Titlebook: Deep Learning Theory and Applications; 5th International Co Ana Fred,Allel Hadjali,Carlo Sansone Conference proceedings 2024 The Editor(s)

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書目名稱Deep Learning Theory and Applications影響因子(影響力)




書目名稱Deep Learning Theory and Applications影響因子(影響力)學(xué)科排名




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書目名稱Deep Learning Theory and Applications網(wǎng)絡(luò)公開度學(xué)科排名




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書目名稱Deep Learning Theory and Applications被引頻次學(xué)科排名




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書目名稱Deep Learning Theory and Applications年度引用學(xué)科排名




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978-3-031-66704-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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,Str?mungen mit mehreren Phasen,e from traditional statistical models to domain-specific algorithms, and more recently deep neural network models typically rely on raw time series observations, with alternative representations like higher-dimensional embedding used mainly for auxiliary analyses such as Topological Data Analysis (T

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nnovation and diversity in the field. This position paper advocates for a strategic pivot of small institutions to research directions that are computationally economical, specifically through a modular approach inspired by neurobiological mechanisms. We argue for a balanced approach that draws insp

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Zusammenfassung der Diskussionsformen,e heated HTF is then used in thermal power blocks to produce electricity in conventional steam generators. Unexpectedly high HTF temperatures may lead to degradation of the system components and reduced efficiency. Therefore, closely monitoring and maintaining the HTF’s operational temperatures is c

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Kompetenz: Den Alltag meistern,concentration of pollutant gas in the air, in order to estimate the position and intensity of a pollutant source. In a Hierarchical Agglomerative Clustering (HAC) framework we aim to regroup sensors of the same behavior, based on similarity measure, then, we keep only one sensor of each cluster. Unl

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Denktaktik: Verschenke überraschungen,rdisciplinary field, delves into environmental themes within cultural works, broadening the scope of humanities’ focus on representation issues. Our objective is to pioneer a method for automated, dependable analysis of audiovisual narratives within fictional feature films, exploring the interplay b

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,Führung in der Zweierbeziehung,n is most often encountered in agriculture for the classification of crop diseases. This can lead to challenges in training deep learning models, as they may become biased toward the majority class and perform poorly in predicting the minority class. One common approach to address class imbalance is