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Titlebook: Computer Vision, Graphics, and Image Processing; ICVGIP 2016 Satellit Snehasis Mukherjee,Suvadip Mukherjee,Santanu Chaud Conference proceed

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41#
發(fā)表于 2025-3-28 15:39:12 | 只看該作者
Brain Tumor Segmentation from Multimodal MR Images Using Rough Setst boundaries, which is one of the major challenges faced in tumor segmentation. Experiments are carried out on the BRATS 2013 and 2015 databases and results are comparable to those reported by recent works.
42#
發(fā)表于 2025-3-28 20:37:51 | 只看該作者
43#
發(fā)表于 2025-3-29 02:44:58 | 只看該作者
44#
發(fā)表于 2025-3-29 06:24:13 | 只看該作者
Photometric Normalization Techniques for Extended Multi-spectral Face Recognition: A Comparative Anavancement in sensor technology, face recognition based on Multi-spectral imaging has gained lot of popularity due to its potential of capturing discrete spatio-spectral images across the electromagnetic spectrum. Our contribution here is to study empirically, the extensive comparative performance an
45#
發(fā)表于 2025-3-29 10:20:17 | 只看該作者
Dictionary Based Approach for Facial Expression Recognition from Static Imagessual appearance based feature descriptors like histogram of oriented gradients (HOG), local binary patterns (LBP) and eigenfaces are used. We use Fisher discrimination dictionary which has discrimination capability in addition to being reconstructive. The classification is based on the fact that eac
46#
發(fā)表于 2025-3-29 13:17:59 | 只看該作者
47#
發(fā)表于 2025-3-29 18:33:53 | 只看該作者
48#
發(fā)表于 2025-3-29 20:58:49 | 只看該作者
Simultaneous Reconstruction of Multiple Hand Shredded Content-Less Pages Using Graph-Based Global Rewhen the number of pages from which the fragments are obtained is unknown. An iterative framework to solve the jigsaw puzzles of multiple hand shredded content-less pages has been proposed in this paper. This framework makes use of the shape-based information alone to solve the puzzle. All pairs of
49#
發(fā)表于 2025-3-30 03:31:29 | 只看該作者
Super Resolution Mapping of Trees for Urban Forest Monitoring in Madurai City Using Remote Sensinges is a significant issue in remote sensing applications where the lack of height information becomes a hard monocular recognition task. The density and shape of the trees gets affected by other man-made objects which gives rise to an erroneous recognition. The quality of recognition may be affected
50#
發(fā)表于 2025-3-30 05:26:19 | 只看該作者
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