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Semi-Automatic Retrieval of Relevant Segments from Laparoscopic Surgery Videos.

. ICMR, page 484-488. ACM, (2017)

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Deep Learning for Shot Classification in Gynecologic Surgery Videos., and . MMM (1), volume 10132 of Lecture Notes in Computer Science, page 702-713. Springer, (2017)An Inception-like CNN Architecture for GI Disease and Anatomical Landmark Classification., , and . MediaEval, volume 1984 of CEUR Workshop Proceedings, CEUR-WS.org, (2017)Early and Late Fusion of Temporal Information for Classification of Surgical Actions in Laparoscopic Gynecology., , , , and . CBMS, page 369-374. IEEE Computer Society, (2018)Binary convolutional neural network features off-the-shelf for image to video linking in endoscopic multimedia databases, and . Multimedia Tools Appl., (2018)Real-Time Image-based Smoke Detection in Endoscopic Videos., , , and . ACM Multimedia (Thematic Workshops), page 296-304. ACM, (2017)Image-Based Smoke Detection in Laparoscopic Videos., , , and . CARE/CLIP@MICCAI, volume 10550 of Lecture Notes in Computer Science, page 70-87. Springer, (2017)Static vs. Dynamic Content Descriptors for Video Retrieval in Laparoscopy., , , , and . ISM, page 216-223. IEEE Computer Society, (2017)Merge and forward: self-organized inter-destination multimedia synchronization., , and . MMSys, page 77-80. ACM, (2015)Semi-Automatic Retrieval of Relevant Segments from Laparoscopic Surgery Videos.. ICMR, page 484-488. ACM, (2017)ITEC-UNIKLU Ad-hoc Video Search Submission 2016., , , and . TRECVID, National Institute of Standards and Technology (NIST), (2016)