Lightweight Surface Litter Detection Algorithm Based on Improved YOLOv5s

In response to the problem of the high cost and low efficiency of traditional water surface litter cleanup through manpower,a lightweight water surface litter detection algorithm based on improved YOLOv5s is proposed to provide core technical support for real-time water surface litter detection by water surface litter cleanup vessels.The method reduces network parameters by introducing the deep separable convolution GhostConv in the lightweight network GhostNet to substitute the ordinary convolution in the original YOLOv5s feature extraction and fusion network;introducing the C3Ghost module to substitute the C3 module in the original backbone and neck networks to further reduce computational effort.Using a Convolutional Block Attention Mechanism(CBAM)module in the backbone network to strengthen the network’s ability to extract significant target features from images.Finally,the loss function is optimized using the Focal-EIoU loss func-tion to improve the convergence speed and model accuracy.The experimental results illustrate that the improved algorithm outperforms the original Yolov5s in all aspects of the homemade water surface litter dataset and has certain advantages over some current mainstream algorithms in terms of model size,detection accuracy,and speed,which can deal with the problems of real-time detection of water surface litter in real life.

Landscape Effects on Decomposition

The average annual rainfall was close to the average for the Jornada Experimental Range basin (225 mm∙y−1). Decomposition of leaf litter bags on the soil surface was a function of the rainfall at the site and of soil texture. Sites with the highest splash erosion and infiltration (highest sand content) had the highest decomposition rates. There was no evidence that run-off, run-on processes had an effect on the decomposition of surface litter. Root decomposition was only different at one of the tarbush sites (p > 0.001) and that difference was primarily due to soil texture and spatial distribution of rainfall. High concentration of the clay-silt fraction resulted in differences in mass loss of surface litter at grassland, dry-lakes, and tarbush sites. One site at each of these was different from the other two sites because they are between 8 and 20 km from the other two sites.