Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

Salient object detection models mimic the behavior of human beings and capture the most
salient region/object from the images or scenes, this field contains many important …

显著性目标检测旨在对图像中最显著的对象进行检测和分割, 是计算机视觉任务中重要的预处理
步骤之一, 且在信息检索, 公共安全等领域均有广泛的应用. 本文对近期基于深度学习的显著性 …

Salient object detection is a key step in many image analysis tasks as it not only identifies
relevant parts of a visual scene but may also reduce computational complexity by filtering …

Recent progress in salient object detection (SOD) mainly depends on dilated convolution
with different receptive fields to capture contextual information for multi-scale learning …

In this paper, we propose an efficient and discriminative saliency method that takes
advantage of background divergence and foreground compactness. Concretely, a graph is …

Smart city infrastructure for lightning detection is one of the most important parameters for
building protection. To get outcomes within a short frame of time having high accuracy …

There have been remarkable improvements in the salient object detection in the recent
years. During the past few years, graph-based saliency detection algorithms have been …

Hyperspectral salient object detection (HSOD) aims to extract targets or regions with
significantly different spectra from hyperspectral images. While existing deep learning-based …

Existing road marking detection primarily focuses on the direction, position, and color of road
markings. However, clear and accurate road markings directly impact issues such as …