Deep learning (DL) based instance segmentation has attracted a growing research interest
in the scientific community to tackle precision agriculture problems over the past few years …

This study presents a novel approach to identifying trolls and toxic content on social media
using deep learning. We developed a machine-learning model capable of detecting toxic …

A trademark's image is usually the first type of indirect contact between a consumer and a
product or a service. Companies rely on graphical trademarks as a symbol of quality and …

Nonmydriatic retinal fundus images often suffer from quality issues and artifacts due to
ocular or systemic comorbidities, leading to potential inaccuracies in clinical diagnoses. In …

The rise of multi-modal unstructured data has intensified the need for advanced processing
solutions capable of deriving meaningful insights efficiently. UDNet emerges as a concurrent …

With the extension of road service life, cracks are the most significant type of pavement
distress. To monitor road conditions and avoid excessive damage, pavement crack detection …

Reinforcement learning (RL) is a dynamic and evolving subfield of machine learning that
focuses on training intelligent agents to learn and adapt through interactions with their …

High-power laser facilities necessitate predicting incremental damage to final optics to
identify evolving damage trends. In this study, we propose a surface damage detection …

Cataracts, known for lens clouding and being a common cause of visual impairment, persist
as a primary contributor to vision loss and blindness, presenting notable diagnostic and …

The nuclear imaging system at the National Ignition Facility (NIF) is a crucial diagnostic for
determining the geometry of inertial confinement fusion implosions. The geometry is …