Pub Date : 2018-03-29DOI: 10.1109/ICECA.2018.8474882
V. Thanikaiselvan, Paras Mani Seth, K. Nirmal
Wireless MIMO(Multiple input and multiple output) is a wireless communication setup in which the transmission is done using multiple antenna at both transmitter and the receiver side for efficient and errorless transmission. In this paper an algorithm is proposed for selecting the node which will take part in intra communication between different clusters of mimo network. The advantage of this algorithm is enhancement in security of a wireless MIMO thus making it less prone to attack, hence improving the reliability of data.
{"title":"Compromised Node Detection in MIMO with Increased Security","authors":"V. Thanikaiselvan, Paras Mani Seth, K. Nirmal","doi":"10.1109/ICECA.2018.8474882","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474882","url":null,"abstract":"Wireless MIMO(Multiple input and multiple output) is a wireless communication setup in which the transmission is done using multiple antenna at both transmitter and the receiver side for efficient and errorless transmission. In this paper an algorithm is proposed for selecting the node which will take part in intra communication between different clusters of mimo network. The advantage of this algorithm is enhancement in security of a wireless MIMO thus making it less prone to attack, hence improving the reliability of data.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122616756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-29DOI: 10.1109/ICECA.2018.8474624
L. Priya, S. Aarthi, S. M. Preethi, P. E. Jothi, R. Aruna, M. Anitha
Electrocardiography (ECG) is the recording of the electrical activity of the heart with the help of the electrodes placed on the skin. The transmission of the ECG signal is very helpful in the field of Telemedicine. This will help the doctors to view the patient's ECG who is living in the remote region. Other applications are ambulance monitoring, Intensive Care Unit (ICU) patient monitoring, home patient monitoring, etc, where Internet of Things (IoT) plays a major role in the transmission of medical data and information. In existing wireless technology like Global System for Mobile Communication (GSM), Satellite, Bluetooth, zigbee, etc., communication of data, installation and other practical difficulties are quite complex. But in IoT even long distance communication is made that much easier when compared to other methods.
{"title":"Development of Telecardiology Monitor using Internet of Things","authors":"L. Priya, S. Aarthi, S. M. Preethi, P. E. Jothi, R. Aruna, M. Anitha","doi":"10.1109/ICECA.2018.8474624","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474624","url":null,"abstract":"Electrocardiography (ECG) is the recording of the electrical activity of the heart with the help of the electrodes placed on the skin. The transmission of the ECG signal is very helpful in the field of Telemedicine. This will help the doctors to view the patient's ECG who is living in the remote region. Other applications are ambulance monitoring, Intensive Care Unit (ICU) patient monitoring, home patient monitoring, etc, where Internet of Things (IoT) plays a major role in the transmission of medical data and information. In existing wireless technology like Global System for Mobile Communication (GSM), Satellite, Bluetooth, zigbee, etc., communication of data, installation and other practical difficulties are quite complex. But in IoT even long distance communication is made that much easier when compared to other methods.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124208133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-29DOI: 10.1109/ICECA.2018.8474728
V. Pawar, Nilesh P. Bhosale
The Internet of Things (IoT) is a state of art paradigm that makes any electronic apparatus as part of the Internet atmosphere. IoT is about mounting sensors (RFID, IR etc.) for everything, furthermore, interfacing them to web through protocols for data exchange and communications, to attain smart recognition, location tracking, supervising and controlling. In current work, we invented a novel IoT based framework to develop Smart Local Bus Transportation System (SLBTS). The proposed system comprises of electronic device that is located in the moving public vehicle which provides real time data, a cloud server that absorbs this data, application software installed at bus depot and a mobile application for commuters travelling in buses. The devices gather substantial amount of information like number of passengers travelling, vehicle speed, fuel level, engine temperature and being connected to internet the collected information is synched up with cloud server to convert it into some useful data. Passengers in turn can check the status of bus on mobile app by entering bus number. The current work, realizes the full potential of IoT, also discourses its several challenges and advances the conceptual solutions to tackle them.
{"title":"Internet-of-Things Based Smart Local Bus Transport Management System","authors":"V. Pawar, Nilesh P. Bhosale","doi":"10.1109/ICECA.2018.8474728","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474728","url":null,"abstract":"The Internet of Things (IoT) is a state of art paradigm that makes any electronic apparatus as part of the Internet atmosphere. IoT is about mounting sensors (RFID, IR etc.) for everything, furthermore, interfacing them to web through protocols for data exchange and communications, to attain smart recognition, location tracking, supervising and controlling. In current work, we invented a novel IoT based framework to develop Smart Local Bus Transportation System (SLBTS). The proposed system comprises of electronic device that is located in the moving public vehicle which provides real time data, a cloud server that absorbs this data, application software installed at bus depot and a mobile application for commuters travelling in buses. The devices gather substantial amount of information like number of passengers travelling, vehicle speed, fuel level, engine temperature and being connected to internet the collected information is synched up with cloud server to convert it into some useful data. Passengers in turn can check the status of bus on mobile app by entering bus number. The current work, realizes the full potential of IoT, also discourses its several challenges and advances the conceptual solutions to tackle them.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125771545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The more traditional approach towards launching a complaint is through written complaints that would be dropped into the complaint boxes available in some sectors, which has a lot of problems associated with it such as loss of complaints, security issues, etc. The proposed model that is structured towards replacement of this approach is an online complaint bot that would accept complaints through the onion routing algorithm. This would indeed secure complainant's identity and the bot would also use NLP to prioritize the complaints based on keywords. It would also direct it towards concerned authorities with a timestamp associated with each complaint and this complaint would have an id being sent back to the complainant for tracking of the issue on an online portal. These traits would in turn result into a system where data flows faster than the traditional approach and effective results a shorter time interval.
{"title":"Secure Complaint bot using Onion Routing Algorithm Concealing identities to increase effectiveness of complain bot","authors":"Abhishek Naik, Apurva Saksena, Kumaresan Mudliar, Ayesha Kazi, Prerna Sukhija, R. Pawar","doi":"10.1109/ICECA.2018.8474839","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474839","url":null,"abstract":"The more traditional approach towards launching a complaint is through written complaints that would be dropped into the complaint boxes available in some sectors, which has a lot of problems associated with it such as loss of complaints, security issues, etc. The proposed model that is structured towards replacement of this approach is an online complaint bot that would accept complaints through the onion routing algorithm. This would indeed secure complainant's identity and the bot would also use NLP to prioritize the complaints based on keywords. It would also direct it towards concerned authorities with a timestamp associated with each complaint and this complaint would have an id being sent back to the complainant for tracking of the issue on an online portal. These traits would in turn result into a system where data flows faster than the traditional approach and effective results a shorter time interval.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"7 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130275138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-29DOI: 10.1109/ICECA.2018.8474912
Suresh Dara, Priyanka Tumma
Deep learning is presently an effective research area in machine learning technique and pattern classification association. This has achieved big success in the areas of application namely computer vision, speech recognition, and NLP. This paper gives the impact of feature extraction that used in a deep learning technique such as Convolutional Neural Network (CNN). The purpose of this paper presents an emerged survey of actual literatures on feature extraction methods since past five years. As the raising of application demand increases, a large study and analysis in the feature extraction field became very efficient. In this paper, we presented a detailed study on deep learning, and a described some of existing methodology of feature extraction.
{"title":"Feature Extraction By Using Deep Learning: A Survey","authors":"Suresh Dara, Priyanka Tumma","doi":"10.1109/ICECA.2018.8474912","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474912","url":null,"abstract":"Deep learning is presently an effective research area in machine learning technique and pattern classification association. This has achieved big success in the areas of application namely computer vision, speech recognition, and NLP. This paper gives the impact of feature extraction that used in a deep learning technique such as Convolutional Neural Network (CNN). The purpose of this paper presents an emerged survey of actual literatures on feature extraction methods since past five years. As the raising of application demand increases, a large study and analysis in the feature extraction field became very efficient. In this paper, we presented a detailed study on deep learning, and a described some of existing methodology of feature extraction.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"60 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131720427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-29DOI: 10.1109/ICECA.2018.8474572
Sneha N. Gauns Dessai, Sangam Borkar
In this paper, we present the segmentation of fingernail patterns. In order to segment the nail and to extract the only the ROI from nail plate, the ROI segmentation technique is used which helps to mask the texture based properties from the required portion from the fingernail.
{"title":"ROI Segmentation for Feature Extraction from Human Fingernail","authors":"Sneha N. Gauns Dessai, Sangam Borkar","doi":"10.1109/ICECA.2018.8474572","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474572","url":null,"abstract":"In this paper, we present the segmentation of fingernail patterns. In order to segment the nail and to extract the only the ROI from nail plate, the ROI segmentation technique is used which helps to mask the texture based properties from the required portion from the fingernail.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115820584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-29DOI: 10.1109/ICECA.2018.8474790
A. V. Reddy, B. M. Kumar
The tremendous changes in solid state electronics technology from few decades, it leads the Switched Reluctance Motor (SRM) is trending machine in the areas of aerospace, electric and hybrid electric vehicles etc. Even though this motor is fault tolerant but it is not absolute. In order to avoid discontinuity of service, loss of economy and time wastage, predefinition of various faults is most important. Eccentricity problem is one of the mostly occurring mechanical faults in rotating machines due to the non-uniformity in air gap. It is prerequisite to forecast and diagnose the faults to achieve better performance of the motor. The simulation results for the sample 500 watt motor successfully exhibited the effects of the air gap faults and its impact on the currents through the stator windings, and analyzed how differential current varies with respect to various degrees of faults.
{"title":"Analysis of Various Levels of Air Gap Eccentricity Faults In Switched Reluctance Motor","authors":"A. V. Reddy, B. M. Kumar","doi":"10.1109/ICECA.2018.8474790","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474790","url":null,"abstract":"The tremendous changes in solid state electronics technology from few decades, it leads the Switched Reluctance Motor (SRM) is trending machine in the areas of aerospace, electric and hybrid electric vehicles etc. Even though this motor is fault tolerant but it is not absolute. In order to avoid discontinuity of service, loss of economy and time wastage, predefinition of various faults is most important. Eccentricity problem is one of the mostly occurring mechanical faults in rotating machines due to the non-uniformity in air gap. It is prerequisite to forecast and diagnose the faults to achieve better performance of the motor. The simulation results for the sample 500 watt motor successfully exhibited the effects of the air gap faults and its impact on the currents through the stator windings, and analyzed how differential current varies with respect to various degrees of faults.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124033213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-29DOI: 10.1109/ICECA.2018.8474917
Rahul Ravichandran, Akshay Kumar, R. Kumar
The implementation and efficacy of closed loop systems in machines with moving limbs/parts is largely dependent upon the feedback systems that measure the extent of motion - linear or rotational. This paper proposes a novel technique for measurement of joint angles and thus rotational motion for links pivoted at a powered/non-powered joint, using low-cost inertial sensors. The paper proposes the substitution of noisy, inefficient and poor resolution mechanical sensors like optical or pulse encoders with tri-axial accelerometers and tri-axial gyroscope fused in low-cost Inertial Measurement Units(IMUs). This technique is used to measure the angles between the various joints of a bipedal robot and estimate its complete orientation in three dimensional space. The crux of this paper is utilizing the extended capabilities of the inertial sensors in joint angle estimation for closed loop operation of a twelve-Degree Of Freedom(DOF) lower body biped robot with potential implementation on stable bent knee walking on flat surfaces. All the joints of the biped are revolute and facilitate rotation of various limbs like thigh, shin and foot, analogous to a human leg. All links have IMUs mounted on them for the proposed task.
{"title":"Joint Angle Measurement Using MEMs Based Inertial Sensors for Biped Robot","authors":"Rahul Ravichandran, Akshay Kumar, R. Kumar","doi":"10.1109/ICECA.2018.8474917","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474917","url":null,"abstract":"The implementation and efficacy of closed loop systems in machines with moving limbs/parts is largely dependent upon the feedback systems that measure the extent of motion - linear or rotational. This paper proposes a novel technique for measurement of joint angles and thus rotational motion for links pivoted at a powered/non-powered joint, using low-cost inertial sensors. The paper proposes the substitution of noisy, inefficient and poor resolution mechanical sensors like optical or pulse encoders with tri-axial accelerometers and tri-axial gyroscope fused in low-cost Inertial Measurement Units(IMUs). This technique is used to measure the angles between the various joints of a bipedal robot and estimate its complete orientation in three dimensional space. The crux of this paper is utilizing the extended capabilities of the inertial sensors in joint angle estimation for closed loop operation of a twelve-Degree Of Freedom(DOF) lower body biped robot with potential implementation on stable bent knee walking on flat surfaces. All the joints of the biped are revolute and facilitate rotation of various limbs like thigh, shin and foot, analogous to a human leg. All links have IMUs mounted on them for the proposed task.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125851718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dermatology is one of the most unpredictable and difficult terrains to diagnose due its complexity. In the field of dermatology, many a times extensive tests are to be carried out so as to decide upon the skin condition the patient may be facing. The time may vary from practitioner to practitioner. This is also based on the experience of that person too. So, there is a need of a system which can diagnose the skin diseases without any of these constraints. We propose an automated image based system for recognition of skin diseases using machine learning classification. This system will utilize computational technique to analyze, process, and relegate the image data predicated on various features of the images. Skin images are filtered to remove unwanted noise and also process it for enhancement of the image. Feature extraction using complex techniques such as Convolutional Neural Network (CNN), classify the image based on the algorithm of softmax classifier and obtain the diagnosis report as an output. This system will give more accuracy and will generate results faster than the traditional method, making this application an efficient and dependable system for dermatological disease detection. Furthermore, this can also be used as a reliable real time teaching tool for medical students in the dermatology stream.
{"title":"Diagnosis of skin diseases using Convolutional Neural Networks","authors":"Jainesh Rathod, Vishal Wazhmode, Aniruddh Sodha, Praseniit Bhavathankar","doi":"10.1109/ICECA.2018.8474593","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474593","url":null,"abstract":"Dermatology is one of the most unpredictable and difficult terrains to diagnose due its complexity. In the field of dermatology, many a times extensive tests are to be carried out so as to decide upon the skin condition the patient may be facing. The time may vary from practitioner to practitioner. This is also based on the experience of that person too. So, there is a need of a system which can diagnose the skin diseases without any of these constraints. We propose an automated image based system for recognition of skin diseases using machine learning classification. This system will utilize computational technique to analyze, process, and relegate the image data predicated on various features of the images. Skin images are filtered to remove unwanted noise and also process it for enhancement of the image. Feature extraction using complex techniques such as Convolutional Neural Network (CNN), classify the image based on the algorithm of softmax classifier and obtain the diagnosis report as an output. This system will give more accuracy and will generate results faster than the traditional method, making this application an efficient and dependable system for dermatological disease detection. Furthermore, this can also be used as a reliable real time teaching tool for medical students in the dermatology stream.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129109971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-29DOI: 10.1109/ICECA.2018.8474594
Neelesh Bhakt, Pankaj Joshi, Piyush Dhyani
Smile is and has always been an evident parameter for judging one's state of mind. An indicator of emotions, a smile can be categorized into two types. Some are real, originating from an exhilarated atmosphere, while some are fake. Hence, it becomes utterly difficult to differentiate between the two smiles. This research work is based on capturing the movement of zygomatic major and obicularis oculli which plays a vital role in detecting whether a smile is fake or real. The appearance of wrinkles on the cheeks, corner of the mouth, indicate the contraction of the zygomatic major muscle, whereas the eye elongation indicates the obicularis oculli contraction. We have primarily worked on Videos in which the main emphasis is on the images of facial parts such as lips, eyes and cheeks area to distinguish between real and fake smile. The requisite portion of frames of training data videos are extracted and GIST is applied to it which is further trained by SVM. For test videos, the nature of frames for each video is predicted and based on the majority of real or fake frames in a video, it is classified into fake or real. Results show that the best accuracy in detecting true and fake smiles is close to 76.66%, while in reality, human true-fake-smile recognition ability is much lower. Thus, our work assures efficient output which could be used as a tool for the analysis of smiles in the psychological area and this research work can be further extended to detect fake and real expressions.
{"title":"A Novel Framework for Real and Fake Smile Detection from Videos","authors":"Neelesh Bhakt, Pankaj Joshi, Piyush Dhyani","doi":"10.1109/ICECA.2018.8474594","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474594","url":null,"abstract":"Smile is and has always been an evident parameter for judging one's state of mind. An indicator of emotions, a smile can be categorized into two types. Some are real, originating from an exhilarated atmosphere, while some are fake. Hence, it becomes utterly difficult to differentiate between the two smiles. This research work is based on capturing the movement of zygomatic major and obicularis oculli which plays a vital role in detecting whether a smile is fake or real. The appearance of wrinkles on the cheeks, corner of the mouth, indicate the contraction of the zygomatic major muscle, whereas the eye elongation indicates the obicularis oculli contraction. We have primarily worked on Videos in which the main emphasis is on the images of facial parts such as lips, eyes and cheeks area to distinguish between real and fake smile. The requisite portion of frames of training data videos are extracted and GIST is applied to it which is further trained by SVM. For test videos, the nature of frames for each video is predicted and based on the majority of real or fake frames in a video, it is classified into fake or real. Results show that the best accuracy in detecting true and fake smiles is close to 76.66%, while in reality, human true-fake-smile recognition ability is much lower. Thus, our work assures efficient output which could be used as a tool for the analysis of smiles in the psychological area and this research work can be further extended to detect fake and real expressions.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130794847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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