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科研机构
西安交通大学 [21]
内容类型
会议论文 [18]
期刊论文 [3]
发表日期
2019 [1]
2018 [7]
2017 [4]
2016 [8]
2015 [1]
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专题:西安交通大学
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A Graph-Based Semisupervised Deep Learning Model for PolSAR Image Classification
期刊论文
IEEE Transactions on Geoscience and Remote Sensing, 2019, 卷号: 57, 页码: 2116-2132
作者:
Bi, Haixia
;
Sun, Jian
;
Xu, Zongben
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2019/11/19
Convolutional Neural Networks (CNN)
Graph model
Image edge detection
Polarimetric synthetic aperture radars
Prediction algorithms
Semi-supervised method
Task analysis
An Energy-Efficient and Flexible Accelerator based on Reconfigurable Computing for Multiple Deep Convolutional Neural Networks
会议论文
作者:
Yang, Chen
;
Zhang, HaiBo
;
Wang, XiaoLi
;
Geng, Li
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/11/19
CNN
Zero Detection Technology
Image Row Broadcast dataflow
Reconfigurable computing
Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification
会议论文
作者:
Wei, Xing
;
Zhang, Yue
;
Gong, Yihong
;
Zhang, Jiawei
;
Zheng, Nanning
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2019/11/19
Bilinear pooling
Burstiness
Convolutional Neural Networks (CNN)
Grassmann manifold
Second order statistics
Similarity measurements
State-of-the-art performance
Visual classification
Android Malware Detector Exploiting Convolutional Neural Network and Adaptive Classifier Selection
会议论文
作者:
Jin, Yangxu
;
Liu, Ting
;
He, Ancheng
;
Qu, Yu
;
Chi, Jianlei
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/11/19
Adaptive classifiers
Adaptive selection
Android malware
Convolutional neural network
Convolutional Neural Networks (CNN)
Empirical evaluations
Malware classifications
Single- machines
A Visual System of Citrus Picking Robot Using Convolutional Neural Networks
会议论文
作者:
Liu, Yan-Ping
;
Mabu, Shingo
;
Yang, Chang-Hui
;
Kuremoto, Takashi
;
Ling, Huang
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2019/11/26
citrus harvesting robot
YOLOv3
Mask R-CNN
deep learning
Spatial-temproal based lane detection using deep learning
会议论文
作者:
Huang, Yuhao
;
Chen, Shitao
;
Chen, Yu
;
Jian, Zhiqiang
;
Zheng, Nanning
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/11/26
Boundary detection method
Convolutional neural network
Convolutional Neural Networks (CNN)
Environment conditions
Lane detection
Perspective transforms
Spatial-temporal correlation
State-of-the-art methods
Improving CNN Performance Accuracies With Min-Max Objective
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 页码: 2872-2885
作者:
Shi, Weiwei
;
Gong, Yihong
;
Tao, Xiaoyu
;
Wang, Jinjun
;
Zheng, Nanning
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2019/11/26
image classification
Convolutional neural network (CNN)
incremental minibatch training procedure
face verification
min-max objective
Model Compression for Faster Structural Separation of Macromolecules Captured by Cellular Electron Cryo-Tomography
会议论文
作者:
Guo, Jialiang
;
Zhou, Bo
;
Zeng, Xiangrui
;
Freyberg, Zachary
;
Xu, Min
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2019/11/26
3D Visualization
Classification accuracy
Classification approach
Classification models
Computational costs
Convolutional Neural Networks (CNN)
Model compression
Structural separations
Vision-based Robotic Grasp Success Determination with Convolutional Neural Network
会议论文
作者:
Zhang, Hanbo
;
Lan, Xuguang
;
Zhou, Xinwen
;
Wang, Jianji
;
Zheng, Nanning
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2019/11/26
Convolutional neural network
Convolutional Neural Networks (CNN)
Deep convolutional neural networks
Generalization ability
Potential ability
RGB images
Robotic grasp
Spatial relationships
Boosting CNN-based pedestrian detection via 3d lidar fusion in autonomous driving
会议论文
作者:
Dou, Jian
;
Fang, Jianwu
;
Li, Tao
;
Xue, Jianru
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/11/26
Autonomous driving
Calibration method
Complex learning
Convolutional Neural Networks (CNN)
Large spaces
LIDAR sensors
Pedestrian detection
State of the art
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