SearcharxivSearch

arXiv subjects

Shenglin Li

Publications and source records attributed to Shenglin Li.

3 recordsLinked to original sources

SatBLIP: Context Understanding and Feature Identification from Satellite Imagery with Vision-Language Learning

Rural environmental risks are shaped by place-based conditions (e.g., housing quality, road access, land-surface patterns), yet standard vulnerability indices are coarse and provide limited insight into risk contexts. We propose SatBLIP, a satellite-specific vision-language framework for rural context understanding and feature identification that predicts county-level Social Vulnerability Index (SVI). SatBLIP addresses limitations of prior remote sensing pipelines-handcrafted features, manual virtual audits, and natural-image-trained VLMs-by coupling contrastive image-text alignment with bootstrapped captioning tailored to satellite semantics. We use GPT-4o to generate structured descriptions of satellite tiles (roof type/condition, house size, yard attributes, greenery, and road context), then fine-tune a satellite-adapted BLIP model to generate captions for unseen images. Captions are encoded with CLIP and fused with LLM-derived embeddings via attention for SVI estimation under spatial aggregation. Using SHAP, we identify salient attributes (e.g., roof form/condition, street width, vegetation, cars/open space) that consistently drive robust predictions, enabling interpretable mapping of rural risk environments.

cs.CV

Learning Spatial-Aware Manipulation Ordering

Manipulation in cluttered environments is challenging due to spatial dependencies among objects, where an improper manipulation order can cause collisions or blocked access. Existing approaches often overlook these spatial relationships, limiting their flexibility and scalability. To address these limitations, we propose OrderMind, a unified spatial-aware manipulation ordering framework that directly learns object manipulation priorities based on spatial context. Our architecture integrates a spatial context encoder with a temporal priority structuring module. We construct a spatial graph using k-Nearest Neighbors to aggregate geometric information from the local layout and encode both object-object and object-manipulator interactions to support accurate manipulation ordering in real-time. To generate physically and semantically plausible supervision signals, we introduce a spatial prior labeling method that guides a vision-language model to produce reasonable manipulation orders for distillation. We evaluate OrderMind on our Manipulation Ordering Benchmark, comprising 163,222 samples of varying difficulty. Extensive experiments in both simulation and real-world environments demonstrate that our method significantly outperforms prior approaches in effectiveness and efficiency, enabling robust manipulation in cluttered scenes.

cs.RO

Broadband Terahertz Modulators based on MEMS-Reconfigurable Mesh Filters

Active tuning and switching of electromagnetic properties of materials is of great importance for controlling their interaction with electromagnetic waves. Superconductors are the only natural materials that exhibit diamagnetic switching at their critical temperatures. Here, we demonstrate a new class of meta-surfaces with electrically-induced diamagnetic switching capability at room temperature. Structural configuration of the subwavelength meta-molecules determines their magnetic response to an external electromagnetic radiation. By reconfiguration of the meta-molecule structure, the strength of the induced magnetic field in the opposite direction to the external magnetic field is varied and the diamagnetic state of the meta-surface is altered, consequently. We demonstrate a significant change in the relative permeability and permittivity of a custom-designed meta-surface with diamagnetic switching capability at terahertz frequencies, enabling terahertz intensity modulation with record high modulation depths and modulation bandwidths through a fully integrated device platform at room temperature.

physics.optics