A Ramachandran, AK Sangaiah - International Journal of Cognitive …, 2021 - Elsevier
Purpose Computer vision in drones has gained a lot of attention from artificial intelligence researchers. Providing intelligence to drones will resolve many real-time problems …
Semantic segmentation of remotely sensed urban scene images is required in a wide range of practical applications, such as land cover mapping, urban change detection …
Drones, or general UAVs, equipped with cameras have been fast deployed with a wide range of applications, including agriculture, aerial photography, and surveillance …
D Wang, J Zhang, B Du, M Xu, L Liu… - Advances in Neural …, 2024 - proceedings.neurips.cc
The success of the Segment Anything Model (SAM) demonstrates the significance of data- centric machine learning. However, due to the difficulties and high costs associated with …
Open-vocabulary semantic segmentation presents the challenge of labeling each pixel within an image based on a wide range of text descriptions. In this work we introduce a …
Due to its wide applications, remote sensing (RS) image semantic segmentation has attracted increasing research interest in recent years. Benefiting from its hierarchical abstract …
For robots to navigate and interact more richly with the world around them, they will likely require a deeper understanding of the world in which they operate. In robotics and related …
L Wang, R Li, D Wang, C Duan, T Wang, X Meng - Remote Sensing, 2021 - mdpi.com
Semantic segmentation from very fine resolution (VFR) urban scene images plays a significant role in several application scenarios including autonomous driving, land cover …
H Jung, HS Choi, M Kang - IEEE Transactions on Geoscience …, 2021 - ieeexplore.ieee.org
Image processing via convolutional neural network (CNN) has been developed rapidly for remote sensing technology. Moreover, techniques for accurately extracting building …