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Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2021; 30th International C Igor Farkaš,Paolo Masulli,Stefan Wermter Conference proc

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First-Order and Second-Order Variants of the Gradient Descent in a Unified Frameworkradient descent, the classical and generalized Gauss-Newton methods, the natural gradient descent method, the gradient covariance matrix approach, and Newton’s method. Besides interpreting these methods within a single framework, we explain their specificities and show under which conditions some of them coincide.
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,Meßvorrichtungen und Meßautomaten,be integrated in both single-stage and two-stage detectors to boost detection performance, with nearly no extra inference cost. RetinaNet combined with SMSL obtains 1.8% improvement in AP (from 39.1% to 40.9%) on COCO dataset. When integrated with SMSL, two-stage detectors can get around 1.0% improvement in AP.
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https://doi.org/10.1007/978-3-322-96810-4of an unparalleled size in the literature, with the main diseases and damages of papaya fruit (.). The proposed data set in this work consists of 15,179 RGB images duly and manually annotated with the position of the fruit and the disease/damage found within it..In order to validate our dataset, we
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,Grundlagen der Fertigungsmeßtechnik, regressors in different levels. Then, the features derived from the density map were cascaded to assist generating a higher quality density map in next stage. Finally, the gated blocks were designed to achieve the controllable information interaction between cascade and backbone. Extensive experime
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