Results 251 to 260 of about 27,881 (274)
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Bug localization via searching crowd-contributed code
Proceedings of the 6th Asia-Pacific Symposium on Internetware on Internetware, 2014Bug localization, i.e., locating bugs in code snippets, is a frequent task in software development. Although static bug-finding tools are available to reduce manual effort in bug localization, these tools typically detect bugs with known project-independent bug patterns. However, many bugs in real-world code snippets are project-specific.
Qianxiang Wang, Xuan Li
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Local ensemble surrogate assisted crowding differential evolution
2015 IEEE Congress on Evolutionary Computation (CEC), 2015Differential evolution (DE) is a powerful population-based stochastic optimization algorithm. Although its efficacy has been witnessed in various applications, the performance of DE is usually challenged when the computational budget is decreased and/or the search landscape's complexity is increased.
Chen Jin, A. K. Qin, Ke Tang
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Clustering of local behaviour in crowd videos
2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014Surveillance cameras are playing more important role in our daily life with the increasing number of human population and surveillance cameras. While there are a myriad of methods for video analysis, they are generally designed for low-density areas. Running of these algorithms in crowded areas would not give expected results and results in high number
Cihan Ongun +2 more
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An approach to localization in crowded area
2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom), 2016Every year millions of people gather at Makkah, Saudi Arabia during the Hajj, an annual Islamic pilgrimage. The area at Makkah is small, and the number of attendees increases each year, which has created an ongoing and ever increasing problem of crowd management.
Md Osman Gani +7 more
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Spatiotemporally localized new event detection in crowds
2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011The behavior of crowds is of interest in many applications, but difficult to analyze due to the complexity of the activities taking place, the number of people moving in the scene and occlusions occurring between them. This work focuses on the problem of detecting new events in crowds using an original approach that is based on properties of the data ...
Alexia Briassouli, Ioannis Kompatsiaris
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When local crowding reinforces an anomeric effect
Tetrahedron Letters, 1989Abstract In furanose-pyranose structures, a bulky substituent at the anomeric center of the furanose ring induces an axial conformation of the pyranosic part. The relative positions of the two rings are also modified: syn instead of anti with regard to the C-3/O-4/C-5 plane.
J.E Dubois, A Cossé-Barbi, D.G Watson
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Consistency-Aware Anchor Pyramid Network for Crowd Localization
IEEE Transactions on Pattern Analysis and Machine IntelligenceCrowd localization aims to predict the positions of humans in images of crowded scenes. While existing methods have made significant progress, two primary challenges remain: (i) a fixed number of evenly distributed anchors can cause excessive or insufficient predictions across regions in an image with varying crowd densities, and (ii) ranking ...
Xinyan Liu +7 more
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Mobile Image Search via Local Crowd: A User Study
2011 IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications, 2011In this paper we present a on-field study for evaluating a crowd sourcing mobile social search application. With the help of the local crowd via social medias, this application assists foreign visitors in Japan by answering their image-based questions at hand in a timely fashion. We ran a controlled field experiment for 6 weeks with 55 participants. We
Liu, Yefeng +4 more
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CrossNet: Boosting Crowd Counting with Localization
Proceedings of the 30th ACM International Conference on Multimedia, 2022Ji Zhang +4 more
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Scale-Context Perceptive Network for Crowd Counting and Localization in Smart City System
IEEE Internet of Things Journal, 2023Wenzhe Zhai, Mingliang Gao, Xiangyu Guo
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