DFT-Net: Deep Feature Transformation Based Network for Object Categorization and Part Segmentation in 3-Dimensional Point Clouds.

Sheikh, Mehak; Asghar, Muhammad Adeel; Bibi, Ruqia; Malik, Muhammad Noman; Shorfuzzaman, Mohammad; Mehmood, Raja Majid; Kim, Sun-Hee

Sheikh, Mehak; Asghar, Muhammad Adeel; Bibi, Ruqia; Malik, Muhammad Noman; Shorfuzzaman, Mohammad; Mehmood, Raja Majid; Kim, Sun-Hee.

Afiliação

Sheikh M; Department of Computer Science, National University of Modern Languages, NUML, Rawalpindi 46000, Pakistan.
Asghar MA; Department of Computer Science, National University of Modern Languages, NUML, Rawalpindi 46000, Pakistan.
Bibi R; Department of Software Engineering, National University of Modern Languages, NUML, Rawalpindi 46000, Pakistan.
Malik MN; Department of Computer Science, National University of Modern Languages, NUML, Rawalpindi 46000, Pakistan.
Shorfuzzaman M; Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
Mehmood RM; Information and Communication Technology Department, School of Electrical and Computer Engineering, Xiamen University Malaysia, Sepang 43900, Malaysia.
Kim SH; Department of Brain & Cognitive Engineering, Korea University, Anam-dong, Seongbuk-ku, Seoul 02841, Korea.

Sensors (Basel) ; 22(7)2022 Mar 25.

Article em En | MEDLINE | ID: mdl-35408126

Palavras-chave

3D object categorization; classification; deep neural network; part segmentation; point cloud

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Paquistão

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