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RoadNet: A Deep Learning Framework for Road Extraction from Remote Sensing Data

Taspiya AlamDepartment of Computer Science and Engineering, Port City International University, Chittagong, State, BangladeshNafisa LubabaDepartment of Computer Science and Engineering, Port City International University, Chittagong, State, BangladeshTahmina AkterDepartment of Computer Science and Engineering, Port City International University, Chittagong, State, BangladeshMst. Sharmin AkterDepartment of Computer Science and Engineering, Port City International University, Chittagong, State, BangladeshMohammad Tarek AzizDepartment of CSE, Chittagong University of Engineering and Technology, Chittagong, 4331, BangladeshMahmud TanjimDepartment of CSE, Rangamati Science and Technology University, Rangamati, 4500, BangladeshG.M. Sakhawat HossainDepartment of CSE, Rangamati Science and Technology University, Rangamati, 4500, BangladeshMd. KhaliluzzamanDepartment of CSE, Chittagong University of Engineering and Technology, Chittagong, 4331, BangladeshNurullaeva NodiraAtayev ShokirUrgench State University, Urgench, UzbekistanAbubokor HanipWashington University of Science and Technology, 2900 Eisenhower Ave, Alexandria, VA, 22314, USAMohammad Shahadat HossainDepartment of CSE, University of Chittagong, Chittagong, 4331, Bangladesh

Communications in computer and information sciencebook series2025en

ABI

Annotatsiya

Annotatsiya mavjud emas.

Mavzular

Automated Road and Building Extraction Autonomous Vehicle Technology and Safety Remote-Sensing Image Classification

Identifikatorlar

DOI: 10.1007/978-3-032-11355-9_18

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