Multiscale attention-based detection of tiny targets in aerial beach images

Tiny target detection in marine scenes is of practical importance in marine vision applications such as personnel search and rescue, navigation safety, and marine management. In the past few years, methods based on deep convolutional neural networks (CNN) have performed well for targets of common sizes. However, the accurate detection of tiny targets in marine scene images is affected by three difficulties: perspective multiscale, tiny target pixel ratios, and complex backgrounds. We proposed the feature pyramid network model based on multiscale attention to address the problem of tiny target detection in aerial beach images with large field-of-view, which forms the basis for the tiny target recognition and counting. To improve the ability of the tiny targets’ feature extraction, the proposed model focuses on different scales of the images to the target regions based on the multiscale attention enhancement module. To improve the effectiveness of tiny targets’ feature fusion, the pyramid structure is guided by the feature fusion module in order to give further semantic information to the low-level feature maps and prevent the tiny targets from being overwhelmed by the information at the high-level. Experimental results show that the proposed model generally outperforms existing models, improves accuracy by 8.56 percent compared to the baseline model, and achieves significant performance gains on the TinyPerson dataset. The code is publicly available via Github

Gallic Acid Accelerates the Oxidation Ability of the Peracetic Acid/Fe(III) System for Bisphenol A Removal: Fate of Various Radicals

Conveniently and cost-effectively obtained Fe(III) can be utilized for peracetic acid (PAA) activation in the presence of natural polyphenols. However, the effect of polyphenols on the fate of generated reactive oxygen species (ROS) remains unclear. In this study, it was demonstrated that Fe(III) can efficiently trigger PAA oxidation of pollutants with the assistance of gallic acid (GA), a widely distributed natural polyphenol. The GA/Fe(III)/PAA system efficiently removed bisphenol A (BPA) over a wide initial pH range of 4.0–7.0, with a removal rate of >90% over 20 min. Further, •OH played a dominant role in BPA degradation, and O2•– functioned as an intermediate contributing to the partial generation of •OH. The generated organic radicals (R-O•) did not considerably contribute to BPA removal. Apart from GA itself, both the reaction intermediates (phenoxy radicals) of GA with ROS and BPA degradation intermediates were crucial for the regeneration of Fe(II) from Fe(III) and the subsequent enhanced activation of PAA. Notably, further comprehensive analysis revealed an increase in •OH yield, but a decrease in R-O• production as the dosage of GA was increased from 10 to 100 μM. This finding emphasized the importance of properly utilizing GA, considering the reactivity of varied ROS toward different contaminants. R-O• (CH3CO2• and CH3CO3•) was quickly consumed by the GA-Fe(II) complex through single-electron transfer (SET) and/or by GA via H-abstraction (HAA). This study proposes a promising strategy for improving the Fe(III)/PAA process and advances the understanding of the trade-off between radical generation and elimination by polyphenols in PAA-based advanced oxidation processes (AOPs)