scholarly journals Design and Development of On-Board Earth Resources Detection System Based on FPGA and LabVIEW for Remote Sensing Application

10.29007/4q63 ◽  
2018 ◽  
Author(s):  
Alpesh Vala ◽  
Riddhi Goswami ◽  
Amit Patel ◽  
Keyur Mahant
Keyword(s):  
Detection System ◽  
System Development ◽  
Detection Algorithm ◽  
Memory Storage ◽  
Satellite Imaging ◽  
High Speeds ◽  
Ground System ◽  
Imaging Sensors ◽  
Mass Volume ◽  
Water Vegetation

This paper presents system development for the detection of earth resources such as a water, vegetation and land for the satellite application. Satellite imaging sensors generate mass volume of data at very high speeds. On the other hand, storage capacity and communication bandwidth are crucial parameters for satellite resources. Here we have proposed the system that can be used on board to extract relative information from the image and can send out the required (obtained) results to the ground system (Result of pixel information whether it contains water/vegetation/land). The system can be used for the saving of on board satellite resources such as memory storage, power and communication bandwidth. The detection of earth resources are based on their reflectance value. For the analysis of proposed detection algorithm LabVIEW based simulation has been carried out for the detection of Land, Water and vegetation from their reflectance value. Same algorithm has implemented in FPGA for the real time implementation using SPARTAN XC3S500e-4vq100 FPGA board. The results are accurate and matched with the simulation results performed in LabVIEW.

scholarly journals Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1081
Author(s):  
Tamon Miyake ◽  
Shintaro Yamamoto ◽  
Satoshi Hosono ◽  
Satoshi Funabashi ◽  
Zhengxue Cheng ◽  
...  
Keyword(s):  
Learning Algorithm ◽  
Detection System ◽  
Calibration Method ◽  
Detection Algorithm ◽  
Video Data ◽  
Detection Accuracy ◽  
Phase Detection ◽  
Gait Phase ◽  
Logistic Regression Algorithm ◽  
Short Time

Gait phase detection, which detects foot-contact and foot-off states during walking, is important for various applications, such as synchronous robotic assistance and health monitoring. Gait phase detection systems have been proposed with various wearable devices, sensing inertial, electromyography, or force myography information. In this paper, we present a novel gait phase detection system with static standing-based calibration using muscle deformation information. The gait phase detection algorithm can be calibrated within a short time using muscle deformation data by standing in several postures; it is not necessary to collect data while walking for calibration. A logistic regression algorithm is used as the machine learning algorithm, and the probability output is adjusted based on the angular velocity of the sensor. An experiment is performed with 10 subjects, and the detection accuracy of foot-contact and foot-off states is evaluated using video data for each subject. The median accuracy is approximately 90% during walking based on calibration for 60 s, which shows the feasibility of the static standing-based calibration method using muscle deformation information for foot-contact and foot-off state detection.

Structural Design of Intrusion Detection System

2014 ◽  
Vol 530-531 ◽  
pp. 705-708
Author(s):  
Yao Meng
Keyword(s):  
Intrusion Detection ◽  
Structural Design ◽  
Intrusion Detection System ◽  
Detection System ◽  
Algorithm Design ◽  
Detection Algorithm ◽  
Attack Detection ◽  
Detection Algorithms ◽  
Defense Systems ◽  
Ddos Attack Detection

This paper first engine starting defense from Intrusion Detection, Intrusion detection engine analyzes the hardware platform, the overall structure of the technology and the design of the overall structure of the plug, which on the whole structure from intrusion defense systems were designed; then described in detail improved DDOS attack detection algorithm design thesis, and the design of anomaly detection algorithms.

Search on Method of Netwok Intrusion Detection Based on Support Vector Machine with Pre-Extracting Support Vector

2013 ◽  
Vol 655-657 ◽  
pp. 1787-1790
Author(s):  
Sheng Chen Yu ◽  
Li Min Sun ◽  
Yang Xue ◽  
Hui Guo ◽  
Xiao Ju Wang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Detection Algorithm ◽  
Support Vector ◽  
Distance Ratio ◽  
Training Time ◽  
Training Examples ◽  
Center Distance

Intrusion detection algorithm based on support vector machine with pre-extracting support vector is proposed which combines the center distance ratio and classification algorithm. Given proper thresholds, we can use the support vector as a substitute for the training examples. Then the scale of dataset is decreased and the performance of support vector machine is improved in the detection rate and the training time. The experiment result has shown that the intrusion detection system(IDS) based on support vector machine with pre-extracting support needs less training time under the same detection performance condition.

scholarly journals Robust Real-Time Detection of Laparoscopic Instruments in Robot Surgery Using Convolutional Neural Networks with Motion Vector Prediction

2019 ◽  
Vol 9 (14) ◽  
pp. 2865 ◽  
Author(s):  
Kyungmin Jo ◽  
Yuna Choi ◽  
Jaesoon Choi ◽  
Jong Woo Chung
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Convolutional Neural Networks ◽  
Detection System ◽  
Motion Vector ◽  
Detection Algorithm ◽  
Surgical Instruments ◽  
The Mean ◽  
Real Time Detection ◽  
Motion Vector Prediction

More than half of post-operative complications can be prevented, and operation performances can be improved based on the feedback gathered from operations or notifications of the risks during operations in real time. However, existing surgical analysis methods are limited, because they involve time-consuming processes and subjective opinions. Therefore, the detection of surgical instruments is necessary for (a) conducting objective analyses, or (b) providing risk notifications associated with a surgical procedure in real time. We propose a new real-time detection algorithm for detection of surgical instruments using convolutional neural networks (CNNs). This algorithm is based on an object detection system YOLO9000 and ensures continuity of detection of the surgical tools in successive imaging frames based on motion vector prediction. This method exhibits a constant performance irrespective of a surgical instrument class, while the mean average precision (mAP) of all the tools is 84.7, with a speed of 38 frames per second (FPS).

Next-Generation NASA Hazard Detection System Development

2020 ◽  
Author(s):  
Carolina I. Restrepo ◽  
Po-Ting Chen ◽  
Ronald R. Sostaric ◽  
John M. Carson
Keyword(s):  
Detection System ◽  
System Development ◽  
Next Generation ◽  
Hazard Detection

Research on TV Goniometer Object Extraction Algorithm Based on Threshold Segmentation

2014 ◽  
Vol 889-890 ◽  
pp. 1093-1098
Author(s):  
He Chen ◽  
Nan Li ◽  
Tian Chen Huang ◽  
Rong Xia Duan
Keyword(s):  
Optimal Algorithm ◽  
Detection System ◽  
Detection Algorithm ◽  
Field Of View ◽  
Object Extraction ◽  
Gray Level ◽  
Line Extraction ◽  
Standard Signal ◽  
Extraction Algorithm ◽  
Target Extraction

In the TV goniometer detection system, to play the signal and field of view points line extraction is a key link in the process of parameter detection. Combination of target processing requirements, this article will target extraction algorithm based on gray level threshold and edge detection algorithm is studied, and through the experimental analysis to select the optimal algorithm was applied to the detection of TV goniometer; According to the characteristics of the standard signal and view points, lines, and put forward the corresponding methods of target recognition, and is verified through experiments

Sign in / Sign up

Export Citation Format

Share Document