Test Whats new message.
Scheduled Maintenance on Monday 1/13/2025
Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.
BrowseConferences >2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)
2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)
Volume 1 • June-2020
Showing 1-25 of 536
Select a Month
Sort By
Design and implementation of Bootloader base on CAN bus
Publication Year: 2020,Page(s):43 - 46
Cited by: Papers (4)
Bootloader function is one of the essential function of embedded system. In this paper, a bootloader is designed based on the 16-bit Freescale MCU MC9S12XEP100 and CAN bus, which includes driver module design, diagnostic module design, BOOT method design, memory module design, and Flash protected design. Through the experiment, the results show that bootloader designed could boot the application a...Show More
Vehicle detection based on remote sensing image of Yolov3
Publication Year: 2020,Page(s):468 - 472
Cited by: Papers (9)
The recognition and classification of remote sensing satellite images have unique value and significance in many fields. Based on the yolov3 deep learning neural network, this paper first adjusts the network model to make it suitable for small target detection on remote sensing images, then uses k-means algorithm to calculate the grid size of Yolo network model suitable for vehicles, and then uses...Show More
Recognition Method for Engine Intake Gas Micelle State Based on Computed Tomography Image
Publication Year: 2020,Page(s):473 - 477
In order to measure the density, shape and spatial distribution of engine intake gas micelles in real time, dynamic and non-destructive manner, this paper studies a recognition method for engine intake gas micelle state based on computed tomography image (CT image). First, the engine cross-section CT image is collected through the X-ray layer imaging system. Secondly, by extracting the cylinder ci...Show More
Clustering Algorithm in Wireless Sensor Networks Based on Differential Evolution Algorithm
Publication Year: 2020,Page(s):478 - 482
Cited by: Papers (10)
Wireless sensor network (WSN) is a kind of self-organized distributed network composed of a large number of sensor nodes and one base station. The existing clustering model of wireless sensor network has the problems of uneven node energy consumption and high energy cost. In this paper, we build the model of cluster head selection, clustering and path planning based on Differential Evolution Algor...Show More
Research on adaptive cruise following control strategy based on model prediction
Publication Year: 2020,Page(s):483 - 487
In this paper, an adaptive cruise following strategy is designed based on the model prediction, and an appropriate inter-distance strategy is designed. By taking three indicators of traceability, comfort and safety as the quantitative indicators of ACC performance, a comprehensive performance indicator function is established based on inter-distance strategy so as to obtain the desired acceleratio...Show More
A Pneumonia Detection Method Based on Improved Convolutional Neural Network
Publication Year: 2020,Page(s):488 - 493
Cited by: Papers (8)
For traditional machine learning and image processing, it is difficult to extract features, the quality of feature extraction will directly affect the classification accuracy, another problem is that the large difference between the original datasets and the target datasets in the transfer learning, lead to unsatisfactory results. In addition, the original convolution model network is too shallow,...Show More
Research on an Automatic Conversion Method of Power Flow Input Data from PSD-BPA to Pandapower
Publication Year: 2020,Page(s):494 - 498
Cited by: Papers (2)
With the popularity of Python and its wide application in the scientific computing field, Pandapower, which is an open source power system analysis tool based on Python, is also recognized and appreciated. It is perfect for research and education which based on power flow calculation since it has advantages of easy programming, convenient operation, accurate calculation and intuitive result. Never...Show More
Transmission Line Image Object Detection Method Considering Fine-Grained Contexts
Neng Wan;Xuming Tang;Siyan Liu;Jiangqi Chen;Kegui Guo;Luyao Li;Shuai Liu
Publication Year: 2020,Page(s):499 - 502
Cited by: Papers (5)
It takes a huge amount of works to take pictures of transmission line towers and check electrical fittings manually. In spite of the introduction of deep learning technology to transmission line inspection, it is not well utilized that fine-grained contexts on components in state-of-the-art research. On the basis of region-based fully convolutional network (R-FCN), a novel object detection method ...Show More
Research on the Energy Management Strategy of Range Extended Fuel Cell Electric Vehicle
Xiangfei Meng;Dong Hao;Renguang Wang;Yuanli Xu;Zengna Wei;Lei Zhang
Publication Year: 2020,Page(s):503 - 507
Cited by: Papers (3)
Aiming at the influence of too low SOC of battery and fuel cell power change on the life of energy source system, a kind of multi-mode energy management control strategy was designed based on an extended-range fuel cell vehicle equipped with a fuel cell-battery power system. The strategy can control the vehicle to switch automatically between power following and multi-point thermostat control meth...Show More
Study on Electro-mechanical Combined Braking Control Strategy for 4WD Electric Vehicle with Two Motors
Publication Year: 2020,Page(s):508 - 512
In the braking process of double-motor electric vehicle, Both front and rear axles can both output regenerative braking force to recover braking energy, In order to study the influence of the ratio of braking force distribution between front and rear axes on the braking energy recovery, In this paper, three different braking force distribution schemes are designed on the premise of ensuring the br...Show More
Research on Extended Image Data Set Based on Deep Convolution Generative Adversarial Network
Publication Year: 2020,Page(s):47 - 50
Cited by: Papers (5)
The Deep Convolution Generative Adversarial Network (DCGAN) adds the structure of Generative Adversarial Network (GAN) on the basis of the generation countermeasure network, and specially generates image samples. In this paper, DCGAN is used to generate the image which does not belong to MNIST data set, and then, a new data set is obtained. Finally, Convolutional Neural Networks (CNN) [1] is used ...Show More
Topology Identification of Uncertain General Dynamical Network with Distributed Time Delays
Publication Year: 2020,Page(s):513 - 519
There are much uncertain information in a complex dynamical network, such as uncertain topological structure and node dynamics. Based on the Lyapunov function method and stability theory of differential equation, the impulsive controlling method and the bidirectional coupling method are proposed to identify the topological structure and systems parameters of the complex network model with distribu...Show More
Measurement Linearity and Accuracy Optimization for Time-of-Flight Range Imaging Cameras
Publication Year: 2020,Page(s):520 - 524
Cited by: Papers (1)
Time-of-flight (TOF) range imaging is a new method for 3d measurement and modeling in many scenarios. The time-of-flight imaging system using amplitude modulated continuous wave (AMCW) technology often suffers from measurement non-linearity because of aliasing harmonics, and temperature changes. It is required to correct these errors by using calibration. We demonstrate a correction method based o...Show More
Optimized BP neural network algorithm for predicting ship trajectory
Publication Year: 2020,Page(s):525 - 532
Cited by: Papers (8)
Ship navigation trajectory prediction is very important for ship transportation service. Therefore, a BP neural network based on ship's AIS data is proposed to predict ship trajectory. Aiming at the random characteristics of BP neural network initial weight threshold and the characteristics of easy to fall into local minimum, GA (Genetic Algorithm), PSO (Partical Swarm Optimization), ACO (Ant Colo...Show More
Application of Kalman Fixed Interval Smoothing in Trajectory Correction
Publication Year: 2020,Page(s):533 - 537
A Kalman fixed interval trajectory smoothing algorithm is established combining with the particle trajectory model, which is used to find a way to resolve the contradictions of one-dimensional modified projectile path correction while the flight trajectory of ammunition needs to be accurately estimated. This algorithm can effectively solve the problem of accurately extracting trajectory landing po...Show More
Influencing factors on excitation signal of torsional mode magnetostrictive guided wave
Wenwu Deng;Shengrong Long;Zhinong Li;Jingyi Ren;Yongyue Huang;Lin Gu;Xuanyu Chen
Publication Year: 2020,Page(s):538 - 541
This paper constructed the experimental platform for the testing of torsional mode magnetostrictive guided wave, based on the propagation mechanism of torsional guided wave, and studied the effects on testing signal of torsional mode guided wave under different intensity, frequency and periodic numbers of exciting current. According to the specific object, it shows that the higher signal amplitude...Show More
Images are the basis of human vision and an important way for humans to communicate with the world. Making computers with efficient and accurate image recognition is an important technical field of artificial intelligence. In recent years, image recognition technology has developed rapidly, and many new recognition technologies have emerged. This article first outlines the development process of i...Show More
Activation function is an integral part of convolutional neural networks. Through many experiments we find that there are some complementary properties between Relu activation function and Tanh activation function. The output of Tanh function could increase the values activated by Relu units and decrease the values clipped by Relu units. By changing Relu activation function into the weighted sum o...Show More
Thyroid Nodule Ultrasonic Imaging Segmentation Based on a Deep Learning Model and Data Augmentation
Publication Year: 2020,Page(s):549 - 554
Cited by: Papers (5)
The segmentation of thyroid nodule ultrasonic image is a critical step for thyroid disease diagnosis. With the advent of medical big data, deep convolutional neural networks (DCNNs) have contributed to the analysis of medical image. However, there is still room for improving the accuracy of the result. In this paper, we employ several data pre-processing algorithms to amplify the feature of the or...Show More
Radar Emitter Identification Based on Feedforward Neural Networks
Publication Year: 2020,Page(s):555 - 558
Cited by: Papers (7)
The aim of the article is implement radar emitter Identification. This paper applies neural network classifier in identification, and proposes a approach based on combination of multiple classifiers to improve the training efficiency. In the study, feedforward neural networks are utilized for identifying radar radiation sources, and the parameters of radar signals (direction of arrival, pulse widt...Show More
A Review of Methods for Detecting Point Anomalies on Numerical Dataset
Publication Year: 2020,Page(s):559 - 565
Cited by: Papers (8)
Due to the fast development of anomaly detection techniques and its widely application fields, we attempt to provide a clear structure about the newly methods for detecting point anomaly in relative low dimensional numerical datasets. Firstly, we have reviewed recent advancements in three aspects including classification-based anomaly detection techniques, nearest-neighbor-based anomaly detection ...Show More
Fault Tolerance Research of Visual Convolutional Neural Networks Based on Soft Errors
Publication Year: 2020,Page(s):566 - 570
Cited by: Papers (2)
Injecting faults to the system architecture layer and studying the upper neural network for fault tolerancehe is difficult and time-consuming. This paper proposes an automatic method covering time and space, which can inject faults into the processor on the Simics simulation platform, simulating soft errors, and then collect the time sequence data of the system architecture layer and the observed ...Show More
Detection method of phishing email based on persuasion principle
Publication Year: 2020,Page(s):571 - 574
Cited by: Papers (12)
“Phishing emails” are phishing emails with illegal links that direct users to pages of some real websites that are spoofed, or pages where real HTML has been inserted with dangerous HTML code, so as to deceive users' private information such as bank or credit card account numbers, email account numbers, and passwords. People are the most vulnerable part of security. Phishing emails use human weakn...Show More
A Cluster Autoscaler Based on Multiple Node Types in Kubernetes
Publication Year: 2020,Page(s):575 - 579
Cited by: Papers (8)
Kubernetes, as a production-grade container orchestration system, has been used in varieties of fields on a large scale. However, as used more and more widely, the appropriate selection of auto scaling schemes in kubernetes also faces considerable challenges in their respective application fields. Based on multiple node types with image pre-loaded, this paper proposes an improved automatic scaling...Show More
An Automatic Blind Image Deblurring Method via Label Confidence
Publication Year: 2020,Page(s):56 - 61
Image deblurring has been an active research topic in the computer vision and image processing. Generally, the existing deep learning methods can get high quality deblurred image while the quality depends on the variety of training dataset for blurred images. On the other side, the blur kernel estimation methods can work well on wider range images without training dataset for blurred images while ...Show More
IEEE Account
Purchase Details
Profile Information
Need Help?
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Contact Us
- Help
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Sitemap
- Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.