Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Despite significant progress in the past few years, machine learning systems are still often
viewed as" black boxes", which lack the ability to explain their output decisions. In high …

Measuring perceptions of visual walkability in urban streets and exploring the associations
between the visual features of the street built environment that make walking attractive to …

Maize leaf diseases significantly reduce maize yield; therefore, monitoring and identifying
the diseases during the growing season are crucial. Some of the current studies are based …

The rising prevalence of gastrointestinal (GI) tract disorders worldwide highlights the urgent
need for precise diagnosis, as these diseases greatly affect human life and contribute to …

Despite the great progress of person re-identification (ReID) with the adoption of
Convolutional Neural Networks, current ReID models are opaque and only outputs a scalar …

Aims: Brain diseases refer to intracranial tissue and organ inflammation, vascular diseases,
tumors, degeneration, malformations, genetic diseases, immune diseases, nutritional and …

Quantitative photoacoustic tomography (QPAT) is a valuable tool in characterizing ovarian
lesions for accurate diagnosis. However, accurately reconstructing a lesion's optical …

This paper proposes an attributable visual similarity learning (AVSL) framework for a more
accurate and explainable similarity measure between images. Most existing similarity …

Artificial intelligence and its derivative technologies are not only playing a role in the fields of
medicine, economy, policing, transportation, and natural science computing today but also …