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Volume 7 | Issue 8

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Paper Title: Bacterial Foraging Optimization with Multilayer Neural Network using Shape Based Object Detections in Digital Images
Unique Id: IJSDR1907062
Published In: Volume 4 Issue 7, July-2019
Abstract: Over past few decades, object recognition and tracing is an essential area of research. Object detection and tracking become important because of adjustment in movement of object and change in size of scene image, change in look of object and illumination modifications. Generally the selecting of features plays an essential role in detection of object. Object detection and tracking are used in various real time applications areas like as vehicular object observation, video investigation and so forth. Hence, to overcome the problem of tracking and detection of object reliant on motion and look of object. Various algorithms concentrate on detection algorithms to clear the object image. Along with that, also other techniques related to data about figure, color, smoothness of object and so forth. In this research, technique using Scale Invariant Feature Transformation(SIFT) algorithm for extraction of features in three stages which are: - (i) Elimination (ii) Dispersal and (iii) Reproduction.Extraction of featur
Keywords: Object detection, Multi perceptron neural network, Scale Invariant feature transformation, Object observation
Cite Article: "Bacterial Foraging Optimization with Multilayer Neural Network using Shape Based Object Detections in Digital Images", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 7, page no.363 - 369, July-2019, Available :http://www.ijsdr.org/papers/IJSDR1907062.pdf
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Publication Details: Published Paper ID: IJSDR1907062
Registration ID:190824
Published In: Volume 4 Issue 7, July-2019
DOI (Digital Object Identifier):
Page No: 363 - 369
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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