Deep learning networks powered by AI are essential predictive tools relying on image data
availability and processing hardware advancements. However, little attention has been paid …

Microplastics (MPs), measuring less than 5 mm, pose threats to ecological security and
human health in urban waters. Additionally, they act as carriers, transporting pollutants from …

Since light propagation in water bodies is subject to absorption and scattering effects,
underwater images using only conventional intensity cameras will suffer from low …

Abstract Microplastics, particularly microfibres (< 5 mm), are a significant environmental
pollutant. Detecting and quantifying them in complex matrices is challenging and time …

IoT (Internet-of-Things) powered devices can be exploited to connect vehicles to a smart city
infrastructure and thus allow vehicles to share their intentions while retrieving contextual …

Plastic products' widespread applications and their non-biodegradable nature have resulted
in the continuous accumulation of microplastic waste, emerging as a significant component …

In the study, we have combined speckle metrology and deep learning tools in discriminating
supermicroplastics (SMPs) sizes and concentrations. Polystyrene spheres used as SMPs …

Rapid and accurate measurements of microplastic residues in biological tissues are crucial
for determining exposure levels and studying microplastic invasion mechanisms. However …

The contamination of microplastics (MPs) creates a substantial risk to both the environment
and human health, necessitating the development of efficient methods for detecting and …

We introduce a novel microscopic image dataset augmented with segmentation and
detection labels specifically designed for microplastic analysis in sewage environments …