[HTML][HTML] Deep transfer learning for intelligent vehicle perception: A survey
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 …
recent years to provide a reliable source for motion planning and decision making in …
YOLOv4-5D: An effective and efficient object detector for autonomous driving
Y Cai, T Luan, H Gao, H Wang, L Chen… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The use of object detection algorithms has become extremely important in autonomous
vehicles. Object detection at high accuracy and a fast inference speed is essential for safe …
vehicles. Object detection at high accuracy and a fast inference speed is essential for safe …
Semantic segmentation with context encoding and multi-path decoding
Semantic image segmentation aims to classify every pixel of a scene image to one of many
classes. It implicitly involves object recognition, localization, and boundary delineation. In …
classes. It implicitly involves object recognition, localization, and boundary delineation. In …
IoT-based route recommendation for an intelligent waste management system
The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors
and services. These sensors are incorporated to collect various information, track physical …
and services. These sensors are incorporated to collect various information, track physical …
Domain adaptation from daytime to nighttime: A situation-sensitive vehicle detection and traffic flow parameter estimation framework
Vehicle detection in traffic surveillance images is an important approach to obtain vehicle
data and rich traffic flow parameters. Recently, deep learning based methods have been …
data and rich traffic flow parameters. Recently, deep learning based methods have been …
Semantic-aware scene recognition
Scene recognition is currently one of the top-challenging research fields in computer vision.
This may be due to the ambiguity between classes: images of several scene classes may …
This may be due to the ambiguity between classes: images of several scene classes may …
Enabling edge-cloud video analytics for robotics applications
Emerging deep learning-based video analytics tasks demand computation-intensive neural
networks and powerful computing resources on the cloud to achieve high accuracy. Due to …
networks and powerful computing resources on the cloud to achieve high accuracy. Due to …
Geospatial transformer is what you need for aircraft detection in SAR Imagery
Although deep learning techniques have achieved noticeable success in aircraft detection,
the scale heterogeneity, position difference, complex background interference, and speckle …
the scale heterogeneity, position difference, complex background interference, and speckle …
Tiny object tracking: A large-scale dataset and a baseline
Tiny objects, frequently appearing in practical applications, have weak appearance and
features, and receive increasing interests in many vision tasks, such as object detection and …
features, and receive increasing interests in many vision tasks, such as object detection and …
RLDS: An explainable residual learning diagnosis system for fetal congenital heart disease
Fetal congenital heart disease (CHD) is a prevalent and highly complicated fetal deformity.
Furthermore, the number of infants with CHD accounts for as high as 6‰–8‰ among all the …
Furthermore, the number of infants with CHD accounts for as high as 6‰–8‰ among all the …