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Found 7 papers, 1 papers with code
GeoAI Reproducibility and Replicability: a computational and spatial perspective
We then discuss the factors that may cause the lack of R&R in GeoAI research, with an emphasis on (1) the selection and use of training data; (2) the uncertainty that resides in the GeoAI model design, training, deployment, and inference processes; and more importantly (3) the inherent spatial heterogeneity of geospatial data and processes.
Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model's Generalizability in Permafrost Mapping
To evaluate the performance of large AI vision models, especially Meta's Segment Anything Model (SAM), we implemented different instance segmentation pipelines that minimize the changes to SAM to leverage its power as a foundation model.
Assessment of a new GeoAI foundation model for flood inundation mapping
Vision foundation models are a new frontier in Geospatial Artificial Intelligence (GeoAI), an interdisciplinary research area that applies and extends AI for geospatial problem solving and geographic knowledge discovery, because of their potential to enable powerful image analysis by learning and extracting important image features from vast amounts of geospatial data.
Real-time GeoAI for High-resolution Mapping and Segmentation of Arctic Permafrost Features
This paper introduces a real-time GeoAI workflow for large-scale image analysis and the segmentation of Arctic permafrost features at a fine-granularity.
Explainable GeoAI: Can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection
This paper compares popular saliency map generation techniques and their strengths and weaknesses in interpreting GeoAI and deep learning models' reasoning behaviors, particularly when applied to geospatial analysis and image processing tasks.
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection
This paper reports a new solution of leveraging temporal classification to support weakly supervised object detection (WSOD).
Generation of sub-MHz and spectrally-bright biphotons from hot atomic vapors with a phase mismatch-free scheme
The generation rate per linewidth of the 610-kHz biphoton source is 1, 500 pairs/(s$\cdot$MHz), which is the best result of all the sub-MHz biphoton sources in the literature.
Quantum Physics
