Titlebook: Artificial Intelligence and Robotics; 7th International Sy Shuo Yang,Huimin Lu Conference proceedings 2022 The Editor(s) (if applicable) an

Glucocorticoids

Information Acquisition and Feature Extraction of Motor Imagery EEG,de range of application scenarios. Through the BCI technology based on electroencephalography (EEG) signal, the communication and control of external devices can be realized independently of the peripheral nervous system and muscle tissue. Motor imagery (MI) is a process in which people imagine thei

gerontocracy

Lightweight 3D Point Cloud Classification Network,search focuses on aggregating network features through pooling layers and extracting abstract features of 3D point clouds using higher dimensions. In this work, we turn our attention to exploring the relationships between points at a deeper level, using a multilayer perceptron module with a residual

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Unsupervised Domain Adaptive Image Semantic Segmentation Based on Convolutional Fine-Grained Discrirences, even modern networks cannot segment test datasets from different domains very well. To reduce and avoid costly annotation of the source domain training data, unsupervised domain adaptation attempts to provide efficient information transfer from the source domain with detailed annotation to t

走調(diào)

Ensemble of Classification and Matching Models with Alpha-Refine for UAV Tracking, the online updating tracker. However, few efforts were spent on drone-based object tracking because of its complexity. In this paper, a novelty ensemble of classification and matching model with alpha-refine (ECMMAR) method is proposed for drone-based object tracking. ECMMAR integrates two differen

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率直

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innate

Geometry-Aware Network for Table Structure Recognition in Wild,ture recognition have been widely discussed in recent years. The recognition of table structure in clean and noiseless images or documents has achieved good results, but in the real world with distorted images containing noise disturbance, the existing methods cannot get good results. The reason for

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Indebted

A Semi-supervised Road Segmentation Method for Remote Sensing Image Based on SegFormer,or remote sensing images is proposed. Firstly, an unsupervised network is designed to generate pseudo-labels of road images. In this module, a super-pixel segmentation method is used to pre-segment roads in remote sensing images, and then a lightweight convolutional neural network is used to extract