Titlebook: Computer Vision, Imaging and Computer Graphics Theory and Applications; 15th International J Kadi Bouatouch,A. Augusto de Sousa,Jose Braz C

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https://doi.org/10.1057/9780230599116tion performance only drops from . to . while . of the label information is removed. The flexibility of the detector with respect to the different levels of details in label definitions is investigated for a traffic surveillance application, involving public and proprietary datasets with non-overlap

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https://doi.org/10.1057/9780230599116ing the fusion of two lightweight neural network architectures, MobileNetV2 and Single Shot Detector (SSD), into our approach named MobText. As experimental results in the ICDAR’11 and ICDAR’13 datasets demonstrates that our solution yields the best trade-off between effectiveness and efficiency in

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A Changing Focus: The Invalided Men,ual networks. In addition to reducing overfitting, this method also reduces the training cost, since it usually requires fewer epochs to complete the classification process. Experiments are conducted on UCF101 and HMDB51 datasets, which are two challenging benchmarks in the context of action recogni

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Computer Vision, Imaging and Computer Graphics Theory and Applications15th International J

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Conference proceedings 2022phics Theory and Applications, VISIGRAPP 2020, held in Valletta, Malta, in February 2020..The 25 thoroughly revised and extended papers presented in this volume were carefully reviewed and selected from 455 submissions. The papers contribute to the understanding of relevant trends of current researc