Artificial Intelligence (AI) has emerged as a useful aid in numerous clinical applications for
diagnosis and treatment decisions. Deep neural networks have shown the same or better …

Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …

Deep learning approaches have recently raised the bar in many fields, from Natural
Language Processing to Computer Vision, by leveraging large amounts of data. However …

Humans are able to learn to recognize new objects even from a few examples. In contrast,
training deep-learning-based object detectors requires huge amounts of annotated data. To …

Background. Artificial intelligence (AI) has developed rapidly, and its application extends to
clinical decision support system (CDSS) for improving healthcare quality. However, the …

Deep learning techniques have found applications across diverse fields, enhancing the
efficiency and effectiveness of decision-making processes. The integration of these …

We present a novel and computationally efficient method for the detection of meniscal tears
in Magnetic Resonance Imaging (MRI) data. Our method is based on a Convolutional …

Few-shot object detection (FSOD) aims to extract semantic knowledge from limited object
instances of novel categories within a target domain. Recent advances in FSOD focus on …

So far, few researchers have targeted the explainability of point cloud neural networks. Part
of the explainability methods are not directly applicable to those networks due to the …

Natural protected areas are vital for biodiversity, climate change mitigation, and supporting
ecological processes. Despite their significance, comprehensive mapping is hindered by a …