Titlebook: Minimum Error Entropy Classification; Joaquim P. Marques de Sá,Luís M.A. Silva,Luís A. A Book 2013 Springer-Verlag Berlin Heidelberg 2013

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書目名稱Minimum Error Entropy Classification影響因子(影響力)




書目名稱Minimum Error Entropy Classification影響因子(影響力)學(xué)科排名




書目名稱Minimum Error Entropy Classification網(wǎng)絡(luò)公開度




書目名稱Minimum Error Entropy Classification網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Minimum Error Entropy Classification被引頻次




書目名稱Minimum Error Entropy Classification被引頻次學(xué)科排名




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書目名稱Minimum Error Entropy Classification讀者反饋




書目名稱Minimum Error Entropy Classification讀者反饋學(xué)科排名

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調(diào)情

Book 2013 neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions..

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使長胖

Joaquim P. Marques de Sá,Luís M.A. Silva,Luís A. APresents data classification methodologies based on a minimum error entropy approach.Includes both theoretical results and applications to real world datasets.Written by leading experts in the field

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A Scale-Aware YOLO Model for Pedestrian Detectionization within a scene. Recently, convolutional neural networks (CNNs) have been demonstrated to achieve superior detection results compared to traditional approaches. Although YOLOv3 (an improved You Only Look Once model) is proposed as one of state-of-the-art methods in CNN-based object detection,