Results 11 to 20 of about 11,603,043 (210)

A Novel 2D-3D CNN with Spectral-Spatial Multi-Scale Feature Fusion for Hyperspectral Image Classification

Remote Sensing, 2021
Multifarious hyperspectral image (HSI) classification methods based on convolutional neural networks (CNN) have been gradually proposed and achieve a promising classification performance.
Dongxu Liu, Guangliang Han, Peixun Liu, Hang Yang, Xinglong Sun, Qingqing Li, Jiajia Wu   +6 more
doaj   +3 more sources

Image Deraining Algorithm Based on Multi-Scale Features

Applied Sciences
In target detection, tracking, and recognition tasks, high-quality images can achieve better results. However, in actual scenarios, the visual effects and data quality of images are greatly reduced due to the influence of environmental factors, which ...
Jingkai Yang, Jingyuan Wang, Yanbo Li, Bobin Yao, Tangwen Xu, Ting Lu, Xiaoxuan Gao, Junshuo Chen, Weiyu Liu   +8 more
doaj   +2 more sources

Hyperspectral Image Classification Based on Multi-Scale Convolutional Features and Multi-Attention Mechanisms

Remote Sensing
Convolutional neural network (CNN)-based and Transformer-based methods for hyperspectral image (HSI) classification have rapidly advanced due to their unique characterization capabilities. However, the fixed kernel sizes in convolutional layers limit the
Qian Sun, Guangrui Zhao, Xinyuan Xia, Yu Xie, Chenrong Fang, Le Sun, Zebin Wu, Chengsheng Pan   +7 more
doaj   +2 more sources

Stereo Matching Method Based on Multi-Scale and Multi-Level Features Fusion [PDF]

Jisuanji gongcheng, 2021
The stereo matching method based on Convolutional Neural Network(CNN) does not make full use of the feature map information of each level in the image,resulting in the poor feature extraction performance in the ill posed region in the image.This paper ...
WANG Jinhe, CHE Zhilong, ZHANG Nan, MENG Fanyun, SU Cuili, TAN Hao
doaj   +1 more source

Optical Fiber Vibration Signal Recognition Based on the Fusion of Multi–Scale Features

Sensors, 2022
Because of the problem of low recognition accuracy in the recognition of intrusion vibration events by the distributed Sagnac type optical fiber sensing system, this paper combines the traditional optical fiber vibration signal recognition idea and the ...
Xinrong Ma, Jiaqing Mo, Jiangwei Zhang, Jincheng Huang   +3 more
doaj   +1 more source

Automatic Essay Scoring Method Based on Multi-Scale Features

Applied Sciences, 2023
Essays are a pivotal component of conventional exams; accurately, efficiently, and effectively grading them is a significant challenge for educators. Automated essay scoring (AES) is a complex task that utilizes computer technology to assist teachers in ...
Feng Li, Xuefeng Xi, Zhiming Cui, Dongyang Li, Wanting Zeng   +4 more
doaj   +1 more source

MSPR-Net: A Multi-Scale Features Based Point Cloud Registration Network

Remote Sensing, 2022
Point-cloud registration is a fundamental task in computer vision. However, most point clouds are partially overlapping, corrupted by noise and comprised of indistinguishable surfaces, especially for complexly distributed outdoor LiDAR point clouds ...
Jinjin Yu, Fenghao Zhang, Zhi Chen, Liman Liu   +3 more
doaj   +1 more source

Effective Point Cloud Analysis Using Multi-Scale Features

Sensors, 2021
Fully exploring the correlation of local features and their spatial distribution in point clouds is essential for feature modeling. This paper, inspired by convolutional neural networks (CNNs), explores the relationship between local patterns and point ...
Qiang Zheng, Jian Sun
doaj   +1 more source

Automatic analysis framework based on 3D-CT multi-scale features for accurate prediction of Ki67 expression levels in substantial renal cell carcinoma

Insights into Imaging, 2023
Purpose To investigate the effectiveness of an automatic analysis framework based on 3D-CT multi-scale features in predicting Ki67 expression levels in substantial renal cell carcinoma (RCC).
Huancheng Yang, Jiashan Lin, Hanlin Liu, Jiehua Yao, Qianyu Lin, Jiaxin Wang, Feiye Jiang, Liying Wei, Chongyang Lin, Kai Wu, Song Wu   +10 more
doaj   +1 more source

A Few Shot Classification Methods Based on Multiscale Relational Networks

Applied Sciences, 2022
Learning information from a single or a few samples is called few-shot learning. This learning method will solve deep learning’s dependence on a large sample. Deep learning achieves few-shot learning through meta-learning: “how to learn by using previous
Wenfeng Zheng, Xia Tian, Bo Yang, Shan Liu, Yueming Ding, Jiawei Tian, Lirong Yin   +6 more
doaj   +1 more source