数据融合是最大程度发挥大数据价值的关键, 深度学习是挖掘数据深层特征信息的技术利器,
基于深度学习的数据融合能够充分挖掘大数据潜在价值, 从新的深度和广度拓展对世界的探索和 …

Object detection studies aim to solve safety problems at industrial sites; however, improving
object detection performance and ensuring real-time capabilities simultaneously remains …

Existing methods based on convolutional neural networks (CNNs) have progressed
significantly in the salient object detection task. However, in some cases, the accurate …

Recent deep learning-based salient object detection methods have achieved impressive
performance by leveraging multi-level convolutional features, which contain informative and …

In this paper, an Edge-information Guided Multi-scale Feature-fusion Network (EGMFNet) is
proposed to solve the problems of unclear boundary and incomplete structure of saliency …

Saliency detection is a computer vision task that has been studied for a long time. Although
the recent methods continuously improve detection accuracy, most of them do not consider …

针对基于FCN 和U 型网络架构的深度学习显著性目标检测方法提取的显著性图存在边界不清晰
和结构不完整的问题, 文中提出了一种基于边缘信息引导多级尺度特征融合网络(EGMFNet) …

Salient object detection is a traditional topic in computer vision that has attracted a lot of
interest recent years. It detects the most salient object in an image and then segments the …

Salient object detection (SOD) is particularly important especially for applications like
autonomous driving which requires real-time inference speed and high performance. Most …