Convolutional Neural Networks (CNNs) are used in many domains but the requirement of
large datasets for robust training sessions and no overfitting makes them hard to apply in …

Planktonic organisms including phyto-, zoo-, and mixoplankton are key components of
aquatic ecosystems and respond quickly to changes in the environment, therefore their …

Algae represent the majority of the diversity on Earth and are a large group of organisms that
have photosynthetic properties that are important to life. The species of algae are estimated …

Image segmentation of the corneal endothelium with deep convolutional neural networks
(CNN) is challenging due to the scarcity of expert-annotated data. This work proposes a data …

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that presents
challenges for early diagnosis and treatment. Magnetic resonance imaging (MRI) is a …

Dynamical systems across the sciences, from electrical circuits to ecological networks,
undergo qualitative and often catastrophic changes in behavior, called bifurcations, when …

Obtaining high-quality images for training AI models in the field of plankton identification,
particularly cyanobacteria, is a challenging and time-critical task that necessitates the …

In this study, we made two new Songket Silungkang motifs and then tested them, then we
combined two new Songket motifs. The purpose of this research is to create a new Songket …

This research investigates the impact of data augmentation and noise injection on various
image filtering techniques employed for static image denoising and image recognition tasks …

Diatoms are a type of unicellular algae found in all aquatic environments. These organisms
are very sensitive to changes in water quality and habitat conditions. This characteristic …