中文版 | English

在结果中检索

OPT OpenIR

浏览/检索结果: 共5条，第1-5条 帮助

限定条件        
已选(0)清除 条数/页：   排序方式：
Alzheimer's level classification by 3D PMNet using PET/MRI multi-modal images 会议论文
2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022, Changchun, China, 2022-02-25
作者:  Li, Chao;  Song, Liyao;  Zhu, Guangpu;  Hu, Bingliang;  Liu, Xuebin;  Wang, Quan
Adobe PDF(878Kb)  |  收藏  |  浏览/下载：129/0  |  提交时间：2022/05/11
Alzheimer's disease  3D CNN  Multi-modality  Image classification  PET/MRI  
DNN-Assisted activity classification using fiber interferometer sensor 会议论文
Optoelectronic Devices and Integration X, Nantong, China, 2021-10-10
作者:  Zhu, Guohao;  Xu, Wei;  Yu, Cheung Chuen;  Sun, Wenye;  Dong, Bo;  Yu, Changyuan;  Zhao, Wei;  Wang, Yishan
Adobe PDF(650Kb)  |  收藏  |  浏览/下载：80/3  |  提交时间：2022/01/27
MZI  Activity Monitoring  DNN  CNN  LSTM  FNN  
Pneumonia image classification based on convolutional neural network 会议论文
Twelfth International Conference on Information Optics and Photonics, CIOP 2021, Xi'an, China, 2021-07-23
作者:  Xiong, Feng;  He, Di;  Liu, Yujie;  Qi, Meijie;  Zhang, Zhoufeng;  Liu, Lixin
Adobe PDF(475Kb)  |  收藏  |  浏览/下载：95/0  |  提交时间：2022/01/21
image classification  convolution neural network (CNN)  deep learning (DL)  pneumonia image  chest X-ray  
Monocular depth estimation based on a single image: A literature review 会议论文
Twelfth International Conference on Graphics and Image Processing, ICGIP 2020, Xi'an, China, 2020-11-13
作者:  Tian, Yuan;  Hu, Xiaodong
Adobe PDF(487Kb)  |  收藏  |  浏览/下载：174/0  |  提交时间：2021/03/02
Depth estimation  depth cues  probabilistic graphical models  data-driven  CNN  
Learning to Predict Eye Fixations via Multiresolution Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 2, 页码: 392-404
作者:  Liu, Nian;  Han, Junwei;  Liu, Tianming;  Li, Xuelong
Adobe PDF(2296Kb)  |  收藏  |  浏览/下载：177/1  |  提交时间：2018/12/11
Contrast  Convolutional Neural Network (Cnn)  Eye Fixation Prediction  Rgb-d  Saliency Detection