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Skin Disease Detection by Image Processing Using CNN

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dc.contributor.author Akhter, Sraboni
dc.date.accessioned 2023-03-19T04:43:38Z
dc.date.available 2023-03-19T04:43:38Z
dc.date.issued 23-01-29
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/9985
dc.description.abstract Image processing is remarkable algorithm for detecting a anything from image data. There are some models in Image processing. Such as CNN, ResNet50, EfficientNetB3, VGG19 etc. There are many existing works used by CNN. And the accuracy of those are also high. So CNN is recognized as most useful method in image processing. So in this paper ResNet50, EfficientNetB3 and VGG19 are introduced. Those methods are also useful and bring more accuracy while performing image processing. In ResNet50 and VGG 19, there are 50 and 19 methods respectively. So those method can show a better possibility in future for image processing. Skin Disease is a now days, a concern thing which can be more dangerous if there is no proper detection path. For detecting perfectly image proceeding is the key. And those proposed methods can be crucial if those methods works perfectly. So in this paper ResNet50, EfficientNetB3 and VGG is introduced and will work through it. In future, Image processing will reach a higher level. So for this project it can be turn over to AI technology, so that the measurement would be more dynamic and accurate. So this work will recognize as a beginning of the work which will be pathway of future works. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Algorithms en_US
dc.subject Image processing en_US
dc.title Skin Disease Detection by Image Processing Using CNN en_US
dc.type Other en_US


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