Luminescence imaging techniques assume a critical role in the evaluation of the durability and lifespan of solar cells. This study presents a novel empirical approach that capitalizes on simple machine learning-based linear regression (MLLR) to progn... read more
An enchondroma is a benign neoplasm of mature hyaline cartilage that proliferates from the medullary cavity toward the cortical bone. This results in the formation of a significant endogenous mass within the medullary cavity. Although enchondromas ar... read more
Brain-inspired Spiking Neural Networks (SNNs) exhibit significant potential
for low-power computation, yet their application in visual tasks remains
largely confined to image classification, object detection, and event-based
tracking. In contrast, ... read more
Monitoring the effects of the chemotherapeutic agent Taxol at the cellular
level is critical for both clinical evaluation and biomedical research.
However, existing detection methods require specialized equipment, skilled
personnel, and extensive s... read more
The extended Gaussian family is the closure of the Gaussian family obtained
by completing the Gaussian family with the counterpart elements induced by
degenerate covariance or degenerate precision matrices, or a mix of both
degeneracies. The parame... read more
In one-stage multi-object detection tasks, various intersection over union
(IoU)-based solutions aim at smooth and stable convergence near the targets
during training. However, IoU-based losses fail to correctly update the
gradient of small objects... read more
Recent years have witnessed remarkable achievements in perceptual image
restoration (IR), creating an urgent demand for accurate image quality
assessment (IQA), which is essential for both performance comparison and
algorithm optimization. Unfortun... read more
The paper presents a novel technique for creating a 6D pose estimation
dataset for marine vessels by fusing monocular RGB images with Automatic
Identification System (AIS) data. The proposed technique addresses the
limitations of relying purely on ... read more
The Model Context Protocol has emerged as a transformative standard for
connecting large language models to external data sources and tools, rapidly
gaining adoption across major AI providers and development platforms. However,
existing benchmarks ... read more
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