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Fusing generic objectness and deformable part-based models for weakly supervised object detection

contributor authorTang, Yuxing
contributor authorWang, Xiaofang
contributor authorDellandrea, Emmanuel
contributor authorMasnou, Simon
contributor authorChen, Liming
date accessioned2020-03-12T22:50:29Z
date available2020-03-12T22:50:29Z
date issued2014
identifier other7025827.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1096406?locale-attribute=fa&show=full
formatgeneral
languageEnglish
publisherIEEE
titleFusing generic objectness and deformable part-based models for weakly supervised object detection
typeConference Paper
contenttypeMetadata Only
identifier padid8236920
subject keywordsdata visualisation
subject keywordsn gradient methods
subject keywordsn learning (artificial intelligence)
subject keywordsn rendering (computer graphics)
subject keywordsn stochastic processes
subject keywordsn transfer functions
subject keywordsn DR methods
subject keywordsn DVR
subject keywordsn GCSE
subject keywordsn dictionary learning
subject keywordsn dimension reduction
subject keywordsn dimensionality reduction
subject keywordsn direct volume rendering
subject keywordsn geometry constrained sparse embedding
subject keywordsn geometry distance
subject keywordsn medical visualization
subject keywordsn multidimensional transfer function design
subject keywordsn real CT data sets
subject keywordsn stochastic gradient de
identifier doi10.1109/ICRA.2014.6907019
journal titlemage Processing (ICIP), 2014 IEEE International Conference on
filesize690234
citations0


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