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Results show that deep learning architectures coupled with specialized attention mechanisms are viable approaches for robust performance on change detection tasks in bi-temporal satellite images.
Centralized deep-learning intrusion detection systems (IDS) are accurate, but they scale badly and require raw traffic to be collected on one server, which creates privacy and communication problems. Federated learning (FL) avoids moving the data: clients train a shared model and exchange only updates. Its weakness is...
Electroencephalography (EEG) has been investigated as a noninvasive approach for characterizing brain activity in neurodegenerative conditions. This study evaluated whether multidomain EEG biomarkers could distinguish Alzheimer's disease (AD), frontotemporal dementia (FTD), and healthy controls (HC). The publicly avail...
A lightweight two-step claim verification framework that decomposes LLM responses into atomic factual claims and independently verifies each extracted claim against a separately generated reference produced through an isolated factual recall prompt, showing consistent performance across the evaluated benchmarks without...
Experimental results demonstrate that task-specific acoustic conditioning and probability-guided speech segmentation improve speaker diarization, transcription, and word-level speaker attribution under challenging body-worn camera recording conditions.
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