H
Hwan Seung Yong
Publications - 4
Citations - 132
Hwan Seung Yong is an academic researcher. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.
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Journal ArticleDOI
Multiclass Skin Lesion Classification Using Hybrid Deep Features Selection and Extreme Learning Machine
Farhat Afza,Muhammad Irfan Sharif,Muhammad Attique Khan,Usman Tariq,Hwan Seung Yong,Jaehyuk Cha +5 more
TL;DR: A new method for multiclass skin lesion classification using best deep learning feature fusion and an extreme learning machine is proposed and the method’s accuracy is improved and the proposed method is computationally efficient.
Journal ArticleDOI
An Efficient Deep Learning Approach to Automatic Glaucoma Detection Using Optic Disc and Optic Cup Localization
Marriam Nawaz,Tahira Nazir,Ali Javed,Usman Tariq,Hwan Seung Yong,Muhammad Attique Khan,Jaehyuk Cha +6 more
TL;DR: A Deep Learning (DL)-based approach namely EfficientDet-D0 with EfficientNet-B0 as the backbone, which outperforms the newest frameworks and is more proficient in glaucoma classification and confirmed the robustness of the work by evaluating it on a challenging dataset.
Journal ArticleDOI
Cucumber Leaf Diseases Recognition Using Multi Level Deep Entropy-ELM Feature Selection
Muhammad Attique Khan,Abdullah Alqahtani,Aimal Khan,Shtwai Alsubai,Adel Binbusayyis,M Ch,Hwan Seung Yong,Jaehyuk Cha +7 more
TL;DR: An automated framework is proposed using deep learning and best feature selection for cucumber leaf diseases classification using machine learning classifiers and refined through the Entropy-ELM technique.
Journal ArticleDOI
Design and Implementation of a WML Converter and WML Editor for Automatic Generation of Wireless Internet Content
TL;DR: The design and development of a WML converter and WML editor is described that can convert HTML pages in real time into WML documents that are suitable for the WAP environment and provides an integrated WYSIWYG environment for creating, converting and publishing W ML documents.