scholarly journals HYBRID REAL TIME PREDICTION OF STORM SURGES CAUSED BY TYPHOON WHICH USES NEURAL NETWORK METHOD AND NUMERICAL MODEL

2007 ◽  
Vol 51 ◽  
pp. 793-798
Author(s):  
Seiji AMOU ◽  
Susumu NAKANO ◽  
Takeshi KIMURA ◽  
Shigeru TSUGAWA
Keyword(s):  
Neural Network ◽  
Numerical Model ◽  
Real Time ◽  
Storm Surges ◽  
Neural Network Method ◽  
Time Prediction ◽  
Network Method

Real-time Tissue Thermometry Using an Acoustic Neural Network Method during HIFU Treatment

2010 ◽  
Author(s):  
Liexiang Fan ◽  
K. Michael Sekins ◽  
Kullervo Hynynen ◽  
Jacques Souquet
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Hifu Treatment ◽  
Neural Network Method ◽  
Network Method

scholarly journals Comparison Of Cellular Video Quality For Object Detection Using Neural Network Convolution

SinkrOn ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 260 ◽  
Author(s):  
Kevin Kevin ◽  
Nico Gunawan ◽  
Mariana Erfan Kristiani Zagoto ◽  
Laurentius Laurentius ◽  
Amir Mahmud Husein
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Real Time ◽  
Video Quality ◽  
Vehicle Detection ◽  
Neural Network Method ◽  
Network Method ◽  
Object Of Study ◽  
Capture Capacity ◽  
Detection And Recognition

Abstract— The purpose of this study is to compare the video quality between the Samsung HP camera and the Xiaomi HP camera. The object of study was UNPRI students who walked through the front yard of the UNPRI SEKIP campus. Here we test how accurate the camera's HP capture capacity is used to take the video. The method used to test this research is the Convolution Neural Network method. Object detection and recognition aim to detect and classify objects that can be applied to various fields such as face, human, pedestrian, vehicle detection (Pedoeem & Huang, 2018), besides the ability to find, identify, track and stabilize objects in various poses and important backgrounds in many real-time video applications. Object detection, tracking, alignment and stabilization have become very interesting fields of research in the vision and recognition of computer patterns due to the challenging nature of several slightly different objects such as object detection, where the algorithm must be precise enough to identify, track and center an object from the others

Real Time Prediction Method of Sensor Output Time Series

2014 ◽  
Vol 912-914 ◽  
pp. 1322-1326
Author(s):  
Zhi Cheng Liu
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Real Time ◽  
Simulation Experiment ◽  
Prediction Method ◽  
Sensor Output ◽  
Wavelet Filtering ◽  
Time Prediction ◽  
Network Method ◽  
Output Time

In order to improve the real time prediction precision of sensor output time series, the predictable inner mechanism of time series is analyzed, and a method using wavelet filtering and neural network is proposed. Sensor output time series are first handled with wavelet filtering, and then predicted by neural network method. The proposed method can eliminate effect of measurement noise on prediction precision. Simulation experiment shows a higher prediction precision by the method. A new idea is given to increase prediction precision of sensor output time series by neural network-based methods.

Methods for evaluation the manufacturability of a vehicle

2020 ◽  
pp. 152-160
Keyword(s):  
Neural Network ◽  
Initial Data ◽  
Comparative Data ◽  
Training Algorithm ◽  
Neural Network Method ◽  
The Neural Network ◽  
Network Method ◽  
Calculation Results ◽  
Production And Operation

Methods for evaluation the manufacturability of a vehicle in the field of production and operation based on an energy indicator, expert estimates and usage of a neural network are stated. By using the neural network method the manufacturability of a car in a complex and for individual units is considered. The preparation of the initial data at usage a neural network for predicting the manufacturability of a vehicle is shown; the training algorithm and the architecture for calculating the manufacturability of the main units are given. According to the calculation results, comparative data on the manufacturability vehicles of various brands are given.

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