Results 1 to 10 of about 75,080 (277)
Frontal and non-frontal face detection using deep neural networks (DNN) [PDF]
International Journal of Research in Industrial Engineering, 2021 Face recognition has always been one of the most searched and popular applications of object detection, starting from the early seventies. Facial recognition is used for access control, authentication, fraud detection, surveillance, and by individuals to
N. Prasad +4 more
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Research Progress of Text Classification Technology Based on Deep Learning [PDF]
Jisuanji gongcheng, 2021 With the rapid development of deep learning technology,many researchers have tried to utilize deep learning to solve the text classification problems.Especially in terms of the Convolutional Neural Network(CNN) and Recurrent Neural Network(RNN),many ...
HE Li, ZHENG Zaoxian, XIANG Fengtao, WU Jianzhai, TAN Lin
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Sensors, 2022 With the improvement of industrial requirements for the quality of cold rolled strips, flatness has become one of the most important indicators for measuring the quality of cold rolled strips.
Jingyi Liu +5 more
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TiM-DNN: Ternary In-Memory Accelerator for Deep Neural Networks [PDF]
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2020 12 pages, 18 figures, Accepted in IEEE Transactions on Very Large Scale Integration (VLSI) Systems ...
Shubham Jain +2 more
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Deep Neural Network for DrawiNg Networks, (DNN)^2
, 2021 Appears in the Proceedings of the 29th International Symposium on Graph Drawing and Network Visualization (GD 2021)
Giovannangeli, Loann +4 more
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Classification Weighted Deep Neural Network Based Channel Equalization for Massive MIMO-OFDM Systems [PDF]
Radioengineering, 2022 Massive multi-input multi-output (MIMO) has attracted significant interest in academia and industry, which can efficiently increase the transmission rate.
L. Ge +5 more
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SecureAS: A Vulnerability Assessment System for Deep Neural Network Based on Adversarial Examples
IEEE Access, 2020 Deep neural network (DNN) has been recently applied to many safety-critical environments. Unfortunately, recent research has proven that DNN can be vulnerable to well-designed examples, called adversarial examples.
Yan Chu +3 more
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Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security. [PDF]
PLoS ONE, 2016 A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from ...
Min-Joo Kang, Je-Won Kang
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BREAST CANCER SEVERITY DEGREE PREDICATION USING DEEP LEARNING TECHNIQUES [PDF]
Jordanian Journal of Computers and Information Technology, 2020 Breast cancer is one of the most common types of cancer most often affecting women. It is a leading cause of cancer death in less developed countries. Thus, it is important to characterize the severity of the disease as soon as possible.
Alaa M. El halees, Mohammed H. Tafish
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A Wireless Positioning Method Based on Deep Neural Network [PDF]
Jisuanji gongcheng, 2016 To deal with the variant and unpredictable wireless signals,this paper proposes a regressive wireless positioning method based on Deep Neural Network(DNN).It uses a four-layer Deep Neural Network(DNN) structure pre-trained by Stacked Denoising ...
LIU Kan,ZHANG Wei,ZHANG Weidong,ZHANG Youmei,GU Jianjun
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