Polycystic ovary syndrome (PCOS) is the most prevalent endocrinological abnormality and
one of the primary causes of anovulatory infertility in women globally. The detection of …

The rapid development of deep learning in medical imaging has significantly enhanced the
capabilities of artificial intelligence while simultaneously introducing challenges, including …

Study region Flood formation involves complex nonlinear processes and numerous
variables, with data-driven models becoming a key non-engineering approach to flood …

Collapses are common geohazards during tunnel boring machine (TBM) construction under
complex geological conditions. This study proposes a tunnel collapse early warning method …

In the context of multi-label text classification (MLTC), Binary Relevance (BR) stands out as
one of the most intuitive and frequently employed methodologies. It tackles the MLTC task by …

Teeth scans are essential for many applications in orthodontics, where the teeth structures
are virtualized to facilitate the design and fabrication of the prosthetic piece. Nevertheless …

Chaos and unpredictability are traditionally synonymous, yet large-scale machine-learning
methods recently have demonstrated a surprising ability to forecast chaotic systems well …

Micro-expression recognition has gained much attention in research communities. Among
its proposed solutions, deep learning approaches have shown promising results over the …

Industrial inspection is crucial for maintaining quality and safety in industrial processes.
Deep learning models have recently demonstrated promising results in such tasks. This …

Vision-based gait emerged as the preferred biometric in smart surveillance systems due to
its unobtrusive nature. Recent advancements in low-cost depth sensors resulted in …