15 citations · 19 across the 4 of their papers we have counts for
5 papers · 1 filter
BD Open LULC Map: High-resolution land use land cover mapping & benchmarking for urban development in Dhaka, Bangladesh
Mir Sazzat Hossain, Ovi Paul, Md Akil Raihan Iftee +7
Land Use Land Cover (LULC) mapping using deep learning significantly enhances the reliability of LULC classification, aiding in understanding geography, socioeconomic conditions, p…
BD-SAT: High-resolution Land Use Land Cover Dataset & Benchmark Results for Developing Division: Dhaka, BD
Ovi Paul, Abu Bakar Siddik Nayem, Anis Sarker +3
Land Use Land Cover (LULC) analysis on satellite images using deep learning-based methods is significantly helpful in understanding the geography, socio-economic conditions, povert…
A Novel Disaster Image Dataset and Characteristics Analysis using Attention Model
Fahim Faisal Niloy, Arif, Abu Bakar Siddik Nayem +6
The advancement of deep learning technology has enabled us to develop systems that outperform any other classification technique. However, success of any empirical system depends o…
Deep-learning coupled with novel classification method to classify the urban environment of the developing world
Qianwei Cheng, AKM Mahbubur Rahman, Anis Sarker +6
Rapid globalization and the interdependence of humanity that engender tremendous in-flow of human migration towards the urban spaces. With advent of high definition satellite image…
LULC Segmentation of RGB Satellite Image Using FCN-8
Abu Bakar Siddik Nayem, Anis Sarker, Ovi Paul +3
This work presents use of Fully Convolutional Network (FCN-8) for semantic segmentation of high-resolution RGB earth surface satel-lite images into land use land cover (LULC) categ…