Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Amirreza Shaban"'
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585853
ECCV (24)
ECCV (24)
Weakly Supervised Object Localization (WSOL) methods only require image level labels as opposed to expensive bounding box annotations required by fully supervised algorithms. We study the problem of learning localization model on target classes with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5be63ae71ba45a0b5a7b47e489ddc121
https://doi.org/10.1007/978-3-030-58586-0_24
https://doi.org/10.1007/978-3-030-58586-0_24
Publikováno v:
CVPR
In late fusion, each modality is processed in a separate unimodal Convolutional Neural Network (CNN) stream and the scores of each modality are fused at the end. Due to its simplicity, late fusion is still the predominant approach in many state-of-th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e4426e2f3a795f3efdc5c0674765006
http://arxiv.org/abs/1911.08670
http://arxiv.org/abs/1911.08670
Publikováno v:
Intelligent Data Analysis. 20:877-889
With the increasing volume of data in the world, the best approach for learning from this data is to exploit an online learning algorithm. Online ensemble methods are online algorithms which take advantage of an ensemble of classifiers to predict lab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c270bf96cccae8875c94be3456c40a9
https://doi.org/10.3233/ida-160836
https://doi.org/10.3233/ida-160836
Publikováno v:
ICRA
We consider the problems of learning forward models that map state to high-dimensional images and inverse models that map high-dimensional images to state in robotics. Specifically, we present a perceptual model for generating video frames from state
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::086cb1bc49fb33618cccc3e6d8f9bfe9
Publikováno v:
BMVC
Low-shot learning methods for image classification support learning from sparse data. We extend these techniques to support dense semantic image segmentation. Specifically, we train a network that, given a small set of annotated images, produces para
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea221abfb384a83ea3e1babdbb83bc46
https://doi.org/10.5244/c.31.167
https://doi.org/10.5244/c.31.167
Publikováno v:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 24(12)
Feature coding has received great attention in recent years as a building block of many image processing algorithms. In particular, the importance of the locality assumption in coding approaches has been studied in many previous works. We review this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd42048435a4dd28b33bd3f8858c1e3e
https://pubmed.ncbi.nlm.nih.gov/26259084
https://pubmed.ncbi.nlm.nih.gov/26259084
Publikováno v:
CVPR
Bag of words models for feature extraction have demonstrated top-notch performance in image classification. These representations are usually accompanied by a coding method. Recently, methods that code a descriptor giving regard to its nearby bases h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4896d248c8b29cf2731a3b82074911b8
https://doi.org/10.1109/cvpr.2013.360
https://doi.org/10.1109/cvpr.2013.360
Publikováno v:
ICDM Workshops
This paper introduces a novel coding scheme based on the diffusion map framework. The idea is to run a t-step random walk on the data graph to capture the similarity of a data point to the codebook atoms. By doing this we exploit local similarities e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad240a1c9636f1ba5e58f4804b618c1c
https://doi.org/10.1109/icdmw.2012.86
https://doi.org/10.1109/icdmw.2012.86
Publikováno v:
ICDM Workshops
Semi-Supervised Learning (SSL) has become a topic of recent research that effectively addresses the problem of limited labeled data. Many SSL methods have been developed based on the manifold assumption, among them, the Local and Global Consistency (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3211f30f2f8f060fd9f39fd1c8bb46d
https://doi.org/10.1109/icdmw.2011.181
https://doi.org/10.1109/icdmw.2011.181
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783642237799
ECML/PKDD (1)
ECML/PKDD (1)
When the number of labeled data is not sufficient, Semi-Supervised Learning (SSL) methods utilize unlabeled data to enhance classification. Recently, many SSL methods have been developed based on the manifold assumption in a batch mode. However, when
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d2e4b5e1015344146a11fd5a3b7d764
https://doi.org/10.1007/978-3-642-23780-5_35
https://doi.org/10.1007/978-3-642-23780-5_35