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In this study, we explore methods for minimizing labeling costs, which is a critical issue in the active learning process. We focus on efficiently selecting the most essential datasets from an entire pool of unlabeled da...

This paper proposes an innovative model-free deep reinforcement learning-based controller (RL-C) for a grid-connected 5-level packed-U-cell (PUC5) multilevel inverter (MLI). The controller is designed to deliver a high-q...

Vegetation optical depth (VOD), as a key parameter of vegetation, plays an important role in the process of vegetation growth and change. The spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technolog...

Manual cocoa bean inspection is subjective and prone to error, significantly impacting chocolate production. This study presents an automated, high-throughput cocoa bean grading system leveraging YOLOv10, YOLOv11, and Vi...

Passive SONAR has attracted significant attention in covert operations, enabling vessel detection and classification through spectrogram analysis of received signals without active transmission. However, in realistic oce...

The shift toward sustainable and intelligent buildings has accelerated the demand for advanced maintenance strategies that reduce energy waste, downtime, and improve reliability. Traditional maintenance approaches (react...

Driven by satellite remote sensing observations, deep learning models provide a promising solution for the rapid estimation of subsurface thermohaline structures. By learning from large-scale paired surface–subsur...