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14 August 2019 Deep learning concepts and datasets for image recognition: overview 2019
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Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111791S (2019) https://doi.org/10.1117/12.2539806
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China
Abstract
We present basics of a deep learning concept and an overview of well-known deep learning concepts as general Convolutional Neural Networks, R-CNN family, Single Shot Multibox Detector, You Only Look Once architecture and the RetinaNet in the first part of this paper. The all mentioned architectures are described to quickly compare to each other regarding their suitability for given general task. Several selected datasets often used in deep learning competitions are listed in the subsequent chapters in more details. The most known of practically used and listed datasets are COCO, KITTI, PascalVOC and CityShapes. The overview serves as a comparison of the state-of-the-art deep learning methods.
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Karel Horak and Robert Sablatnig "Deep learning concepts and datasets for image recognition: overview 2019", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791S (14 August 2019); https://doi.org/10.1117/12.2539806
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