Search Results for author:
Found 5 papers, 3 papers with code
Enhancing Environmental Monitoring through Multispectral Imaging: The WasteMS Dataset for Semantic Segmentation of Lakeside Waste
This study introduces WasteMS, the first multispectral dataset established for the semantic segmentation of lakeside waste.
Seg-LSTM: Performance of xLSTM for Semantic Segmentation of Remotely Sensed Images
Recent advancements in autoregressive networks with linear complexity have driven significant research progress, demonstrating exceptional performance in large language models.
Rethinking Scanning Strategies with Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study
In this research, we conduct a comprehensive experimental investigation on the impact of mainstream scanning directions and their combinations on semantic segmentation of remotely sensed images.
Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model
The results reveal that Samba achieved unparalleled performance on commonly used remote sensing datasets for semantic segmentation.
Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey
Deep learning (DL) has become one of the mainstream and effective methods for point cloud analysis tasks such as detection, segmentation and classification.
