中文版 | English

在结果中检索

OPT OpenIR

浏览/检索结果: 共29条，第1-10条 帮助

限定条件                    
已选(0)清除 条数/页：   排序方式：
Deep neural network: As the novel pipelines in multiple preprocessing for Raman spectroscopy 期刊论文
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2023, 卷号: 302
作者:  Gao, Chi;  Zhao, Peng;  Fan, Qi;  Jing, Haonan;  Dang, Ruochen;  Sun, Weifeng;  Feng, Yutao;  Hu, Bingliang;  Wang, Quan
Adobe PDF(2962Kb)  |  收藏  |  浏览/下载：70/0  |  提交时间：2023/09/25
Raman spectroscopy  Deep learning  Baseline correction  Spectroscopy denoising  
Improvement of the sediment flux estimation in the Yangtze River Estuary with a GOCI data adjusted numerical model 期刊论文
Ocean Modelling, 2023, 卷号: 186
作者:  Xie, Guohu;  Zhang, Yang;  Liu, Jia;  Xue, Huijie;  Ge, Jianzhong;  He, Xianqiang;  Ma, Wentao;  Chai, Fei
Adobe PDF(7878Kb)  |  收藏  |  浏览/下载：40/0  |  提交时间：2023/11/23
Sediment flux  Yangtze River Estuary  Geostationary Ocean Color Imager (GOCI)  Numerical model  Morphology  
Extraction and analysis algorithms for Sanxingdui cultural relics based on hyperspectral imaging 期刊论文
Computers and Electrical Engineering, 2023, 卷号: 111
作者:  Qiu, Shi;  Zhang, Pengchang;  Li, Siyuan;  Hu, Bingliang
Adobe PDF(8586Kb)  |  收藏  |  浏览/下载：42/0  |  提交时间：2023/10/30
Sanxingdui Ruins  Hyperspectral  Unet  FCM  
Multi-Prior Graph Autoencoder with Ranking-Based Band Selection for Hyperspectral Anomaly Detection 期刊论文
REMOTE SENSING, 2023, 卷号: 15, 期号: 18
作者:  Wang, Nan;  Shi, Yuetian;  Li, Haiwei;  Zhang, Geng;  Li, Siyuan;  Liu, Xuebin
Adobe PDF(4511Kb)  |  收藏  |  浏览/下载：51/0  |  提交时间：2023/10/27
hyperspectral anomaly detection  deep learning  band selection  autoencoder  
Temporal transformer-spatial graph convolutional network: an intelligent classification model for anti N-methyl-D-aspartate receptor encephalitis based on electroencephalogram signal 期刊论文
FRONTIERS MEDIA SA, 2023, 卷号: 17
作者:  Dang, Ruochen;  Yu, Tao;  Hu, Bingliang;  Wang, Yuqi;  Pan, Zhibin;  Luo, Rong;  Wang, Quan
Adobe PDF(1349Kb)  |  收藏  |  浏览/下载：56/0  |  提交时间：2023/10/10
anti NMDA receptor encephalitis  viral encephalitis  EEG  transformer  graph network  classification  
Spectral Calibration for SO2 Cameras with Light Dilution Effect Correction 期刊论文
REMOTE SENSING, 2023, 卷号: 15, 期号: 14
作者:  Wu, Kuijun;  Guo, Jianjun;  Zhang, Zihao;  Zhang, Huiliang;  Li, Juan;  Li, Faquan;  He, Weiwei
Adobe PDF(7046Kb)  |  收藏  |  浏览/下载：37/0  |  提交时间：2023/10/13
SO2 camera  calibration  light dilution  atmospheric scattering  emission rate  
Joint Diagnostic Method of Tumor Tissue Based on Hyperspectral Spectral-Spatial Transfer Features 期刊论文
DIAGNOSTICS, 2023, 卷号: 13, 期号: 12
作者:  Du, Jian;  Tao, Chenglong;  Xue, Shuang;  Zhang, Zhoufeng
Adobe PDF(83446Kb)  |  收藏  |  浏览/下载：33/0  |  提交时间：2023/07/17
hyperspectral imaging  spectral-spatial transfer feature  deep learning  tumor tissue  joint diagnosis  
Deep learning methods for medical image fusion: A review 期刊论文
COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 卷号: 160
作者:  Zhou, Tao;  Cheng, QianRu;  Lu, HuiLing;  Li, Qi;  Zhang, XiangXiang;  Qiu, Shi
Adobe PDF(4857Kb)  |  收藏  |  浏览/下载：78/0  |  提交时间：2023/06/12
Deep learning  Medical image fusion  Convolutional neural network  Generative adversarial network  Encoder -decoder network  
Performance Assessment of Four Data-Driven Machine Learning Models: A Case to Generate Sentinel-2 Albedo at 10 Meters 期刊论文
REMOTE SENSING, 2023, 卷号: 15, 期号: 10
作者:  Chen, Hao;  Lin, Xingwen;  Sun, Yibo;  Wen, Jianguang;  Wu, Xiaodan;  You, Dongqin;  Cheng, Juan;  Zhang, Zhenzhen;  Zhang, Zhaoyang;  Wu, Chaofan;  Zhang, Fei;  Yin, Kechen;  Jian, Huaxue;  Guan, Xinyu
Adobe PDF(13289Kb)  |  收藏  |  浏览/下载：43/0  |  提交时间：2023/07/03
Sentinel-2  albedo  data-driven machine learning algorithms  remote sensing  
Automatic Seizure Detection and Prediction Based on Brain Connectivity Features and a CNNsMeet Transformers Classifier 期刊论文
BRAIN SCIENCES, 2023, 卷号: 13, 期号: 5
作者:  Tian, Ziwei;  Hu, Bingliang;  Si, Yang;  Wang, Quan
Adobe PDF(3837Kb)  |  收藏  |  浏览/下载：41/0  |  提交时间：2023/07/05
epileptic state classification  EEG  brain connectivity  support vector machine  CNNs  meet transformers