scholarly journals A FACE SPOOFING DETECTION SYSTEM USING SURF ANALYSIS BASED ON GENETIC ALGORITHM AND ARTIFICIAL INTELLIGENCE TECHNIQUE.

2020 ◽  
Vol 9 (9) ◽  
pp. 125-135
Keyword(s):  
Artificial Intelligence ◽  
High Performance ◽  
Detection System ◽  
Optimization Technique ◽  
User Cooperation ◽  
Artificial Intelligence Technique ◽  
Spoofing Detection ◽  
Feature Optimization ◽  
Face Spoofing ◽  
Intelligence Technique

Modern face biometric systems are susceptible to spoofing attacks and a secure face spoof detection system demands the capability to recognize whether a face is from a real person or a spoofed image that is created by an unauthenticated person. Inspired by the feature selection algorithm, characterization of printing artifacts, and differences in light reflection, we proposed to approach the problem of spoofing detection from a pattern analysis point of view. Indeed, face prints often contain printing quality faults that can be well detected using pattern features, the Speech up Robust Feature (SURF) descriptor. Hence, introduces a novel approach based on face pattern image analysis to find out if there is live in front of a camera or a printed face. The proposed approach analyzes the pattern and quality of the facial images using the SURF descriptor as a feature extraction algorithm. Compared to a lot of previous works, our proposed face spoofing detection approach is robust, computationally fast, and does not require user-cooperation. In addition, the feature optimization technique is used for the selection of a unique feature set from the ROI of face images. Convolutional Neural Network (CNN) classifier is used for the training of the proposed spoof detection system. It is seen that the designed hybrid system face spoof detection achieves high performance than the existing system and execution time is also well. The proposed method is assessed using the MATLAB simulator in computer vision and image processing toolbox. The experimental analysis on a publicly accessible database presented brilliant results compared to existing works by using the concept of feature optimization and artificial intelligence technique.

Towards a Customized¬ Awareness Campaign to Educate the Public about COVID-19: Development and Validation of a Messaging Campaign to Promote Precautionary Behavior Using Geospatial Intelligence in Saudi Arabia (Preprint)

2020 ◽  
Author(s):  
Mayda Alrige ◽  
Hind Bitar Bitar ◽  
Maram Meccawi ◽  
Balakrishnan Mullachery
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Content Validity ◽  
Awareness Campaign ◽  
Artificial Intelligence Technique ◽  
The Public ◽  
High Infection ◽  
Local Map ◽  
The City ◽  
Intelligence Technique

BACKGROUND Designing a health promotion campaign is never an easy task, especially during a pandemic of a highly infectious disease, such as Covid-19. In Saudi Arabia, many attempts have been made toward raising the public awareness about Covid-19 infection-level and its precautionary health measures that have to be taken. Although this is useful, most of the health information delivered through the national dashboard and the awareness campaign are very generic and not necessarily make the impact we like to see on individuals’ behavior. OBJECTIVE The objective of this study is to build and validate a customized awareness campaign to promote precautionary health behavior during the COVID-19 pandemic. The customization is realized by utilizing a geospatial artificial intelligence technique called Space-Time Cube (STC) technique. METHODS This research has been conducted in two sequential phases. In the first phase, an initial library of thirty-two messages was developed and validated to promote precautionary messages during the COVID-19 pandemic. This phase was guided by the Fogg Behavior Model (FBM) for behavior change. In phase 2, we applied STC as a Geospatial Artificial Intelligence technique to create a local map for one city representing three different profiles for the city districts. The model was built using COVID-19 clinical data. RESULTS Thirty-two messages were developed based on resources from the World Health Organization and the Ministry of Health in Saudi Arabia. The enumerated content validity of the messages was established through the utilization of Content Validity Index (CVI). Thirty-two messages were found to have acceptable content validity (I-CVI=.87). The geospatial intelligence technique that we used showed three profiles for the districts of Jeddah city: one for high infection, another for moderate infection, and the third for low infection. Combining the results from the first and second phases, a customized awareness campaign was created. This awareness campaign would be used to educate the public regarding the precautionary health behaviors that should be taken, and hence help in reducing the number of positive cases in the city of Jeddah. CONCLUSIONS This research delineates the two main phases to developing a health awareness messaging campaign. The messaging campaign, grounded in FBM, was customized by utilizing Geospatial Artificial Intelligence to create a local map with three district profiles: high-infection, moderate-infection, and low-infection. Locals of each district will be targeted by the campaign based on the level of infection in their district as well as other shared characteristics. Customizing health messages is very prominent in health communication research. This research provides a legitimate approach to customize health messages during the pandemic of COVID-19.

scholarly journals Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study

2020 ◽  
Author(s):  
Yuchen Luo ◽  
Yi Zhang ◽  
Ming Liu ◽  
Yihong Lai ◽  
Panpan Liu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
High Performance ◽  
Detection System ◽  
Random Order ◽  
Colon Polyps ◽  
Clinical Environment ◽  
Polyp Detection ◽  
Link Type ◽  
Polyp Detection Rate

Abstract Background and aims Improving the rate of polyp detection is an important measure to prevent colorectal cancer (CRC). Real-time automatic polyp detection systems, through deep learning methods, can learn and perform specific endoscopic tasks previously performed by endoscopists. The purpose of this study was to explore whether a high-performance, real-time automatic polyp detection system could improve the polyp detection rate (PDR) in the actual clinical environment. Methods The selected patients underwent same-day, back-to-back colonoscopies in a random order, with either traditional colonoscopy or artificial intelligence (AI)-assisted colonoscopy performed first by different experienced endoscopists (> 3000 colonoscopies). The primary outcome was the PDR. It was registered with clinicaltrials.gov. (NCT047126265). Results In this study, we randomized 150 patients. The AI system significantly increased the PDR (34.0% vs 38.7%, p < 0.001). In addition, AI-assisted colonoscopy increased the detection of polyps smaller than 6 mm (69 vs 91, p < 0.001), but no difference was found with regard to larger lesions. Conclusions A real-time automatic polyp detection system can increase the PDR, primarily for diminutive polyps. However, a larger sample size is still needed in the follow-up study to further verify this conclusion. Trial Registration clinicaltrials.gov Identifier: NCT047126265

Artificial intelligence technique for estimating PV modules performance ratio under outdoor operating conditions

2018 ◽  
Vol 10 (5) ◽  
pp. 053505 ◽  
Author(s):  
Alain K. Tossa ◽  
Y. M. Soro ◽  
Y. Coulibaly ◽  
Y. Azoumah ◽  
Anne Migan-Dubois ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Operating Conditions ◽  
Performance Ratio ◽  
Artificial Intelligence Technique ◽  
Pv Modules ◽  
Intelligence Technique

scholarly journals A Study on Preventing Food Wastage in India Using AI

2020 ◽  
pp. 378-425
Keyword(s):  
Artificial Intelligence ◽  
Technology Transfer ◽  
Resource Utilization ◽  
New Technology ◽  
Asian Country ◽  
Foreign Technology ◽  
Artificial Intelligence Technique ◽  
Developed Nations ◽  
Food Wastage ◽  
Intelligence Technique

Exponential Growth of Technology in Asian country has compete a major role altogether spherical development and growth of economy and social development in our country. Asian country has opted for a even handed mixture of autochthone and foreign technology. Purchase of technology is often referred to as “Technology transfer” and it's usually coated by a technology transfer agreement. This work focuses on the key areas of computer science and the way it implements within the future to forestall the waste matter. This write-up nearly identifies the crucial problems or issues related to food & cash wastage in food. In Asian country there square measure such a big amount of those that aren't obtaining correct food and in an exceedingly same time there square measure some folks with excess food and at the top it goes to the wastage half. Our main intention is distinguishing the issues and giving the mandatory recommendations for resolution the issues encountered. the event of any country is nearly depends on the advancement in developing the technology in numerous fields and cash management. Countries that participate across this age square measure developed additional far more rather more way more than alternative countries as a result of the machine occupies the work more from men. additional advancements in twentieth century in house, aircraft, computers, biotech and knowledge technology square measure boost the developed nations abundant advanced. The new technology with young minds creates an activity each in information and resource utilization. For waste matter calculation and bar we are going to use some powerful artificial intelligence technique, intelligence and technologies.

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