Image Format P&ID Recognition Technique Using Synthetic Data and Text-symbol Integrated Detection

2021 ◽  
Vol 26 (4) ◽  
pp. 355-365
Author(s):  
Wonyong Lee ◽  
Mijoo Kim ◽  
Duhwan Mun ◽  
Hyungki Kim
Keyword(s):  
Synthetic Data ◽  
Integrated Detection ◽  
Image Format ◽  
Recognition Technique

scholarly journals Towards Visible and Thermal Drone Monitoring with Convolutional Neural Networks

2019 ◽  
Vol 8 ◽  
Author(s):  
Ye Wang ◽  
Yueru Chen ◽  
Jongmoo Choi ◽  
C.-C. Jay Kuo
Keyword(s):  
Deep Learning ◽  
Data Augmentation ◽  
Tracking System ◽  
Synthetic Data ◽  
The Public ◽  
Detection And Tracking ◽  
Individual Module ◽  
Augmentation Techniques ◽  
Bounding Boxes ◽  
Integrated Detection

This paper reports a visible and thermal drone monitoring system that integrates deep-learning-based detection and tracking modules. The biggest challenge in adopting deep learning methods for drone detection is the paucity of training drone images especially thermal drone images. To address this issue, we develop two data augmentation techniques. One is a model-based drone augmentation technique that automatically generates visible drone images with a bounding box label on the drone's location. The other is exploiting an adversarial data augmentation methodology to create thermal drone images. To track a small flying drone, we utilize the residual information between consecutive image frames. Finally, we present an integrated detection and tracking system that outperforms the performance of each individual module containing detection or tracking only. The experiments show that, even being trained on synthetic data, the proposed system performs well on real-world drone images with complex background. The USC drone detection and tracking dataset with user labeled bounding boxes is available to the public.

An Approach for Speech Recognition Technique

2014 ◽  
Vol 1 (2) ◽  
pp. 7-15
Author(s):  
M. Suleman Basha ◽  
◽  
K. Rajendra Prasad ◽  
B. Rama Subbaiah ◽  
◽  
...  
Keyword(s):  
Speech Recognition ◽  
Recognition Technique

A Variant Group Assignment Three Dimensional Model Using Pattern Recognition Technique

2019 ◽  
Vol 10 (6) ◽  
pp. 1382-1394
Author(s):  
R. Vijayalakshmi ◽  
V. K. Soma Sekhar Srinivas ◽  
E. Manjoolatha ◽  
G. Rajeswari ◽  
M. Sundaramurthy
Keyword(s):  
Pattern Recognition ◽  
Three Dimensional ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
Pattern Recognition Technique ◽  
Group Assignment ◽  
Recognition Technique

Segmentasi Citra Mri Menggunakan Deteksi Tepi Untuk Identifikasi Kanker Payudara

2017 ◽  
Vol 15 (2) ◽  
pp. 17 ◽  
Author(s):  
Ervina Varijki ◽  
Bambang Krismono Triwijoyo
Keyword(s):  
Breast Cancer ◽  
Edge Detection ◽  
Object Segmentation ◽  
Computation Time ◽  
Input Image ◽  
Boundary Line ◽  
Cancer Breast ◽  
Average Computation Time ◽  
Breast Cancer Mri ◽  
Image Format

One type of cancer that is capable identified using MRI technology is breast cancer. Breast cancer is still the leading cause of death world. therefore early detection of this disease is needed. In identifying breast cancer, a doctor or radiologist analyzing the results of magnetic resonance image that is stored in the format of the Digital Imaging Communication In Medicine (DICOM). It takes skill and experience sufficient for diagnosis is appropriate, andaccurate, so it is necessary to create a digital image processing applications by utilizing the process of object segmentation and edge detection to assist the physician or radiologist in identifying breast cancer. MRI image segmentation using edge detection to identification of breast cancer using a method stages gryascale change the image format, then the binary image thresholding and edge detection process using the latest Robert operator. Of the20 tested the input image to produce images with the appearance of the boundary line of each region or object that is visible and there are no edges are cut off, with the average computation time less than one minute.

Layout Overlay Techniques to Improve Failure Analysis

1998 ◽  
Author(s):  
Christian Burmer ◽  
Siegfried Görlich ◽  
Siegfried Pauthner
Keyword(s):  
Failure Analysis ◽  
Focused Ion Beam ◽  
New Technologies ◽  
Ion Beam ◽  
Image Correlation ◽  
Microelectronic Devices ◽  
Overlay Technique ◽  
Correlation Techniques ◽  
Navigation Software ◽  
Image Format

Abstract New layout overlay technique has been developed based on standard image correlation techniques to support failure analysis in modern microelectronic devices, which are critical to analyze because they are realized in new technologies using sub-ìm design rules, chemical mechanical polishing techniques (CMP) and autorouted design techniques. As the new technique is realized as an extension of a standard CAD-navigation software and as it makes use of standard image format "TIFF" for data input, which is available at all modern equipments for failure analysis, these technique can be applied to all modern failure analysis methods. Here examples are given for three areas of application: circuit modification using Focused Ion Beam (FIB), support of preparation for backside inspection and fault localization using emission microscopy.

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

A Technique to Determine Unsteady-State Inhibition Kinetics in the Activated Sludge Process

1989 ◽  
Vol 21 (6-7) ◽  
pp. 593-602 ◽  
Author(s):  
Andrew T. Watkin ◽  
W. Wesley Eckenfelder
Keyword(s):  
Activated Sludge ◽  
Kinetic Parameters ◽  
Curve Fitting ◽  
Glucose Utilization ◽  
Batch Reactor ◽  
Synthetic Data ◽  
Utilization Rate ◽  
Fitting Algorithm ◽  
Test Reactor ◽  
Two Parameter

A technique for rapidly determining Monod and inhibition kinetic parameters in activated sludge is evaluated. The method studied is known as the fed-batch reactor technique and requires approximately three hours to complete. The technique allows for a gradual build-up of substrate in the test reactor by introducing the substrate at a feed rate greater than the maximum substrate utilization rate. Both inhibitory and non-inhibitory substrate responses are modeled using a nonlinear numerical curve-fitting technique. The responses of both glucose and 2,4-dichlorophenol (DCP) are studied using activated sludges with various acclimation histories. Statistically different inhibition constants, KI, for DCP inhibition of glucose utilization were found for the various sludges studied. The curve-fitting algorithm was verified in its ability to accurately retrieve two kinetic parameters from synthetic data generated by superimposing normally distributed random error onto the two parameter numerical solution generated by the algorithm.

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