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Found 6 papers, 1 papers with code
Charting New Territories: Exploring the Geographic and Geospatial Capabilities of Multimodal LLMs
Multimodal large language models (MLLMs) have shown remarkable capabilities across a broad range of tasks but their knowledge and abilities in the geographic and geospatial domains are yet to be explored, despite potential wide-ranging benefits to navigation, environmental research, urban development, and disaster response.
GPT4GEO: How a Language Model Sees the World's Geography
Large language models (LLMs) have shown remarkable capabilities across a broad range of tasks involving question answering and the generation of coherent text and code.
SATIN: A Multi-Task Metadataset for Classifying Satellite Imagery using Vision-Language Models
In this work, we introduce SATellite ImageNet (SATIN), a metadataset curated from 27 existing remotely sensed datasets, and comprehensively evaluate the zero-shot transfer classification capabilities of a broad range of vision-language (VL) models on SATIN.
3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training
In this paper, we propose the first 3D semantic mapping system from knee arthroscopy that solves the three challenges above.
Arthroscopic Multi-Spectral Scene Segmentation Using Deep Learning
Knee arthroscopy is a minimally invasive surgical (MIS) procedure which is performed to treat knee-joint ailment.
Learning-Based Procedural Content Generation
Procedural content generation (PCG) has recently become one of the hottest topics in computational intelligence and AI game researches.
