Raman Spectroscopic Investigation Of The Effects Of Heat-treatment And Al, Ce Or Eu Doping Concentration On Tio2 Powder Crystallization

dc.contributor.authorBendaoud, Amira
dc.contributor.authorHachouf, Fella
dc.date.accessioned2023-09-07T05:04:58Z
dc.date.available2023-09-07T05:04:58Z
dc.date.issued2019
dc.description.abstractEdge-based active contour models have been one of the most prominent and influential approaches in image segmentation. It has been proven that they are very effective when they are applied on images with inhomogeneous intensity. Traditional edge-stop functions (ESFs) are usually used when edges are defined by the image gradient. They often produce weak edges because they fail to stop at the precise boundary. In this work, a new approach integrating machine learning algorithm with edge-based model using a level set method (LSM) is proposed. The ESF is constructed from a convolutional neural network. Then it is applied to an edge-based active contour model. The proposed method has been applied on medical images. Obtained results have been compared to those given by k-nearest neighbors and support vector machine to confirm the effectiveness of the proposed method.ar
dc.identifier.issn2170-16X
dc.identifier.issn2588-2082
dc.identifier.urihttp://hdl.handle.net/123456789/15154
dc.language.isoenar
dc.publisherOum-El-Bouaghi Universityar
dc.subjectEdge-based active contourar
dc.subjectImage segmentationar
dc.subjectMedical imagesar
dc.titleRaman Spectroscopic Investigation Of The Effects Of Heat-treatment And Al, Ce Or Eu Doping Concentration On Tio2 Powder Crystallizationar
dc.typeArticlear
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