The primary objective of this study is to develop an advanced, automated system for the
early detection and classification of leaf diseases in potato plants, which are among the most …

Deep convolutional neural networks have gained aggressive success in salient object
detection. This paper uses the Multi-Scale Feature Extraction Module (MFEM) for each …

Salient object detection (SOD) is a challenging task in computer vision. Current SOD
approaches have made significant progress, but they fail in challenging scenarios. This …

Salient object detection (SOD) is a critical task in computer vision that involves accurately
identifying and segmenting visually significant objects in an image. To address the …

Breast tumor segmentation is vital to tumor detection at the early stages. Deep learning
methods are typically used in automatic tumor segmentation tasks. However, in existing …

The salient object detection (SOD) technology predicts which object will attract the attention
of an observer surveying a particular scene. Most state-of-the-art SOD methods are top …

In view of the common problems in image saliency detection, such as inaccurate positioning
of saliency objects and easy loss of detail information in complex scenario. This paper …

Convolutional neural networks originate from image classification tasks. The pooling
operation can expand the receptive field and reduce the amount of calculation, but a large …