A Motion Image Pose Contour Extraction Method Based on B-Spline Wavelet by null Chen chen, Daohui Bi

“…Moving images are acquired through the visual system, the information fusion process is used to perform statistical analysis on the images containing motion information, the location of the motion area is determined, convolutional neural network technology is used to preprocess the initial motion image pose contour, and B-spline wavelet theory is used. …”
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Content-aware image resizing based on random-carving with probability by Ying-chun GUO, Jun-teng HOU, Ming YU, Rui-li WANG

“…To improve the running speed of image resizing,a fast content-aware image resizing algorithm was proposed based on the threshold learning and random-carving with probability.Firstly the important map was calculated by combining the graph-based visual saliency map and gradient map.Then the image threshold value was obtained by radial basis function (RBF) neural network learning.And by the threshold,the original image was separated into the protected part and the unprotected part which was corresponding to the important part and the unimportant part of the original image individually.Finally,the two parts were allocated different resizing scales and the random-carving with probability was applied to them respectively.Experiments results show that the proposed algorithm has lower time cost comparing to the state-of-arts algorithms in MSRA image database,and has a better visual perception on image resizing.…”
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MULTI-OBJECTIVE OPTIMAL DESIGN OF ALUMINUM CELL by YANG EChuan, HUANG Lu, PANG Tong, ZHANG ZhenHua, YUAN TianXun

“…The orthogonal experiment was completed with full factor experimental design method,and the nine-lattice energy absorption box was determined as a follow-up research object,explore the effect of wall thickness on the crashworthiness of crash box,A neural network model was used to construct the proxy model,and the multi-objective optimization design was completed using the NSGA-II genetic algorithm. …”
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A Novel SHLNN Based Robust Control and Tracking Method for Hypersonic Vehicle under Parameter Uncertainty by Chuanfeng Li, Hao Wu, Zhile Yang, Yongji Wang, Zeyu Sun

“…In addition, a nonfragile guaranteed cost controller solved by LMI optimization approach is employed to the linear error system, where a single hidden layer neural network (SHLNN) is employed as an additive gain compensator to reduce excessive performance caused by perturbations and uncertainties. …”
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Res-DNN based signal detection algorithm for end-to-end MIMO systems by Guoquan LI, Yonghai XU, Jinzhao LIN, Zhengwen HUANG

“…Deep learning can improve the effect of signal detection by extracting the inherent characteristics of wireless communication data.To solve the tradeoff between the performance and complexity of MIMO system signal detection, an end-to-end MIMO system signal detection scheme based on deep learning was proposed.The encoder and the decoder based on residual deep neural network replace the transmitter and the receiver of the wireless communication system respectively, and they were trained in an end-to-end manner as a whole.Firstly, the features of the input data were extracted by encoder, then the communication model was established and was sent to the zero forcing detector for preliminary detection.Finally, the detection signal was reconstructed through the decoder.Simulation results show that the proposed detection scheme is superior to the same type of algorithm, and the detection performance is significantly better than that of the MMSE detection algorithm at the expense of a certain time complexity.…”
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Observer-Based Sliding Mode Control for Path Tracking of a Spherical Robot by Majid Taheri Andani, Zahra Ramezani, Saeed Moazami, Jinde Cao, Mohammad Mehdi Arefi, Hassan Zargarzadeh

“…Due to mechanical technicalities, it is assumed that these angles are immeasurable. First, a neural network observer is designed to estimate the pendulum angles. …”
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Shield Tunneling Parameter Matching Model and UI Interface by Gongyu Hou, Zhedong Xu, Le Li, Xiaoge Quan, Yajie Yang

“…The matching model based on BP neural network and PSO algorithm is compared in simulation experiments and engineering case. …”
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Two-stage Non-Intrusive Load Monitoring method for multi-state loads. by Lei Wang, Xia Han, Yushu Cheng, Jiaqi Ma, Xuerui Zhang, Xiaoqing Han

“…This paper proposed an improved NILM method based on the Resnet18 Convolutional Neural Network (CNN) and Support Vector Machine (SVM) algorithm to address the misidentification of multi-state appliances. …”
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Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG) by Qaswaa Khaled Abood

“…Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. …”
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Short-Term Power Prediction of Building Integrated Photovoltaic (BIPV) System Based on Machine Learning Algorithms by R. Kabilan, V. Chandran, J. Yogapriya, Alagar Karthick, Priyesh P. Gandhi, V. Mohanavel, Robbi Rahim, S. Manoharan

“…The results showed that the application of linear regression coefficients to the forecast outputs of the developed photovoltaic power generation neural network improved the PV power generation’s forecast output. …”
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RESEARCH ON EXPANSION METHOD OF TESTING DATA BASED ON PROBABILISTIC DISTRIBUTION FEATURES AND PROXY MODEL (MT) by YUAN FeiMeng, GENG HuaPin, WANG SiRui, SUO Bin, JIN Dong

“…The sample points were generated based on the back propagation（BP） neural network method to build a semi-physical simulation system proxy model, and were selected by the histogram statistical method. …”
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LIFE PREDICTION OF ROLLING BEARING BASED ON BIDIRECTIONAL STACKING SIMPLE RECURRENT UNIT by LI BoYang, YAO DeChen, LIU HengChang, YANG JianWei

“…Relying on the ability of recurrent neural network to process time series data,the SRU model is constructed,the traditional RNN serial operation structure is reconstructed,and the training efficiency is improved. …”
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Specifying High Altitude Electrons Using Low‐Altitude LEO Systems: Updates to the SHELLS Model by A. J. Boyd, J. C. Green, T. P. O’Brien, S. G. Claudepierre

“…The updated model combines the radial, angular and energy dependence into a single neural network, allowing for specification of the electron environment for a set of user input energy, L‐shell and Bmirror values. …”
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Scholarships Determination to Talented Students Based on Academic Characteristics with Deep Learning Approach and Particle Swarm Optimization Algorithm by Dorota Mozyrska, Ewa Pawluszewicz

“…Therefore, the present research tries to present such a system which is based on Natural Language Processing (NLP), feature extraction operations with Particle Swarm Optimization (PSO) algorithm and finally offers suggestions with deep Convolutional Neural Network (CNN). The results show that the accuracy of the proposed approach is higher than previous methods.…”
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Ripples Make Waves: Binding Structured Activity and Plasticity in Hippocampal Networks by Josef H. L. P. Sadowski, Matthew W. Jones, Jack R. Mellor

“…Each step is influenced by distinct neural network states that influence the pattern of activation across cellular assemblies. …”
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Deep learning for stage prediction in neuroblastoma using gene expression data by Aron Park, Seungyoon Nam

“…Taking the International Neuroblastoma Staging System stages as multiple classes, we designed a deep neural network using the gene expression patterns and stages of neuroblastoma patients. …”
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Heterogeneous Wireless Network Resource Management Algorithm Based on Reinforcement Learning by Chenwei Feng, Jiangnan Yuan

“…In order to make full use of the resources of all kinds of wireless network，the integration of heterogeneous network is necessary.However，when it comes to the heterogeneous network integration，the problems of call request access control and resource management emerge.A reinforcement-learning-based algorithm was presented for heterogeneous wireless network resource management.D2D （device-to-device）communication was introduced into the proposed algorithm and the appropriate network for access could be selected according to different traffic types，terminal mobility，network load status and so on.Meanwhile，to reduce the storage requirement，the neural network technology was used to solve the problem of continuous state space.Simulation results show that the proposed algorithm has an efficient learning ability to achieve autonomous radio resource management，which effectively improves the spectrum utility and reduces the blocking probability.…”
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A Machine Learning Approach to Optimize, Model, and Predict the Machining Factors in Dry Drilling of Nimonic C263 by S. Lakshmana Kumar, V. Jacintha, A. Mahendran, R. M. Bommi, M. Nagaraj, Umamahesawari Kandasamy

“…The feed forward neural network (FFNN) was used to develop a predictive model. …”
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Using object-oriented databases in face recognition by X. C. Dong, V. I. Ionin

“…Using a convolutional neural network in the algorithm allows the transition from specific features of the image to more abstract details.…”
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Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process by Mohsen Sarparast, Majid Shafaie, Mohammad Davoodi, Ahmad Memaran Babakan, Hongyan Zhang

“…The research explores the impact of Artificial Neural Network (ANN) architecture, specifically hidden layers and neurons, on predicting fracture parameters. …”
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