller design methods and control algorithms, c.f. chapter 23. The relevant parameter estimation methods were discussed in chapter 24 and 25.
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A systematic global stocktake of evidence on human adaptation to climate change
Nature Climate Change, 2021Gabrielle Wong-Parodi +2 more
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Navigating the continuum between adaptation and maladaptation
Nature Climate Change, 2023Emma Lisa Schipper +2 more
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