Correction: Recognition of mulberry leaf diseases based on multi-scale residual network fusion SENet.

[This corrects the article DOI: 10.1371/journal.pone.

Recognition of mulberry leaf diseases based on multi-scale residual network fusion SENet.

Silkworms are insects with important economic value, and mulberry leaves are the food of silkworms. The quality and quantity of mulberry leaves have a direct impact on cocooning. Mulberry leaves are often infected with various diseases during the growth process.

Height detection of crop divider toes of sugarcane harvester based on Kalman adaptive adjustment.

Crop divider toes are an essential device of sugarcane harvester. Moving forward against the ground is a critical way to improve the harvesting rate of lodged sugarcane. Height detection is the basis for precise control of crop divider toes moving forward against the ground.

Application of improved YOLOv7-based sugarcane stem node recognition algorithm in complex environments.

Introduction: Sugarcane stem node detection is one of the key functions of a small intelligent sugarcane harvesting robot, but the accuracy of sugarcane stem node detection is severely degraded in complex field environments when the sugarcane is in the shadow of confusing backgrounds and other objects.

Methods: To address the problem of low accuracy of sugarcane arise node detection in complex environments, this paper proposes an improved sugarcane stem node detection model based on YOLOv7. First, the SimAM (A Simple Parameter-Free Attention Module for Convolutional Neural Networks) attention mechanism is added to solve the problem of feature loss due to the loss of image global context information in the convolution process, which improves the detection accuracy of the model in the case of image blurring; Second, the Deformable convolution Network is used to replace some of the traditional convolution layers in the original YOLOv7.