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	Symmetric-threshold ReLU for Fast and Nearly Lossless ANN-SNN Conversion 期刊论文 OAI收割 Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 435-446 作者: Jianing Han \| 收藏 \| 浏览/下载：7/0 \| 提交时间：2023/05/29 Symmetric-threshold rectified linear unit (stReLU), deep spiking neural networks, artificial neural network-spiking neural network (ANN-SNN) conversion, lossless conversion, double thresholds
	Application of neural network and time series modeling to study the suitability of drain water quality for irrigation: a case study from Egypt 期刊论文 OAI收割 ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2020, 页码: 17 作者: Abdel-Fattah, Mohamed K.; Mokhtar, Ali; Abdo, Ahmed, I \| 收藏 \| 浏览/下载：11/0 \| 提交时间：2021/03/18 Water resources IWQI Artificial neural networks (ANN) ARIMA Time series Egypt
	Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China 期刊论文 OAI收割 REMOTE SENSING, 2017, 卷号: 9, 期号: 1, 页码: doi:10.3390/rs9010031 作者: Xia, Haoming; Zhao, Wei; Li, Ainong 收藏 \| 浏览/下载：47/0 \| 提交时间：2017/03/31 wetland subpixel inundation percentage (SIP) Landsat-8 unmanned aerial vehicle (UAV) linear spectral unmixing (LSU) regression tree (RT) artificial neural networks (ANN) Zoige Plateau
	Double inverted pendulum control based on three-loop PID and improved BP neural network (EI CONFERENCE) 会议论文 OAI收割 2011 2nd International Conference on Digital Manufacturing and Automation, ICDMA 2011, August 5, 2011 - August 7, 2011, Zhangjiajie, Hunan, China 作者: Fan Y. 收藏 \| 浏览/下载：28/0 \| 提交时间：2013/03/25 To deal with the defects of BP neural networks used in balance control of inverted pendulum such as longer train time and converging in partial minimum this article reaLizes the control of double inverted pendulum with improved BP algorithm of artificial neural networks(ANN) builds up a training model of test simulation and the BP network is 6-10-1 structure. Tansig function is used in hidden layer and PureLin function is used in output layer LM is used in training algorithm. The training data is acquried by three-loop PID algorithm. The model is learned and trained with Matlab calculating software and the simuLink simulation experiment results prove that improved BP algorithm for inverted pendulum control has higher precision better astringency and lower calculation. This algorithm has wide appLication on nonLinear control and robust control field in particular. 2011 IEEE.
	Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China Sun J.; Ma D. 收藏 \| 浏览/下载：17/0 \| 提交时间：2013/03/25 The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly we use frame grabber to capture the 4-bar target image data. Then according to image gray scale we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets along with known target visibility are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.