Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified blueprint for researchers to navigate classification, clustering, ...
Abstract: Overcoming class imbalance is a critical challenge for graph-based semi-supervised classification methods. In this letter, we address this issue from the perspective of graph filtering and ...
Abstract: Terrain classification is essential for traversability estimation and planning of autonomous ground vehicles (AGVs) in complex environments. Most existing approaches utilize fully supervised ...
ABSTRACT: Change-detection analysis highlighted significant declines in sparse forest (−72.88%) and wetlands (−73.49%), alongside a substantial increase in bare land (+55.26%). These trends underscore ...
ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Crop identification and monitoring of crop dynamics are essential for agricultural planning, environmental monitoring, and ensuring food security. Recent advancements in remote sensing technology and ...
Background: Free-text comments in patient-reported outcome measures (PROMs) data provide insights into health-related quality of life (HRQoL). However, these comments are typically analysed using ...
This notebook tested the performance of the following scikit-learn models: Logistic Regression, Multilayer Perception, Naive Bayes, KNN, and Random Forest Classifier in classifying whether a person ...
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