Remote sensing

Machine learning

Advances in Robotics and Automation: Anti-Degeneracy Scheme for Lidar SLAM

Research conducted at the Beijing University of Posts and Telecommunications has led to the development of an anti-degeneracy system for Lidar SLAM (Simultaneous Localization and Mapping) in geometry feature-less environments. The system utilizes a scale-invariant linear mapping, data augmentation based on a Gaussian model, and a degeneracy detection model to

Machine learning

Hybridization of Machine Learning and Remote Sensing Improves Wheat Yield and Quality Predictions

Scientists at the Julius Kuehn-Institute have successfully integrated machine learning and remote sensing techniques to enhance spatial predictions of wheat yield and quality. The study, published in the journal Computers and Electronics In Agriculture, aimed to improve wheat yield prediction by combining process-based models, machine learning, and remote sensing. The

Sensors

Breakthroughs in LiDAR Technology: Enhanced Earth and Space Exploration

Researchers at Brno University of Technology have shed new light on the capabilities and evolution of LiDAR technology, a crucial tool for earth observation and space exploration. According to a recent study, LiDAR instruments have demonstrated significant advancements in understanding environmental and atmospheric phenomena. The research team, led by Jan

Sensors

Breakthrough in Sensor Research: Novel Method for Remote Sensing Scene Classification

Researchers at Zhejiang College of Security Technology have made significant progress in sensor research, developing a novel method for remote sensing scene classification. The proposed approach, High-Frequency Enhanced Vision Transformer and Multi-Layer Learning (HETMCL), overcomes the limitations of existing methods by effectively learning the comprehensive features of high-frequency and low-frequency