Soft Computing, Machine Learning and Computational Intelligence for Laser Based Sensing and Measurement
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".
Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 16088
Special Issue Editors
Interests: hyperspectral image analysis; computational intelligence; medical imaging
Special Issues, Collections and Topics in MDPI journals
Interests: LiDAR data processing; image processing; control for autonomous vehicles; computational intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: geostatistical methods; LiDAR data processing; remote sensing
Interests: hyperspectral image analysis; computational intelligence; LiDAR data processing; soft computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Laser-based sensing and measurement is increasingly used in the industry and many other productive fields, like transportation and surveillance. Computer vision technologies that employ laser in some form or another are widely used in industrial inspection and quality control processes. On the other hand, LiDAR technology has been used for remote sensing with applications in agriculture, forestry and public land management. LiDAR technology also has a prominent role in the emerging transportation systems based on autonomous vehicles in situations that range from personal transportation to industrial vehicle guidance. Finally, safe LiDAR systems may increasingly be used for surveillance and crowd monitoring in public places because of their intrinsic respect for personal data. Laser-based measurements also have a prominent role in the field of flexible manufacturing and additive manufacturing. The goal of this Special Issue is to gather researchers working on the application of innovative computational methods such as deep learning to laser-generated measurement data for various purposes.
Topics
The methods and tools applied to vision and robotics include, but are not limited to, the following:
- Computational intelligence methods;
- Machine learning and deep learning methods;
- Self-adaptation and self-organisation;
- Point cloud registration methods;
- Multimodal information fusion;
- Hardware implementation and algorithms acceleration (GPUs, FPGA,s, etc.).
The fields of application include, but are not limited to, the following:
- 3D scene reconstruction;
- 3D volume visualization;
- Gesture and posture analysis and recognition;
- Surveillance systems in public areas;
- Autonomous and social robots;
- Industry 4.0: inspection and quality control;
- Transportation systems: autonomous navigation and road inventory;
- Remote sensing: forestry, agriculture, land management.
Prof. Manuel Graña
Prof. Jose Manuel Lopez-Guede
Dr. Anna Kamińska-Chuchmała
Dr. Paweł Ksieniewicz
Guest Editors
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