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International Journal of Multimedia Information Retrieval (2020) 9:61–62 https://doi.org/10.1007/s13735-020-00194-y EDITORIAL 1 2 3 4 Ard Oerlemans · Yanming Guo · Michael S. Lew · Tat‑Seng Chua Published online: 16 May 2020 © Springer-Verlag London Ltd., part of Springer Nature 2020 In recent years, deep learning techniques have been rap- Study on Deep Learning Spatiotemporal Models and Fea- idly evolving and advancing, which has resulted in such ture Extraction Techniques for Video Understanding” by M. approaches finding their way into almost all fields where Suresha, S. Kuppa and D.S. Raghukumar. With over 100 machine learning had already been used or where clas- references, the authors start with a discussion on the extrac- sic algorithms were still the chosen solution. From image tion of spatiotemporal features from video data and how classification and image segmentation to natural lan- deep learning models can be used for that. Thereafter, they guage translation and climate modeling, the deep learning explore real-world video understanding problems and inves- approaches have consistently outperformed the best previ- tigate the future perspective research avenues. This overview ous algorithms. provides a general understanding of diverse deep learning This special issue aims to capture the state of the art in strategies for video understanding problems. deep
International Journal of Multimedia Information Retrieval – Springer Journals
Published: Jun 16, 2020
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