{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T09:48:26Z","timestamp":1774518506194,"version":"3.50.1"},"reference-count":7,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2018,8]]},"abstract":"<jats:p>\n            The efficient processing of video streams is a key component in many emerging Internet of Things (IoT) and edge applications, such as Virtual and Augmented Reality (V\/AR) and self-driving cars. These applications require real-time high-throughput video processing. This can be attained via a collaborative processing model between the edge and the cloud---called an\n            <jats:italic>Edge-Cloud model<\/jats:italic>\n            . To this end, many approaches were proposed to optimize the latency and bandwidth consumption of Edge-Cloud video processing, especially for Neural Networks (NN)-based methods. In this demonstration. We investigate the efficiency of these NN techniques, how they can be combined, and whether combining them leads to better performance. Our demonstration invites participants to experiment with the various NN techniques, combine them, and observe how the underlying NN changes with different techniques and how these changes affect accuracy, latency and bandwidth consumption.\n          <\/jats:p>","DOI":"10.14778\/3229863.3236256","type":"journal-article","created":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T12:12:28Z","timestamp":1536581548000},"page":"2046-2049","source":"Crossref","is-referenced-by-count":49,"title":["Collaborative edge and cloud neural networks for real-time video processing"],"prefix":"10.14778","volume":"11","author":[{"given":"Philipp M.","family":"Grulich","sequence":"first","affiliation":[{"name":"University of California and Technische Universit\u00e4t Berlin"}]},{"given":"Faisal","family":"Nawab","sequence":"additional","affiliation":[{"name":"University of California"}]}],"member":"320","published-online":{"date-parts":[[2018,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1600193.1600198"},{"key":"e_1_2_1_2_1","volume-title":"An improved adaptive background mixture model for realtime tracking with shadow detection","author":"Kaewtrakulpong P.","year":"2001","unstructured":"P. Kaewtrakulpong and R. Bowden . An improved adaptive background mixture model for realtime tracking with shadow detection . 2001 . P. Kaewtrakulpong and R. Bowden. An improved adaptive background mixture model for realtime tracking with shadow detection. 2001."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.14778\/3137628.3137664"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3037697.3037698"},{"key":"e_1_2_1_5_1","volume-title":"Fixed-rate compressed floating-point arrays","author":"Lindstrom P.","year":"2014","unstructured":"P. Lindstrom . Fixed-rate compressed floating-point arrays . IEEE transactions on visualization and computer graphics, 20(12):2674--2683, 2014 . P. Lindstrom. Fixed-rate compressed floating-point arrays. IEEE transactions on visualization and computer graphics, 20(12):2674--2683, 2014."},{"key":"e_1_2_1_6_1","volume-title":"YOLO9000: better, faster, stronger. CoRR, abs\/1612.08242","author":"Redmon J.","year":"2016","unstructured":"J. Redmon and A. Farhadi . YOLO9000: better, faster, stronger. CoRR, abs\/1612.08242 , 2016 . J. Redmon and A. Farhadi. YOLO9000: better, faster, stronger. CoRR, abs\/1612.08242, 2016."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2735365"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3229863.3236256","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:12:39Z","timestamp":1672222359000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3229863.3236256"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8]]},"references-count":7,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2018,8]]}},"alternative-id":["10.14778\/3229863.3236256"],"URL":"https:\/\/doi.org\/10.14778\/3229863.3236256","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2018,8]]}}}