Please use this identifier to cite or link to this item: http//localhost:8080/jspui/handle/123456789/4947
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dc.contributor.authorHabes, Salah eddine-
dc.date.accessioned2022-07-17T14:31:30Z-
dc.date.available2022-07-17T14:31:30Z-
dc.date.issued2022-
dc.identifier.urihttp//localhost:8080/jspui/handle/123456789/4947-
dc.description.abstractNeurodegenerativediseases (ND) are a serious issue whichencompasses a myriad of complex and incurable disorders. in thisthesis, we focus on Parkinson’sdisease (PD), specifically; the detection of PD though the automaticanalysis of offline handwriting. To accomplishthistask; we propose Park-Net, ourownconvolutional neural network (CNN) architecture. Weproceed to test this CNN on three PD handwritingdatasetsbeforecomparing the results to state-of-the-art works, and with a 98%accuracy, and to the best of ourknowledge; Park-Net outperformsstudies as recent as (2022).en_US
dc.description.sponsorshipBennour A.en_US
dc.language.isoenen_US
dc.publisherLarbi Tebessi University - Tebessaen_US
dc.titleDetection of neurodegenerativediseases by the automaticanalysis of handwritingen_US
dc.typeThesisen_US
Appears in Collections:3- إعلام آلي



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