This document presents a real-time facial analysis system using TensorFlow and OpenCV. The system can detect facial expressions, age, and gender from images and video in real-time. It uses deep learning models trained on facial datasets to analyze faces. The system is designed for applications like security, attendance tracking, and finding lost children. It works by extracting facial features from images, applying preprocessing techniques, classifying faces, and making predictions about attributes. The document discusses the methodology, existing techniques like PCA and HMM, the proposed system architecture, sample code, and conclusions.
This paper discusses the implementation issues of installing a commercially available hand geometry system in the current infrastructure of Purdue University's Recreational Sports Center. In addition to a performance analysis of the system, a pre- and post- data collection survey was distributed to the 129 test subjects gathering information on perceptions of biometrics, in particular hand geometry, as well as participants' thoughts and feelings during their interaction with the hand geometry device. The results of the survey suggest that participants were accepting of hand geometry. Additionally, analyses of the participants' survey responses revealed that 93% liked using hand geometry, 98% thought it was easy to use, and 87% preferred it to the existing card-based system, while nobody thought the device invaded their personal privacy. System performance achieved a 3-try match rate of 99.02% (FRR 0.98%) when "gaming"/potential impostor attempts were removed from analysis. The failure to enroll rate was zero. Statistical analyses exposed a significant difference in the scores of attempts made by users with prior hand geometry usage, and subjects that could not straighten out their hand on the device. However, there were no statistical difference in the effects of rings/no rings, improper hand placements/proper hand placements, or gender on hand geometry score.
This paper discusses the implementation issues of installing a commercially available hand geometry system in the current infrastructure of Purdue University's Recreational Sports Center. In addition to a performance analysis of the system, a pre- and post- data collection survey was distributed to the 129 test subjects gathering information on perceptions of biometrics, in particular hand geometry, as well as participants' thoughts and feelings during their interaction with the hand geometry device. The results of the survey suggest that participants were accepting of hand geometry. Additionally, analyses of the participants' survey responses revealed that 93% liked using hand geometry, 98% thought it was easy to use, and 87% preferred it to the existing card-based system, while nobody thought the device invaded their personal privacy. System performance achieved a 3-try match rate of 99.02% (FRR 0.98%) when "gaming"/potential impostor attempts were removed from analysis. The failure to enroll rate was zero. Statistical analyses exposed a significant difference in the scores of attempts made by users with prior hand geometry usage, and subjects that could not straighten out their hand on the device. However, there were no statistical difference in the effects of rings/no rings, improper hand placements/proper hand placements, or gender on hand geometry score.
The biometric is a study of human behavior and features. Face recognition is a technique of biometric. Various approaches are used for it. Face recognition is emerging branch of biometric for security as no faces can be defeated as a security approach. So, how we can recognize a face with the help of computers is given in this paper. The typical way that a FRS can be used for identification purposes. The effectiveness of the whole system is highly dependent on the quality and characteristics of the captured face image. The process begins with face detection and extraction from the larger image, which generally contains a background and often more complex patterns and even other faces. A survey for all these techniques is in this paper for analyzing various algorithms and methods. Sagar Deshmukh | Sanjay Rawat | Shubhangi Patil"Face Recognition Technology" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14331.pdf http://www.ijtsrd.com/computer-science/artificial-intelligence/14331/face-recognition-technology/sagar-deshmukh
A Hybrid Approach to Face Detection And Feature Extractioniosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Eye tracking system has played a significant role in many of today’s applications ranging from military
applications to automotive industries and healthcare sectors. In this paper, a novel system for eye tracking and
estimation of its direction of movement is performed. The proposed system is implemented in real time using an
arduino uno microcontroller and a zigbee wireless device. Experimental results show a successful eye tracking and
movement estimation in real time scenario using the proposed hardware interface.
Explaining Aluminous Ascientification Of Significance Examples Of Personal St...SubmissionResearchpa
This article lists the results of an experimental test of algorithms for recognizing ear tags. Like most biometric technologies, one of the key issues is the separation of the characteristic image, which is also included in the recognition of the person on the basis of the ear studship. Because the accuracy and accuracy of the program depends on the criteria for recognizing the person on the basis of any biometric technology. Therefore, by distinguishing the problem of discrete cosine exchange, using the main component method and algorithms for separation, the characteristic sign of the ear stud was detected. These algorithms can be used to develop personal identification systems based on earphones. by Djuraeva Rano Bahrombekovna, Mukhammadiev Alisher Numonhan-ugli, Khodjaeva Mavluda Sabirovna and Jumaev Turdali Saminjonovich 2020. Explaining Aluminous Ascientification Of Significance Examples Of Personal Study On Personal Identity. International Journal on Integrated Education. 2, 1 (Mar. 2020), 48-52. DOI:https://doi.org/10.31149/ijie.v2i1.287. https://journals.researchparks.org/index.php/IJIE/article/view/287/280 https://journals.researchparks.org/index.php/IJIE/article/view/287
Review of face detection systems based artificial neural networks algorithmsijma
Face detection is one of the most relevant applications of image processing and biometric systems.
Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition.
There is lack of literature surveys which give overview about the studies and researches related to the using
of ANN in face detection. Therefore, this research includes a general review of face detection studies and
systems which based on different ANN approaches and algorithms. The strengths and limitations of these
literature studies and systems were included also.
AN IMPROVED TECHNIQUE FOR HUMAN FACE RECOGNITION USING IMAGE PROCESSINGijiert bestjournal
Face recognition is a computer application technique for automatically identifying or
verifying a person from a digital image or a video frame source. To do this is by comparing
selected facial features from the digital image and a face dataset. It is basically used in
security systems and can be compared to other biometrics such as fingerprint recognition or
eye, iris recognition systems. The main limitation of the current face recognition system is
that they only detect straight faces looking at the camera. Separate versions of the system
could be trained for each head orientation, and the results can be combined using arbitration
methods similar to those presented here. In earlier work, the face position must be centerlight
position; any lighting effect will affect the system. Similarly the eyes of person must be
open and without glass.
Human Face Detection and Tracking for Age Rank, Weight and Gender Estimation ...IJERA Editor
This paper describes the technique for real time human face detection and tracking for age rank, weight and gender estimation. Face detection is involved with finding whether there are any faces in a given image and if there are any faces present, track the face and returns the face region with features of each face. Here it describes a simple and convenient hardware implementation of face detection method using Raspberry Pi Processor, which itself is a minicomputer of a credit card size. This paper presents a cost-sensitive ordinal hyperplanes ranking algorithm for human age evaluation based on face images. Two main components for building an efficient age estimator are facial feature extraction and estimator learning. Using feature extraction and comparing with our input database in which we have different age group face images with weight is specified according to that we also specify weight category i.e. under weight, normal weight and overweight . In this article we present gender estimation technique, which effectively integrates the head as well as mouth motion information with facial appearance by taking advantage of a unified probabilistic framework. Facial appearance as well as head and mouth motion possess a potentially relevant discriminatory power, and that the integration of different sources of biometric data from video sequences is the key approach to develop more precise and reliable realization systems.
Face Recognition plays a major role in Biometrics. Feature selection is a measure issue in face
recognition. This paper proposes a survey on face recognition. There are many methods to extract face
features. In some advanced methods it can be extracted faster in a single scan through the raw image and
lie in a lower dimensional space, but still retaining facial information efficiently. The methods which are
used to extract features are robust to low-resolution images. The method is a trainable system for selecting
face features. After the feature selection procedure next procedure is matching for face recognition. The
recognition accuracy is increased by advanced methods.
Face recognition is the ability of categorize a set of images based on certain discriminatory features. Classification of the recognition patterns can be difficult problem and it is still very active field of research. The paper introduces conceptual framework for descriptive study on techniques of face recognition systems. It aims to describe the previous researches have been study the face recognition system, in order scope on the algorithms, usages, benefits , challenges and problems in this felids, the paper proposed the face recognition as sensitive learning task experiments on a large face databases demonstrate of the new feature. The researcher recommends that there's a needs to evaluate the previous studies and researches, especially on face recognition field and 3D, hopeful for advanced techniques and methods in the near future.
Face detection is one of the most suitable applications for image processing and biometric programs. Artificial neural networks have been used in the many field like image processing, pattern recognition, sales forecasting, customer research and data validation. Face detection and recognition have become one of the most popular biometric techniques over the past few years. There is a lack of research literature that provides an overview of studies and research-related research of Artificial neural networks face detection. Therefore, this study includes a review of facial recognition studies as well systems based on various Artificial neural networks methods and algorithms.
AI Approach for Iris Biometric Recognition Using a Median FilterNIDHI SHARMA
The Artificial Intelligence approach is used for Iris recognition by understanding the distinctive and measurable characteristics of the human body such as a person’s face, iris, DNA, fingerprints, etc. AI methods analyzed the attributes like iris images. Privacy and Security being a major concern nowadays, Recognition Technique can find numerous applications.
Face Recognition Based Attendance System using Machine LearningYogeshIJTSRD
In the era of modern technologies emerging at rapid pace there is no reason why a crucial event in education sector such as attendance should be done in the old boring traditional way. Attendance monitoring system will save a lot of time and energy for the both parties teaching staff as well as the students. Attendance will be monitored by the face recognition algorithm by recognizing only the face of the students from the rest of the objects and then marking the students as present. The system will be pre feed with the images of all the students enrolled in the class and with the help of this pre feed data the algorithm will detect the students who are present and match the features with the already saved images of the students in the database. Benazir Begum A | Sreeyuktha R | Haritha M P | Vishnuprasad "Face Recognition Based Attendance System using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39856.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/39856/face-recognition-based-attendance-system-using-machine-learning/benazir-begum-a
Facial image classification and searching –a surveyZac Darcy
Recent developments in the area of image mining have shown the way for incredible growth in
extensively large and detailed image databases. The images which are available in these
databases, if checked, can endow with valuable information to the human users. As one of the
most successful applications of image analysis and understanding, fac
e recognition has
recently gained important attention particularly throughout the past many years. Though
tracking and recognizing face objects is a routine task, building such a system is still an active
research. Among several proposed face rec
ognition schemes, shape based approaches are
possibly the most promising ones. This paper provides an overview of various
classification and retrieval methods that were proposed earlier in literature. Also, this paper
provides a margina
l summary for future research and enhancements in face detection
The biometric is a study of human behavior and features. Face recognition is a technique of biometric. Various approaches are used for it. Face recognition is emerging branch of biometric for security as no faces can be defeated as a security approach. So, how we can recognize a face with the help of computers is given in this paper. The typical way that a FRS can be used for identification purposes. The effectiveness of the whole system is highly dependent on the quality and characteristics of the captured face image. The process begins with face detection and extraction from the larger image, which generally contains a background and often more complex patterns and even other faces. A survey for all these techniques is in this paper for analyzing various algorithms and methods. Sagar Deshmukh | Sanjay Rawat | Shubhangi Patil"Face Recognition Technology" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14331.pdf http://www.ijtsrd.com/computer-science/artificial-intelligence/14331/face-recognition-technology/sagar-deshmukh
A Hybrid Approach to Face Detection And Feature Extractioniosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Eye tracking system has played a significant role in many of today’s applications ranging from military
applications to automotive industries and healthcare sectors. In this paper, a novel system for eye tracking and
estimation of its direction of movement is performed. The proposed system is implemented in real time using an
arduino uno microcontroller and a zigbee wireless device. Experimental results show a successful eye tracking and
movement estimation in real time scenario using the proposed hardware interface.
Explaining Aluminous Ascientification Of Significance Examples Of Personal St...SubmissionResearchpa
This article lists the results of an experimental test of algorithms for recognizing ear tags. Like most biometric technologies, one of the key issues is the separation of the characteristic image, which is also included in the recognition of the person on the basis of the ear studship. Because the accuracy and accuracy of the program depends on the criteria for recognizing the person on the basis of any biometric technology. Therefore, by distinguishing the problem of discrete cosine exchange, using the main component method and algorithms for separation, the characteristic sign of the ear stud was detected. These algorithms can be used to develop personal identification systems based on earphones. by Djuraeva Rano Bahrombekovna, Mukhammadiev Alisher Numonhan-ugli, Khodjaeva Mavluda Sabirovna and Jumaev Turdali Saminjonovich 2020. Explaining Aluminous Ascientification Of Significance Examples Of Personal Study On Personal Identity. International Journal on Integrated Education. 2, 1 (Mar. 2020), 48-52. DOI:https://doi.org/10.31149/ijie.v2i1.287. https://journals.researchparks.org/index.php/IJIE/article/view/287/280 https://journals.researchparks.org/index.php/IJIE/article/view/287
Review of face detection systems based artificial neural networks algorithmsijma
Face detection is one of the most relevant applications of image processing and biometric systems.
Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition.
There is lack of literature surveys which give overview about the studies and researches related to the using
of ANN in face detection. Therefore, this research includes a general review of face detection studies and
systems which based on different ANN approaches and algorithms. The strengths and limitations of these
literature studies and systems were included also.
AN IMPROVED TECHNIQUE FOR HUMAN FACE RECOGNITION USING IMAGE PROCESSINGijiert bestjournal
Face recognition is a computer application technique for automatically identifying or
verifying a person from a digital image or a video frame source. To do this is by comparing
selected facial features from the digital image and a face dataset. It is basically used in
security systems and can be compared to other biometrics such as fingerprint recognition or
eye, iris recognition systems. The main limitation of the current face recognition system is
that they only detect straight faces looking at the camera. Separate versions of the system
could be trained for each head orientation, and the results can be combined using arbitration
methods similar to those presented here. In earlier work, the face position must be centerlight
position; any lighting effect will affect the system. Similarly the eyes of person must be
open and without glass.
Human Face Detection and Tracking for Age Rank, Weight and Gender Estimation ...IJERA Editor
This paper describes the technique for real time human face detection and tracking for age rank, weight and gender estimation. Face detection is involved with finding whether there are any faces in a given image and if there are any faces present, track the face and returns the face region with features of each face. Here it describes a simple and convenient hardware implementation of face detection method using Raspberry Pi Processor, which itself is a minicomputer of a credit card size. This paper presents a cost-sensitive ordinal hyperplanes ranking algorithm for human age evaluation based on face images. Two main components for building an efficient age estimator are facial feature extraction and estimator learning. Using feature extraction and comparing with our input database in which we have different age group face images with weight is specified according to that we also specify weight category i.e. under weight, normal weight and overweight . In this article we present gender estimation technique, which effectively integrates the head as well as mouth motion information with facial appearance by taking advantage of a unified probabilistic framework. Facial appearance as well as head and mouth motion possess a potentially relevant discriminatory power, and that the integration of different sources of biometric data from video sequences is the key approach to develop more precise and reliable realization systems.
Face Recognition plays a major role in Biometrics. Feature selection is a measure issue in face
recognition. This paper proposes a survey on face recognition. There are many methods to extract face
features. In some advanced methods it can be extracted faster in a single scan through the raw image and
lie in a lower dimensional space, but still retaining facial information efficiently. The methods which are
used to extract features are robust to low-resolution images. The method is a trainable system for selecting
face features. After the feature selection procedure next procedure is matching for face recognition. The
recognition accuracy is increased by advanced methods.
Face recognition is the ability of categorize a set of images based on certain discriminatory features. Classification of the recognition patterns can be difficult problem and it is still very active field of research. The paper introduces conceptual framework for descriptive study on techniques of face recognition systems. It aims to describe the previous researches have been study the face recognition system, in order scope on the algorithms, usages, benefits , challenges and problems in this felids, the paper proposed the face recognition as sensitive learning task experiments on a large face databases demonstrate of the new feature. The researcher recommends that there's a needs to evaluate the previous studies and researches, especially on face recognition field and 3D, hopeful for advanced techniques and methods in the near future.
Face detection is one of the most suitable applications for image processing and biometric programs. Artificial neural networks have been used in the many field like image processing, pattern recognition, sales forecasting, customer research and data validation. Face detection and recognition have become one of the most popular biometric techniques over the past few years. There is a lack of research literature that provides an overview of studies and research-related research of Artificial neural networks face detection. Therefore, this study includes a review of facial recognition studies as well systems based on various Artificial neural networks methods and algorithms.
AI Approach for Iris Biometric Recognition Using a Median FilterNIDHI SHARMA
The Artificial Intelligence approach is used for Iris recognition by understanding the distinctive and measurable characteristics of the human body such as a person’s face, iris, DNA, fingerprints, etc. AI methods analyzed the attributes like iris images. Privacy and Security being a major concern nowadays, Recognition Technique can find numerous applications.
Face Recognition Based Attendance System using Machine LearningYogeshIJTSRD
In the era of modern technologies emerging at rapid pace there is no reason why a crucial event in education sector such as attendance should be done in the old boring traditional way. Attendance monitoring system will save a lot of time and energy for the both parties teaching staff as well as the students. Attendance will be monitored by the face recognition algorithm by recognizing only the face of the students from the rest of the objects and then marking the students as present. The system will be pre feed with the images of all the students enrolled in the class and with the help of this pre feed data the algorithm will detect the students who are present and match the features with the already saved images of the students in the database. Benazir Begum A | Sreeyuktha R | Haritha M P | Vishnuprasad "Face Recognition Based Attendance System using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39856.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/39856/face-recognition-based-attendance-system-using-machine-learning/benazir-begum-a
Facial image classification and searching –a surveyZac Darcy
Recent developments in the area of image mining have shown the way for incredible growth in
extensively large and detailed image databases. The images which are available in these
databases, if checked, can endow with valuable information to the human users. As one of the
most successful applications of image analysis and understanding, fac
e recognition has
recently gained important attention particularly throughout the past many years. Though
tracking and recognizing face objects is a routine task, building such a system is still an active
research. Among several proposed face rec
ognition schemes, shape based approaches are
possibly the most promising ones. This paper provides an overview of various
classification and retrieval methods that were proposed earlier in literature. Also, this paper
provides a margina
l summary for future research and enhancements in face detection
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
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Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
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Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
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CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.