@inproceedings{Horak_2019_DL_Overview,
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.},
author = {Horak, Karel and Sablatnig, Robert},
doi = {10.1117/12.2539806},
file = {:D$\backslash$:/PUBLIKACE/2019-03 - ICDIP 2019 Guangzhou China (Deep Learning Concepts and Datasets for Image Recognition - Overview 2019)/1. Paper/ICDIP{\_}2019{\_}Horak{\_}116{\_}ver04 - revised by ICDIP.pdf:pdf},
isbn = {9781510630758},
issn = {1996756X},
keywords = {convolutional neural network,dataset,deep learning,image recognition,r-cnn,retinanet},
number = {March 2016},
pages = {100},
title = {{Deep learning concepts and datasets for image recognition: overview 2019}},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11179/111791S/Deep-learning-concepts-and-datasets-for-image-recognition--overview/10.1117/12.2539806.short?SSO=1},
year = {2019}
}