RTFNet: RGB-thermal fusion network for semantic segmentation of urban scenes
Semantic segmentation is a fundamental capability for autonomous vehicles. With the
advancements of deep learning technologies, many effective semantic segmentation …
advancements of deep learning technologies, many effective semantic segmentation …
Perception and navigation in autonomous systems in the era of learning: A survey
Autonomous systems possess the features of inferring their own state, understanding their
surroundings, and performing autonomous navigation. With the applications of learning …
surroundings, and performing autonomous navigation. With the applications of learning …
CGFNet: cross-guided fusion network for RGB-thermal semantic segmentation
Y Fu, Q Chen, H Zhao - The Visual Computer, 2022 - Springer
Semantic segmentation is a basic task in computer vision, which is widely used in various
fields such as autonomous driving, detection, augmented reality and so on. Recent …
fields such as autonomous driving, detection, augmented reality and so on. Recent …
Predicting human microbe–drug associations via graph convolutional network with conditional random field
Motivation Human microbes play critical roles in drug development and precision medicine.
How to systematically understand the complex interaction mechanism between human …
How to systematically understand the complex interaction mechanism between human …
RGB-D semantic segmentation and label-oriented voxelgrid fusion for accurate 3D semantic mapping
The 3D semantic map plays an increasingly important role in a wide variety of applications,
especially for many kinds of task-driven robots. In this paper, we present a semantic …
especially for many kinds of task-driven robots. In this paper, we present a semantic …
High-resolution remote sensing image segmentation framework based on attention mechanism and adaptive weighting
Y Liu, Q Zhu, F Cao, J Chen, G Lu - ISPRS International Journal of Geo …, 2021 - mdpi.com
Semantic segmentation has been widely used in the basic task of extracting information from
images. Despite this progress, there are still two challenges:(1) it is difficult for a single-size …
images. Despite this progress, there are still two challenges:(1) it is difficult for a single-size …
PSPNet-SLAM: A semantic SLAM detect dynamic object by pyramid scene parsing network
X Long, W Zhang, B Zhao - IEEE access, 2020 - ieeexplore.ieee.org
Simultaneous Localization and Mapping (SLAM) plays an important role in the computer
vision and robotic field. The traditional SLAM framework adopts a strong static world …
vision and robotic field. The traditional SLAM framework adopts a strong static world …
Improving monocular visual SLAM in dynamic environments: an optical-flow-based approach
Visual Simultaneous Localization and Mapping (visual SLAM) has attracted more and more
researchers in recent decades and many state-of-the-art algorithms have been proposed …
researchers in recent decades and many state-of-the-art algorithms have been proposed …
Towards a meaningful 3D map using a 3D lidar and a camera
J Jeong, TS Yoon, JB Park - Sensors, 2018 - mdpi.com
Semantic 3D maps are required for various applications including robot navigation and
surveying, and their importance has significantly increased. Generally, existing studies on …
surveying, and their importance has significantly increased. Generally, existing studies on …