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- W3207662977 endingPage "139507" @default.
- W3207662977 startingPage "139489" @default.
- W3207662977 abstract "Studies show lots of advanced research on various data types such as image, speech, and text using deep learning techniques, but nowadays, research on video processing is also an emerging field of computer vision. Several surveys are present on video processing using computer vision deep learning techniques, targeting specific functionality such as anomaly detection, crowd analysis, activity monitoring, etc. However, a combined study is still unexplored. This paper aims to present a Systematic Literature Review (SLR) on video processing using deep learning to investigate the applications, functionalities, techniques, datasets, issues, and challenges by formulating the relevant research questions (RQs). This systematic mapping includes 93 research articles from reputed databases published between 2011 and 2020. We categorize the deep learning technique for video processing as CNN, DNN, and RNN based. We observe the significant advancements in video processing between 2017 and 2020, primarily due to the advent of AlexNet, ResNet, and LSTM based deep learning techniques. The prominent fields of video processing research are observed as human action recognition, crowd anomaly detection, and behavior analysis. This SLR is a helpful guide for the researchers to explore the recent literature, available datasets, and existing deep learning techniques for video processing." @default.
- W3207662977 created "2021-10-25" @default.
- W3207662977 creator A5013584581 @default.
- W3207662977 creator A5026212514 @default.
- W3207662977 creator A5036770900 @default.
- W3207662977 creator A5057911761 @default.
- W3207662977 date "2021-01-01" @default.
- W3207662977 modified "2023-10-03" @default.
- W3207662977 title "Video Processing Using Deep Learning Techniques: A Systematic Literature Review" @default.
- W3207662977 cites W1413844602 @default.
- W3207662977 cites W147001025 @default.
- W3207662977 cites W1539987097 @default.
- W3207662977 cites W1558293780 @default.
- W3207662977 cites W1582396315 @default.
- W3207662977 cites W1832003755 @default.
- W3207662977 cites W1857884451 @default.
- W3207662977 cites W1923404803 @default.
- W3207662977 cites W1927052826 @default.
- W3207662977 cites W1950136256 @default.
- W3207662977 cites W1967456674 @default.
- W3207662977 cites W1983364832 @default.
- W3207662977 cites W2016053056 @default.
- W3207662977 cites W2019464758 @default.
- W3207662977 cites W2053608739 @default.
- W3207662977 cites W2071266191 @default.
- W3207662977 cites W2113221323 @default.
- W3207662977 cites W2123920041 @default.
- W3207662977 cites W2124386111 @default.
- W3207662977 cites W2126579184 @default.
- W3207662977 cites W2141355815 @default.
- W3207662977 cites W2150066425 @default.
- W3207662977 cites W2151586732 @default.
- W3207662977 cites W2156094107 @default.
- W3207662977 cites W2157363658 @default.
- W3207662977 cites W2163612318 @default.
- W3207662977 cites W2164489414 @default.
- W3207662977 cites W2210900744 @default.
- W3207662977 cites W2259801182 @default.
- W3207662977 cites W2296311849 @default.
- W3207662977 cites W2342662179 @default.
- W3207662977 cites W2440509458 @default.
- W3207662977 cites W2470139095 @default.
- W3207662977 cites W2508429489 @default.
- W3207662977 cites W2510190030 @default.
- W3207662977 cites W2515890997 @default.
- W3207662977 cites W2550462002 @default.
- W3207662977 cites W2566769621 @default.
- W3207662977 cites W2572061318 @default.
- W3207662977 cites W2592115426 @default.
- W3207662977 cites W2600200270 @default.
- W3207662977 cites W2603203130 @default.
- W3207662977 cites W2605288195 @default.
- W3207662977 cites W2734408173 @default.
- W3207662977 cites W2735824323 @default.
- W3207662977 cites W2759692151 @default.
- W3207662977 cites W2769923865 @default.
- W3207662977 cites W2782332354 @default.
- W3207662977 cites W2784066145 @default.
- W3207662977 cites W2791697444 @default.
- W3207662977 cites W2793015883 @default.
- W3207662977 cites W2810572479 @default.
- W3207662977 cites W2884367402 @default.
- W3207662977 cites W2893069018 @default.
- W3207662977 cites W2893511508 @default.
- W3207662977 cites W2896348597 @default.
- W3207662977 cites W2896487087 @default.
- W3207662977 cites W2908327111 @default.
- W3207662977 cites W2912386632 @default.
- W3207662977 cites W2912735527 @default.
- W3207662977 cites W2915935370 @default.
- W3207662977 cites W2917435394 @default.
- W3207662977 cites W2940033050 @default.
- W3207662977 cites W2941609709 @default.
- W3207662977 cites W2944912183 @default.
- W3207662977 cites W2944940038 @default.
- W3207662977 cites W2947209933 @default.
- W3207662977 cites W2949856406 @default.
- W3207662977 cites W2960646647 @default.
- W3207662977 cites W2962775523 @default.
- W3207662977 cites W2962889061 @default.
- W3207662977 cites W2963188159 @default.
- W3207662977 cites W2963251476 @default.
- W3207662977 cites W2963315828 @default.
- W3207662977 cites W2963351113 @default.
- W3207662977 cites W2963524571 @default.
- W3207662977 cites W2963541464 @default.
- W3207662977 cites W2963563276 @default.
- W3207662977 cites W2963741310 @default.
- W3207662977 cites W2964014730 @default.
- W3207662977 cites W2964298670 @default.
- W3207662977 cites W2966313861 @default.
- W3207662977 cites W2966535964 @default.
- W3207662977 cites W2967918518 @default.
- W3207662977 cites W2968597306 @default.
- W3207662977 cites W2969753617 @default.
- W3207662977 cites W2970645682 @default.
- W3207662977 cites W2973617321 @default.
- W3207662977 cites W2976482555 @default.