Mobile crowdsensing (MCS) is a sensing paradigm that Hats allows ordinary citizens to use mobile and wearable technologies and become active observers of their surroundings.MCS services generate a massive amount of data due to the vast number of devices engaging in MCS tasks, and the intrinsic mobility of users can quickly make information obsolete
With the recent developments in computer vision, vision-based odometry plays an increasingly important role in the field of autonomous systems.However, using traditional visual odometry or simultaneous localization and mapping (vSLAM) only performs better in simple environments with Greens obvious structural features.Visual odometry may easily fail
Thermal errors account for more than 40% of the machining errors in CNC machine tools, and even reach 70% in precision and ultra-precision machine tools.One approach to reducing thermal errors is to build thermal error prediction models by monitoring the temperature field of machine tools with the data-driven modeling approaches.Usually the Tech da
Abstract In recent years, convolutional neural networks (CNNs) have made great achievements in the field of medical image segmentation, especially full convolutional neural networks based on U-shaped structures and skip connections.However, limited by the inherent limitations of convolution, CNNs-based methods usually exhibit limitations in modelin