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A convolutional feature map-based deep network targeted towards traffic detection and classification

机译：基于卷积特征的基于地图的深网络，针对交通检测和分类

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Baljit Kaur; Jhilik Bhattacharya;
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年度 2019
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1. A convolutional feature map-based deep network targeted towards traffic detection and classification [J] . Kaur Baljit, Bhattacharya Jhilik Expert Systems with Application . 2019,第JUNa期

机译：基于卷积特征图的深度网络，面向流量检测和分类
2. Network traffic classification using deep convolutional recurrent autoencoder neural networks for spatial-temporal features extraction [J] . DAngelo Gianni, Palmieri Francesco Journal of network and computer applications . 2021,第Jana期

机译：网络流量分类使用深卷积复制自动化器神经网络进行空间时间特征提取
3. An artificial target detection method combining a polarimetric feature extractor with deep convolutional neural networks [J] . Sun Rui, Sun Xiaobing, Chen Feinan, International journal of remote sensing . 2020,第13a14期

机译：具有深度卷积神经网络的偏振特征提取器的人工目标检测方法
4. Polsar Target Classification Using Polarimetric-Feature-Driven Deep Convolutional Neural Network [C] . Si-Wei Chen, Chen-Song Tao, Xue-Song Wang, IEEE International Geoscience and Remote Sensing Symposium . 2018

机译：使用极化特征驱动的深度卷积神经网络进行Polsar目标分类
5. Designing an Effective Model for Traffic Signs Classification Based on Deep Convolutional Neural Network [D] . Alam, Shariful. 2018

机译：基于深度卷积神经网络设计交通符号分类有效模型
6. Automatic Detection and Classification of Focal Liver Lesions Based on Deep Convolutional Neural Networks: A Preliminary Study [O] . Jiarong Zhou, Wenzhe Wang, Biwen Lei, 2020

机译：基于深度卷积神经网络的焦肝病变自动检测和分类：初步研究
7. Semi-Supervised Encrypted Traffic Classification With Deep Convolutional Generative Adversarial Networks [O] . Auwal Sani Iliyasu, Huifang Deng 2020

机译：具有深度卷积生成对抗网络的半监督加密流量分类
8. Keypoint Density-Based Region Proposal for Fine-Grained Object Detection and Classification Using Regions with Convolutional Neural Network Features. [R] . Turner, J. T., Gupta, K., Morris, B., 2015

机译：基于关键点密度的区域提议，用于使用具有卷积神经网络特征的区域进行细粒度目标检测和分类。

A convolutional feature map-based deep network targeted towards traffic detection and classification

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