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Image Matching Based on image Fusion and Hopfield Neural Network
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作者 zhenghao shi Yaning Feng 《通讯和计算机(中英文版)》 2005年第11期24-28,共5页
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Pickering aqueous foam templating:a promising strategy to fabricate porous waterborne polyurethane coatings
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作者 Jianhui Wu Jiajing Zhou +3 位作者 zhenghao shi Chunhua Wang To Ngai Wei Lin 《Collagen and Leather》 EI CAS 2023年第3期44-47,共4页
Waterborne polyurethane(WPU)has been widely used as coatings in industrial fields ranging from wood,real/synthetic leather,and textiles,because it exhibits versatile performance,excellent eco-friendliness,and superior... Waterborne polyurethane(WPU)has been widely used as coatings in industrial fields ranging from wood,real/synthetic leather,and textiles,because it exhibits versatile performance,excellent eco-friendliness,and superior film-forming property.In terms of wearable products,compact WPU coatings often cause discomfort due to the intrinsic poor vapor transmission. 展开更多
关键词 property. WEAR POLYURETHANE
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Algorithm Contest of Calibration-free Motor Imagery BCI in the BCI Controlled Robot Contest in World Robot Contest 2021:A survey
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作者 Jing Luo Qi Mao +2 位作者 Yaojie Wang zhenghao shi Xinhong Hei 《Brain Science Advances》 2022年第2期127-141,共15页
Objective:From September 10 to 13,2021,the finals of the BCI Controlled Robot Contest in World Robot Contest 2021 were held in Beijing,China.Eleven teams participated in the Algorithm Contest of Calibration-free Motor... Objective:From September 10 to 13,2021,the finals of the BCI Controlled Robot Contest in World Robot Contest 2021 were held in Beijing,China.Eleven teams participated in the Algorithm Contest of Calibration-free Motor Imagery BCI.The participants employed both traditional electroencephalograph(EEG)analysis methods and deep learning-based methods in the contest.In this paper,we reviewed the algorithms utilized by the participants,extracted the trends and highlighted interesting approaches from these methods to inform future contests and research recommendations.Method:First,we analyzed the algorithms in separate steps,including EEG channel and signal segment setup,prepossessing technology,and classification model.Then,we emphasized the highlights of each algorithm.Finally,we compared the competition algorithm with the SOTA algorithm.Results:The algorithm employed in the finals performed better than that of the SOTA algorithm.During the final stage of the contest,four of the top five teams used convolutional neural network models,suggesting that with the rapid development of deep learning,convolutional neural network-based models have been the most popular methods in the field of motor imagery BCI. 展开更多
关键词 brain-computer interface motor imagery con-volutional neural network World Robot Contest
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