Pengenalan Bahasa Isyarat Tangan Menggunakan Arsitektur Googlenet

Please use this identifier to cite or link to this item: https://repositori.uma.ac.id/handle/123456789/28108

Full metadata record

DC Field	Value	Language
dc.contributor.advisor	Muhathir	-
dc.contributor.author	Sihombing, Jhon David	-
dc.date.accessioned	2025-08-26T02:08:30Z	-
dc.date.available	2025-08-26T02:08:30Z	-
dc.date.issued	2025-03-11	-
dc.identifier.uri	https://repositori.uma.ac.id/handle/123456789/28108	-
dc.description	76 Halaman	en_US
dc.description.abstract	Dalam beberapa tahun erakhir, penggunaan model pembelajaran mendalam khususnya convolutional neural network, telah menjadi pendekatan dominan dalam tugas klasifikasi citra In recent years, the use of deep learning models, particularly convolutional neural networks, has become the dominant approach in image classification tasks.	en_US
dc.language.iso	id	en_US
dc.publisher	Universitas Medan Area	en_US
dc.relation.ispartofseries	NPM;198160019	-
dc.subject	bahasa isyarat tangan	en_US
dc.subject	sign language	en_US
dc.subject	googlenet	en_US
dc.subject	optimizer	en_US
dc.subject	klasifikasi	en_US
dc.subject	cnn	en_US
dc.title	Pengenalan Bahasa Isyarat Tangan Menggunakan Arsitektur Googlenet	en_US
dc.title.alternative	Hand Sign Language Recognition Using Googlenet Architecture	en_US
dc.type	Thesis	en_US
Appears in Collections:	SP - Informatic Engineering

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File	Description	Size	Format
198160019 - Jhon David Sihombing - Chapter IV.pdf Restricted Access	Chapter IV	1.64 MB	Adobe PDF	View/Open Request a copy
198160019 - Jhon David Sihombing - Fulltext.pdf	Cover, Abstract, Chapter I, II, III, V, Bibliography	2.84 MB	Adobe PDF	View/Open