Deep learning-based intelligent vehicle perception has been developing prominently in
recent years to provide a reliable source for motion planning and decision making in …

Joint use of multisensor information has attracted considerable attention in the remote
sensing community. While applications in land-cover observation benefit from information …

The balance between high accuracy and high speed has always been a challenging task in
semantic image segmentation. Compact segmentation networks are more widely used in the …

In this work, the best size for late gadolinium enhancement (LGE) magnetic resonance
imaging (MRI) images in the training dataset was determined to optimize deep learning …

Computer vision applications in intelligent transportation systems (ITS) and autonomous
driving (AD) have gravitated towards deep neural network architectures in recent years …

In recent years, vehicle detectors built on deep convolutional neural network (DCNN) have
been widely used in autonomous driving. Under the complex conditions of road traffic, the …

Recent works on semantic segmentation witness significant performance improvement by
utilizing global contextual information. In this paper, an efficient multi-granularity based …

Regarding increasingly complex scenarios in hand gesture recognition (HGR), it is
challenging to implement a reliable HGR due to the nonadaptability of individual sensors to …

Online monitoring of pellet size distribution (PSD) of green pellets is an important work in
product quality control of pelletization process. Conventionally, image segmentation …

Semantic segmentation involves classifying each pixel into one of a pre-defined set of
object/stuff classes. Such a fine-grained detection and localization of objects in the scene is …