As a pivotal task within computer vision, object detection finds application across a diverse spectrum of industrial scenarios. The advent of deep learning technologies has significantly elevated the accuracy of object detectors designed for general-purpose applications. Nevertheless, in contrast to conventional terrestrial environments, remote sensing object detection scenarios pose formidable challenges, including intricate and diverse backgrounds, fluctuating object scales, and pronounced interference from background noise, rendering remote sensing object detection an enduringly demanding task.
View Article and Find Full Text PDFThe environmental pollution of organic ultraviolet absorbers (UVAs) has attracted global attention. However, the distribution, sources and risk assessment of UVAs in air from plastic greenhouses are rarely reported. This study was the first to investigate the concentrations of ten UVAs in the air samples from plastic greenhouses.
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