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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title: A Result Paper on Salient Object Detection using Edge Preservation and Multi-Scale Contextual Neural Network for identification
Authors Name: POOJA INGOLE , S C NANDEDKAR
Unique Id: IJSDR1902059
Published In: Volume 4 Issue 2, March-2019
Abstract: Abstract: Everywhere we go we take photographs, images, selfies etc for any social or private lifestyle of human being. That photos must be cleared, sharpened, filtered for this we have different techniques, application etc the one method is Salient Object Detection using Edge Preservation and Multi-Scale Contextual Neural Network. In this paper, we propose a novelty on edge preserving and multi-scale contextual neural networking for saliency. The full proposed framework architecture is mainly aims towards different address two ceiling of the existing CNN based methods. In recent years, salient object detection, which aims to detect object that most attracts people’s attention throughout an image scenes along with whole foreground and background, has been widely exploited. The center of attraction and focus is to get maximum optimized result using the techniques like edge preserving, contextual networking, multi-scaling, detecting the most particular important object with feature extraction using SIFT algorithm. It has also been widely utilized for many computer vision tasks and digital image processing digital marketing, such as semantic segmentation, object tracking and image classification. These proposed framework achieves and optimizes the goals, targets both clear detection boundary of an input image and multi-scale contextual neural networks robustness simultaneously time being, and thus achieves an optimized performance results. Therefore, we get different and many more experimental results that’s sets higher benchmarks, result and applications using various datasets express that this designed proposed methods are to achieves through best and high leveled state-of-the-art performance optimally therefore our proposed system produce the best experimental result that demonstrates recognition, identification of rated object is higher than other method and also reach to high performance with optimal solution in an image .
Keywords: Keywords: Salient object detection, edge preservation, multi-scale context neural networks, RGB-D saliency detection, object mask pooling, SVM, SIFT.
Cite Article: "A Result Paper on Salient Object Detection using Edge Preservation and Multi-Scale Contextual Neural Network for identification", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 2, page no.357 - 362, March-2019, Available :http://www.ijsdr.org/papers/IJSDR1902059.pdf
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Publication Details: Published Paper ID: IJSDR1902059
Registration ID:190121
Published In: Volume 4 Issue 2, March-2019
DOI (Digital Object Identifier):
Page No: 357 - 362
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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