Fully convolutional neural networks (FCNs) have shown their advantages in the salient
object detection task. However, most existing FCNs-based methods still suffer from coarse …

Salient object detection is a fundamental computer vision task. The majority of existing
algorithms focus on aggregating multi-level features of pre-trained convolutional neural …

We present an effective method to progressively integrate and refine the cross-modality
complementarities for RGB-D salient object detection (SOD). The proposed network mainly …

Machine learning and computer vision methods are showing good performance in medical
imagery analysis. Yet only a few applications are now in clinical use and one of the reasons …

With the rapid development of machine learning, its powerful function in the machine vision
field is increasingly reflected. The combination of machine vision and robotics to achieve the …

Fully Convolutional Neural Network (FCN) has been widely applied to salient object
detection recently by virtue of high-level semantic feature extraction, but existing FCN-based …

Significant advances in video compression systems have been made in the past several
decades to satisfy the near-exponential growth of Internet-scale video traffic. From the …

Deep learning-based methods especially using convolutional neural network (CNN) and
generative adversarial network (GAN) have achieved certain success for the task of image …

Recent progress on salient object detection mainly aims at exploiting how to effectively
integrate multiscale convolutional features in convolutional neural networks (CNNs). Many …

Recently, researchers have paid more attention to salient object detection (SOD) of strip
steel surface defects, but there are lots of difficulties, such as a mass of noise, blurry defect …