This paper summarizes the top state-of-the-art contributions reported on the MNIST dataset
for handwritten digit recognition. This dataset has been extensively used to validate novel …

Background: Brain-Computer Interface (BCI) is becoming more reliable, thanks to the
advantages of Artificial Intelligence (AI). Recently, hybrid Deep Learning (hDL), which …

Integrating powerful machine learning models with flood risk assessment and determining
the potential mechanism between risk and the driving factors are crucial for improving flood …

In recent years, increased emphasis has been placed on the challenge of brine disposal,
driven by a heightened awareness of substantial environmental concerns associated with …

Land price is an important economic factor in producing meaningful references for regional
planners by assisting them in urban planning, economic decision-making, and land …

High voltage direct current (HVDC) transmission systems represent a significant
development for future power systems due to presenting promising solutions for long …

Efficient feature extraction is a pivotal requirement for Deep Neural Network (DNN) models,
particularly in the realm of visual tasks where effective feature extraction relies on well …

Accurate real-time prediction of flood inundation ranges and water depths is crucial for
effective flood warning and disaster mitigation. However, traditional hydrodynamic flooding …

Background and objective Patients with dysphagia show changes in articulation and voice
quality, and recent studies using machine learning models have been employed to help in …

Recent advances in (deep) machine learning offer new opportunities to solve indoor
fingerprint-based localization problems. However, the majority of localization solutions …