{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:24:10Z","timestamp":1750220650433,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,11,23]],"date-time":"2019-11-23T00:00:00Z","timestamp":1574467200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,11,23]]},"DOI":"10.1145\/3372422.3372434","type":"proceedings-article","created":{"date-parts":[[2020,2,7]],"date-time":"2020-02-07T23:20:13Z","timestamp":1581117613000},"page":"85-89","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Convolutional Neural Network using Stacked Frames for Video Classification"],"prefix":"10.1145","author":[{"given":"Itthisak","family":"Phueaksri","sequence":"first","affiliation":[{"name":"Computer Engineering, Chulalongkorn University, Bangkok, Thailand"}]},{"given":"Sukree","family":"Sinthupinyp","sequence":"additional","affiliation":[{"name":"Computer Engineering, Chulalongkorn University, Bangkok, Thailand"}]}],"member":"320","published-online":{"date-parts":[[2020,2,7]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"A large-scale hierarchical image database. 2009 ieee conf comput vis pattern recognit","author":"Deng J","year":"2009","unstructured":"J Deng , W Dong , R Socher , LJ Li , K Li , and L ImageNet Fei-Fei . A large-scale hierarchical image database. 2009 ieee conf comput vis pattern recognit , 2009 . J Deng, W Dong, R Socher, LJ Li, K Li, and L ImageNet Fei-Fei. A large-scale hierarchical image database. 2009 ieee conf comput vis pattern recognit, 2009."},{"key":"e_1_3_2_1_2_1","volume-title":"Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman . Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 , 2014 b. Karen Simonyan and Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556, 2014b."},{"key":"e_1_3_2_1_3_1","volume-title":"An analysis of deep neural network models for practical applications. arXiv preprint arXiv:1605.07678","author":"Canziani Alfredo","year":"2016","unstructured":"Alfredo Canziani , Adam Paszke , and Eugenio Culurciello . An analysis of deep neural network models for practical applications. arXiv preprint arXiv:1605.07678 , 2016 . Alfredo Canziani, Adam Paszke, and Eugenio Culurciello. An analysis of deep neural network models for practical applications. arXiv preprint arXiv:1605.07678, 2016."},{"key":"e_1_3_2_1_4_1","first-page":"568","volume-title":"Advances in neural information processing systems","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman . Two-stream convolutional networks for action recognition in videos . In Advances in neural information processing systems , pages 568 -- 576 , 2014 a. Karen Simonyan and Andrew Zisserman. Two-stream convolutional networks for action recognition in videos. In Advances in neural information processing systems, pages 568--576, 2014a."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806222"},{"key":"e_1_3_2_1_6_1","volume-title":"Multiscale deep alternative neural network for large-scale video classification.zIEEE Transactions on Multimedia, 20(10):2578--2592","author":"Wang Jinzhuo","year":"2018","unstructured":"Jinzhuo Wang , Wenmin Wang , and Wen Gao . Multiscale deep alternative neural network for large-scale video classification.zIEEE Transactions on Multimedia, 20(10):2578--2592 , 2018 . Jinzhuo Wang, Wenmin Wang, and Wen Gao. Multiscale deep alternative neural network for large-scale video classification.zIEEE Transactions on Multimedia, 20(10):2578--2592, 2018."},{"key":"e_1_3_2_1_7_1","volume-title":"Exploiting image-trained cnn architectures for unconstrained video classification. arXiv preprint arXiv:1503.04144","author":"Zha Shengxin","year":"2015","unstructured":"Shengxin Zha , Florian Luisier , Walter Andrews , Nitish Srivastava , and Ruslan Salakhut- dinov. Exploiting image-trained cnn architectures for unconstrained video classification. arXiv preprint arXiv:1503.04144 , 2015 . Shengxin Zha, Florian Luisier, Walter Andrews, Nitish Srivastava, and Ruslan Salakhut- dinov. Exploiting image-trained cnn architectures for unconstrained video classification. arXiv preprint arXiv:1503.04144, 2015."},{"key":"e_1_3_2_1_8_1","first-page":"1725","volume-title":"Pro- ceedings of the IEEE conference on Computer Vision and Pattern Recognition","author":"Karpathy Andrej","year":"2014","unstructured":"Andrej Karpathy , George Toderici , Sanketh Shetty , Thomas Leung , Rahul Sukthankar , and Li Fei-Fei . Large-scale video classification with convolutional neural networks . In Pro- ceedings of the IEEE conference on Computer Vision and Pattern Recognition , pages 1725 -- 1732 , 2014 . Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, and Li Fei-Fei. Large-scale video classification with convolutional neural networks. In Pro- ceedings of the IEEE conference on Computer Vision and Pattern Recognition, pages 1725--1732, 2014."},{"key":"e_1_3_2_1_9_1","volume-title":"Scanner: Efficient video analysis at scale. ACM Transactions on Graphics (TOG), 37(4):138","author":"Poms Alex","year":"2018","unstructured":"Alex Poms , Will Crichton , Pat Hanrahan , and Kayvon Fatahalian . Scanner: Efficient video analysis at scale. ACM Transactions on Graphics (TOG), 37(4):138 , 2018 . Alex Poms, Will Crichton, Pat Hanrahan, and Kayvon Fatahalian. Scanner: Efficient video analysis at scale. ACM Transactions on Graphics (TOG), 37(4):138, 2018."},{"key":"e_1_3_2_1_10_1","volume-title":"Video understanding: from video classification to captioning","author":"Sun Jiajun","year":"2019","unstructured":"Jiajun Sun , Jing Wang , and TC Yeh . Video understanding: from video classification to captioning , 2019 . Jiajun Sun, Jing Wang, and TC Yeh. Video understanding: from video classification to captioning, 2019."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299101"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2018.2823900"},{"key":"e_1_3_2_1_13_1","volume-title":"Balakrish- nan Varadarajan, and Sudheendra Vijayanarasimhan. Youtube-8m: A large-scale video classification benchmark. arXiv preprint arXiv:1609.08675","author":"Abu-El-Haija Sami","year":"2016","unstructured":"Sami Abu-El-Haija , Nisarg Kothari , Joonseok Lee , Paul Natsev , George Toderici , Balakrish- nan Varadarajan, and Sudheendra Vijayanarasimhan. Youtube-8m: A large-scale video classification benchmark. arXiv preprint arXiv:1609.08675 , 2016 . Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrish- nan Varadarajan, and Sudheendra Vijayanarasimhan. Youtube-8m: A large-scale video classification benchmark. arXiv preprint arXiv:1609.08675, 2016."},{"key":"e_1_3_2_1_14_1","volume-title":"Amir Roshan Zamir, and M Shah. A dataset of 101 human action classes from videos in the wild","author":"Soomro Khurram","year":"2012","unstructured":"Khurram Soomro , Amir Roshan Zamir, and M Shah. A dataset of 101 human action classes from videos in the wild . Center for Research in Computer Vision, 2012 . Khurram Soomro, Amir Roshan Zamir, and M Shah. A dataset of 101 human action classes from videos in the wild. Center for Research in Computer Vision, 2012."},{"key":"e_1_3_2_1_15_1","first-page":"4489","volume-title":"Proceedings of the IEEE international conference on computer vision","author":"Tran Du","unstructured":"Du Tran , Lubomir Bourdev , Rob Fergus , Lorenzo Torresani , and Manohar Paluri . Learn- ing spatiotemporal features with 3d convolutional networks . In Proceedings of the IEEE international conference on computer vision , pages 4489 -- 4497 , 201 Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri. Learn- ing spatiotemporal features with 3d convolutional networks. In Proceedings of the IEEE international conference on computer vision, pages 4489--4497, 201"}],"event":{"name":"CIIS 2019: 2019 The 2nd International Conference on Computational Intelligence and Intelligent Systems","sponsor":["Queensland University of Technology","City University of Hong Kong City University of Hong Kong"],"location":"Bangkok Thailand","acronym":"CIIS 2019"},"container-title":["Proceedings of the 2019 2nd International Conference on Computational Intelligence and Intelligent Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3372422.3372434","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3372422.3372434","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:02:21Z","timestamp":1750197741000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3372422.3372434"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,23]]},"references-count":15,"alternative-id":["10.1145\/3372422.3372434","10.1145\/3372422"],"URL":"https:\/\/doi.org\/10.1145\/3372422.3372434","relation":{},"subject":[],"published":{"date-parts":[[2019,11,23]]},"assertion":[{"value":"2020-02-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}