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Found 5 papers, 1 papers with code
SonoSAMTrack -- Segment and Track Anything on Ultrasound Images
In this paper, we present SonoSAMTrack - that combines a promptable foundational model for segmenting objects of interest on ultrasound images called SonoSAM, with a state-of-the art contour tracking model to propagate segmentations on 2D+t and 3D ultrasound datasets.
Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management
Traditional ML methods used for fire modeling offer computational speedup but struggle with physically inconsistent predictions, biased predictions due to class imbalance, biased estimates for fire spread metrics (e. g., burned area, rate of spread), and generalizability in out-of-distribution wind conditions.
Effectiveness of the Recent Advances in Capsule Networks
Convolutional neural networks (CNNs) have revolutionized the field of deep neural networks.
Merged-GHCIDR: Geometrical Approach to Reduce Image Data
We propose two variations: Geometrical Homogeneous Clustering for Image Data Reduction (GHCIDR) and Merged-GHCIDR upon the baseline algorithm - Reduction through Homogeneous Clustering (RHC) to achieve better accuracy and training time.
Geometrical Homogeneous Clustering for Image Data Reduction
The intuition behind the first approach, RHCKON, is that the boundary points contribute significantly towards the representation of clusters.
