A hybrid SA-POMDP framework for adaptive mine planning under geological uncertainty reduces the expectation-reality gap from 22.3% to 4.6% and improves realized NPV by up to USD44.6M compared with conventional one-shot stochastic optimization.
Garbage Detection using Advanced Object Detection Techniques
3 Pith papers cite this work. Polarity classification is still indexing.
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Evaluates concept drift effects on ML phishing detectors and explores mitigation strategies.
YOLOv8 achieves the highest mAP of 80.9% for detecting 15 classes of underwater waste among the tested models.
citing papers explorer
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Adaptive mine planning under geological uncertainty: A POMDP framework for sequential decision-making
A hybrid SA-POMDP framework for adaptive mine planning under geological uncertainty reduces the expectation-reality gap from 22.3% to 4.6% and improves realized NPV by up to USD44.6M compared with conventional one-shot stochastic optimization.
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Evaluating and Combating the Impact of Concept Drift on the Performance of Machine Learning-Based Phishing Detection Systems
Evaluates concept drift effects on ML phishing detectors and explores mitigation strategies.
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Underwater Waste Detection Using Deep Learning A Performance Comparison of YOLOv7 to 10 and Faster RCNN
YOLOv8 achieves the highest mAP of 80.9% for detecting 15 classes of underwater waste among the tested models.