Enhancing semantic segmentation of Ecuadorian shrimp ponds through fine-tuned vision transformers and U-Net architectures utilizing open-source remote sensing data
Aquaculture has emerged as an important pillar of global food production, and shrimp farming plays a critical role in fulfilling the growing demand for seafood. This is especially true in Ecuador, which is recognized as one of the world's largest exporters and producers of shrimp. However, conv...
Saved in:
| Main Authors: | Daniel Jacome, Jianghao Wang, Yong Ge |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
|
| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2538214 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Bridging Sensor Gaps via Attention-Gated Tuning for Hyperspectral Image Classification
by: Xizhe Xue, et al.
Published: (2025-01-01) -
Tumor ViT-GRU-XAI: Advanced Brain Tumor Diagnosis Framework: Vision Transformer and GRU Integration for Improved MRI Analysis: A Case Study of Egypt
by: Mohammed Aly, et al.
Published: (2024-01-01) -
Hangul Character Recognition of A New Hangul Dataset with Vision Transformers Model
by: Aurelia Shana, et al.
Published: (2024-12-01) -
Fine-Tuning and the Multiverse Argument Against Naturalism
by: Rad Miksa
Published: (2024-10-01) -
GIVTED-Net: GhostNet-Mobile Involution ViT Encoder-Decoder Network for Lightweight Medical Image Segmentation
by: Resha Dwika Hefni Al-Fahsi, et al.
Published: (2024-01-01)