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Titlebook: Advances in Soft Computing; 18th Mexican Interna Lourdes Martínez-Villase?or,Ildar Batyrshin,Antoni Conference proceedings 2019 Springer Na

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發(fā)表于 2025-3-21 16:11:05 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Advances in Soft Computing
期刊簡(jiǎn)稱(chēng)18th Mexican Interna
影響因子2023Lourdes Martínez-Villase?or,Ildar Batyrshin,Antoni
視頻videohttp://file.papertrans.cn/150/149752/149752.mp4
學(xué)科分類(lèi)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Advances in Soft Computing; 18th Mexican Interna Lourdes Martínez-Villase?or,Ildar Batyrshin,Antoni Conference proceedings 2019 Springer Na
影響因子.This volume constitutes the proceedings of the 18th Mexican Conference on Artificial Intelligence, MICAI 2019, held in Xalapa, Mexico, in October/November 2019.. The 59 full papers presented in this volume were carefully reviewed and selected from 148 submissions. They cover topics such as: machine learning; optimization and planning; fuzzy systems, reasoning and intelligent applications; and vision and robotics.?.
Pindex Conference proceedings 2019
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書(shū)目名稱(chēng)Advances in Soft Computing影響因子(影響力)




書(shū)目名稱(chēng)Advances in Soft Computing影響因子(影響力)學(xué)科排名




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Statistical Approach in Data Filtering for Prediction Vessel Movements Through Time and Estimation R computational work when predictions or route estimations are in execution. The results obtained after testing the method are almost acceptable concerning route estimation with a precision of 74.98%, and with vessel positions predictions through time a 79% of accuracy.
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A Deep Learning Approach for Hybrid Hand Gesture Recognitionidentify both static and dynamic gestures. As far as our knowledge, there is no full dataset based on the LMC that includes both types of gestures. Therefore, we also introduce the Hybrid Hand Gesture Recognition database, which consists of a large set of gestures generated with the LMC, including b
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Early Anomalous Vehicular Traffic Detection Through Spectral Techniques and Unsupervised Learning Moatures and an unsupervised learning model to detect anomalous vehicular traffic. The methodology was evaluated in a real vehicular traffic database. Experimental results show that by using spectral attributes the detection of anomalous vehicular traffic, the Isolation Forest obtains the best results
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Anuj Dawar,Steven Lindell,Scott Weinsteincludes a more balanced and representative set of damages. This dataset is composed of 18,034 road damage images captured with a smartphone, with 45,435 instances road surface damages. Second, we trained different types of object detection methods, both traditional (an LBP-cascaded classifier) and de
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