Results 51 to 60 of about 57,569 (167)

Conventional video shot segmentation to semantic shot segmentation

, 2015
Video shot segmentation is a preliminary process used in video content analysis which requires for content description. Conventional shot segmentation techniques nourished with statistical approaches depend on chromatic distributions of video frames.
Abdullah, NA, Zainuddin, R, Ranathunga, L   +2 more
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3D medical volume segmentation using hybrid multiresolution statistical approaches

, 2010
This article is available through the Brunel Open Access Publishing Fund. Copyright © 2010 S AlZu’bi and A Amira.3D volume segmentation is the process of partitioning voxels into 3D regions (subvolumes) that represent meaningful physical entities which ...
Alzubi, S, Amira, A, Shadi AlZu'bi, Abbes Amira   +3 more
core   +1 more source

Stopping region-based image segmentation at meaningful partitions [PDF]

, 2007
This paper proposes a new stopping criterion for automatic image segmentation based on region merging. The criterion is dependent on image content itself and when combined with the recently proposed approaches to syntactic segmentation can produce ...
O'Connor, Noel E., Adamek, Tomasz, O\u27Connor, Noel E.   +2 more
core   +1 more source

Automatic and controlled semantic retrieval: TMS reveals distinct contributions of posterior middle temporal gyrus and angular gyrus [PDF]

, 2015
Semantic retrieval involves both (1) automatic spreading activation between highly related concepts and (2) executive control processes that tailor this activation to suit the current context or goals.
Cornelissen, Piers, Sonkusare, Saurabh, Cornelissen, Piers L, Thompson, Hannah, Sonkusare, S., Jefferies, E., Davey, J, Smallwood, J, Thompson, Hannah E, Thompson, H.E., Hallam, G, Jefferies, Elizabeth, Thompson, Hannah E., Jefferies, E, Davey, James, Cornelissen, PL, Smallwood, Jonathan, Davey, J., Thompson, H, Smallwood, J., Cornelissen, P.L., Cornelissen, Piers L., Sonkusare, S, Hallam, Glyn   +23 more
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Gradient-Semantic Compensation for Incremental Semantic Segmentation

IEEE Transactions on Multimedia
Incremental semantic segmentation aims to continually learn the segmentation of new coming classes without accessing the training data of previously learned classes. However, most current methods fail to address catastrophic forgetting and background shift since they 1) treat all previous classes equally without considering different forgetting paces ...
Wei Cong, Yang Cong, Jiahua Dong 0001, Gan Sun, Henghui Ding   +4 more
openaire   +2 more sources

Semantic Segmentation Using Regions in Natural Scenes

, 2011
By introducing an over-segmentation algorithm into the conditional model (CM), we propose a new region-based CM model (R-CM), and investigate its performance on semantic segmentation of images. In order to incorporate structure information of objects, we
Hao YM(郝颖明), Wu SL(吴士林), Zhu F(朱枫)   +2 more
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Associating low-level features with semantic concepts using video objects and relevance feedback [PDF]

, 2005
The holy grail of multimedia indexing and retrieval is developing algorithms capable of imitating human abilities in distinguishing and recognising semantic concepts within the content, so that retrieval can be based on ”real world” concepts that come ...
Murphy, Noel, O'Connor, Noel E., Sav, Sorin Vasile, Smeaton, Alan F., O\u27Connor, Noel E.   +4 more
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Hierarchical Context Learning of object components for unsupervised semantic segmentation

Unsupervised Semantic Segmentation (USS) aims to learn semantically rich and dense representations without relying on labels. Recent advances in self-supervised learning have demonstrated the potential of pretrained vision transformers to capture patch ...
Tuxworth, Gervase, Zhou, Jun, Zhang, Jue, Bao, Dong, Gao, Yongsheng   +4 more
core   +1 more source

Semantic Segmentation with Spreading Scribbles

Hand-annotating medical images with segmentation masks requires an immense amount of time and effort from clinical experts. Replacing full masks with a simpler annotating gesture can mitigate annotation costs. This can come in the form of a scribble, and leads to weakly supervised training scenarios.
Yeva Gabrielyan, Varduhi Yeghiazaryan, Irina Voiculescu   +2 more
openaire   +1 more source

SEMANTIC SEGMENTATION OF MICROSCOPIC BLOOD IMAGE DATA USING SELF-TRAINING TO AUGMENT SMALL TRAINING SETS AND ITS APPLICATION FOR COUNTING CELLS

, 2019
Semantic segmentation is a computer vision task of assigning a label describing the content to each pixel in an image. There has been a lot of progress in this area using deep neural networks with an encoder-decoder structure.
Luo, Junliang
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