Tashnim Chowdhury

According to our database, Tashnim Chowdhury authored at least 8 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

SAM-VQA: Supervised Attention-Based Visual Question Answering Model for Post-Disaster Damage Assessment on Remote Sensing Imagery.

Argho Sarkar, Tashnim Chowdhury, Robin Roberson Murphy, Aryya Gangopadhyay, Maryam Rahnemoonfar

IEEE Trans. Geosci. Remote. Sens., 2023

2022

RescueNet: A High Resolution UAV Semantic Segmentation Benchmark Dataset for Natural Disaster Damage Assessment.

Tashnim Chowdhury, Robin R. Murphy, Maryam Rahnemoonfar

CoRR, 2022

2021

Airborne Snow Radar Data Simulation With Deep Learning and Physics-Driven Methods.

Masoud Yari, Oluwanisola Ibikunle, Debvrat Varshney, Tashnim Chowdhury, Argho Sarkar, John Paden, Jilu Li, Maryam Rahnemoonfar

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding.

Maryam Rahnemoonfar, Tashnim Chowdhury, Argho Sarkar, Debvrat Varshney, Masoud Yari, Robin Roberson Murphy

IEEE Access, 2021

Attention Based Semantic Segmentation on UAV Dataset for Natural Disaster Damage Assessment.

Tashnim Chowdhury, Maryam Rahnemoonfar

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

Self Attention Based Semantic Segmentation on a Natural Disaster Dataset.

Tashnim Chowdhury, Maryam Rahnemoonfar

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Comparative Study Between Real-Time and Non-Real-Time Segmentation Models on Flooding Events.

Farshad Safavi, Tashnim Chowdhury, Maryam Rahnemoonfar

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Comprehensive Semantic Segmentation on High Resolution UAV Imagery for Natural Disaster Damage Assessment.

Tashnim Chowdhury, Maryam Rahnemoonfar, Robin R. Murphy, Odair Fernandes

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020