Comparison of reference libraries for the detection of tire-derived microplastics (TMPs).

Introducing microplastics (MPs) into the marine environment is a global problem. Tire-derived microplastics (TMPs) are estimated to account for 60% of all secondary MPs dispersed in aquatic environments. To effectively detect TMPs in environmental samples using micro-Fourier transform infrared (μFTIR) spectroscopy, a high-quality reference library is essential.

Lightweight Tunnel Obstacle Detection Based on Improved YOLOv5.

Considering the high incidence of accidents at tunnel construction sites, using robots to replace humans in hazardous tasks can effectively safeguard their lives. However, most robots currently used in this field require manual control and lack autonomous obstacle avoidance capability. To address these issues, we propose a lightweight model based on an improved version of YOLOv5 for obstacle detection.

Artificial intelligence-aided diagnostic imaging: A state-of-the-art technique in precancerous screening.

Background And Aim: Chromoendoscopy with the use of indigo carmine (IC) dye is a crucial endoscopic technique to identify gastrointestinal neoplasms. However, its performance is limited by the endoscopist's skill, and no standards are available for lesion identification. Thus, we developed an artificial intelligence (AI) model to replace chromoendoscopy.