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In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

Reliable prognostics in predictive maintenance requires not only accurate remaining useful life (RUL) estimation but also robustness under distribution shift and support for decision-making under uncertainty. However, mo...

Wildfires are natural hazards that threaten ecosystems, communities, and economies, and they have shown a significant increase in frequency and intensity in recent years. Accurate wildfire spread prediction is critical f...

The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway transport. These systems can improve operational efficiency and safety, which ...

Spiking neural networks (SNNs) offer a biologically inspired, energy-efficient alternative to conventional artificial neural networks (ANNs). However, deep SNNs struggle to process complex EEG signals because their spike...

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...

Botnet communications often rely on Domain Generation Algorithms (DGAs) to establish channels among attack orchestrators and compromised hosts (bots). Our approach leverages on Artificial Intelligence (AI) to differentia...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

The rapid proliferation of unmanned aerial vehicles (UAVs) has created an urgent need for robust detection & identification systems to ensure airspace security and safety. However, the scarcity of large-scale, div...

As smart meter technology advances, advanced metering infrastructure (AMI) enables the collection of high-resolution energy consumption data, such as 15-minute interval electricity and gas usage. While anomaly detection ...

Question-answering (QA) has been a crucial NLP (Natural Language Processing) task for a long time. As an umbrella term, QA has multiple sub-tasks under its hood. Question classification (QC) is one of the most important ...

The validity of research findings critically depends on the selection of software samples. However, Mining Software Repositories studies often rely on outdated datasets and lack systematic, transparent procedures for rep...

Pixel-level segmentation is critical for remote sensing applications, yet traditional supervised methods suffer from high annotation costs. While foundational vision models like CLIP and the Segment Anything Model (SAM) ...