Three architectures for pixel-level extraction of features from light detection and ranging (lidar)-derived land surface parameters (LSPs) are compared: SegUNet and the UNet typically achieve the best precision and recall balance and the smoothest optimization, and UNet-style architectures with CNN-based decoders generalize most reliably.
Borehole detection in textured quarry reconstructions is challenging because shadows, rocks, and fractured ground can resemble visible surface openings. We introduce GeoBoreNet, which augments RGB with four pixel-aligned inputs derived from reconstructed surface height: local residual relief, spatial gradient magnitude...
Xue-Song Liu, Wen Cao, An-Ke Xu et al.· Italian National Conference...· 0 citations
Spatial downscaling of satellite imagery, the reconstruction of high-resolution outputs from coarser-resolution inputs, is a critical enabler of long-term land cover monitoring, yet the domain adaptation gap between natural-image super-resolution models and satellite sensor characteristics remains largely unaddressed....
Juan Valdés-Quintero, R. D. Vásquez-Salazar, J. C. Parra et al.· Italian National Conference...· 0 citations
The combination of Embedding V1, MLP, and Aitchison distance loss achieved the best overall performance, suggesting that foundation model embeddings combined with compositional losses can improve sub-pixel land-cover estimation.
Ayato Kanno, N. Tsutsumida· The International Archives o...· 0 citations
Rapid lithology identification on open-pit bench faces is typically performed manually by geologists, yet it is subjective, inconsistent under variable field conditions, and cannot be scaled to the large image volumes required by conventional supervised deep learning. We present GeoProtoNet, a lightweight few-shot lear...
Umirzokov Azamat, Shokhjakhon Abdufattokhov, Ryumduk Oh et al.· Journal of engineering and a...· 0 citations
Terraced fields are difficult to delineate from high-resolution imagery because narrow and irregular boundaries, fragmented patches, and visual similarity to adjacent cropland can lead to omission errors and boundary confusion. This study adapts DeepLabV3+ for terraced field extraction from 2 m GF-1 RGB imagery through...
Jia-Lin Li, Jie-Lin Tang, Bo Jia et al.· Remote Sensing· 0 citations
This work presents MarsRecon, a geospatially aware pipeline for learning visual and multimodal representations from HiRISE observations of Olympus Mons, and establishes a working Mars-specific pretraining and retrieval pipeline.
Akshay Naik, Marius F. R. Juston, Jay Mahajan· 0 citations
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