Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
Abstract: Clustering technology has important applications in data mining, pattern recognition, machine learning and other fields. However, with the explosive growth of data, traditional clustering ...
DETRIM.m Main Entry Point. Executes the hierarchical, multi-window search and iterative clustering. DETRIM_fwd_rev_cluster.m Performs the core clustering for a single time window, including forward ...
Introduction: Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as ...
Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...
The growing demand for energy-efficient Wireless Sensor Networks (WSNs) in applications such as IoT, environmental monitoring, and smart cities has sparked exhaustive research into practical solutions ...
PCA + MiniBatch KMeans offers a strong trade-off between performance and computational cost. SAE + DBSCAN produces high-quality clusters but requires significantly more training time. Visual ...
Abstract: Maintaining machinery wells, key to groundwater sustainability, is vital for managing these precious resources. In keeping with the need for effective groundwater management, this study ...
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