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pro vyhledávání: '"Ghauri, Junaid Ahmed"'
Due to the swift growth of patent applications each year, information and multimedia retrieval approaches that facilitate patent exploration and retrieval are of utmost importance. Different types of visualizations (e.g., graphs, technical drawings)
Externí odkaz:
http://arxiv.org/abs/2307.10471
Video summarization aims at generating a compact yet representative visual summary that conveys the essence of the original video. The advantage of unsupervised approaches is that they do not require human annotations to learn the summarization capab
Externí odkaz:
http://arxiv.org/abs/2105.12532
The assignment of importance scores to particular frames or (short) segments in a video is crucial for summarization, but also a difficult task. Previous work utilizes only one source of visual features. In this paper, we suggest a novel model archit
Externí odkaz:
http://arxiv.org/abs/2104.11530
Videos are a commonly-used type of content in learning during Web search. Many e-learning platforms provide quality content, but sometimes educational videos are long and cover many topics. Humans are good in extracting important sections from videos
Externí odkaz:
http://arxiv.org/abs/2010.13626
Autor:
Windler, Torben, Ghauri, Junaid Ahmed, Syed, Muhammad Usman, Belostotskaya, Tamara, Chikukwa, Valerie, Drumond, Rafael Rêgo
Publikováno v:
Archives of Data Science, Series A, 6 (1), P12, 19 S.
Analysis of smart devices’ sensor data for the classification of human activities has become increasingly targeted by industry and motion research. With the popularization of smartwatches, this data becomes available to everyone. The user’s data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77f7a17b83c84b73dd0ec7abd2c06639