ºÝºÝߣshows by User: shritosh / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: shritosh / Fri, 12 Jun 2015 06:35:54 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: shritosh Artificial Neural Network and its Applications /slideshow/paper244/49300861 paper244-150612063554-lva1-app6892
Abstract This report is an introduction to Artificial Neural Networks. The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. The connection between the artificial and the real thing is also investigated and explained. Finally, the mathematical models involved are presented and demonstrated.]]>
Abstract This report is an introduction to Artificial Neural Networks. The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. The connection between the artificial and the real thing is also investigated and explained. Finally, the mathematical models involved are presented and demonstrated.]]> Fri, 12 Jun 2015 06:35:54 GMT /slideshow/paper244/49300861 shritosh@slideshare.net(shritosh) Artificial Neural Network and its Applications shritosh Abstract This report is an introduction to Artificial Neural Networks. The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. The connection between the artificial and the real thing is also investigated and explained. Finally, the mathematical models involved are presented and demonstrated. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/paper244-150612063554-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Abstract This report is an introduction to Artificial Neural Networks. The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. The connection between the artificial and the real thing is also investigated and explained. Finally, the mathematical models involved are presented and demonstrated.
Artificial Neural Network and its Applications from shritosh kumar
]]> 1665 7 https://cdn.slidesharecdn.com/ss_thumbnails/paper244-150612063554-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A survey-report-on-cloud-computing-testing-environment /slideshow/a-surveyreportoncloudcomputingtestingenvironment/49300236 a-survey-report-on-cloud-computing-testing-environment-150612062008-lva1-app6892
Cloud computing not only changes the way of obtaining computing resources (such as computers, infrastructures, data storage, and application services), but also changes the way of managing and delivering computing services, technologies, and solutions. Cloud computing leads an opportunity in offering testing as a service (TaaS) for SaaS and clouds. Meanwhile, it causes new issues, challenges and needs in software testing, particular in testing clouds and cloud-based applications. This paper provides a comprehensive tutorial on cloud testing and cloud-based application testing. It answers the common questions raised by engineers and managers, and it provides clear concepts, discusses the special objectives, features, requirements, and needs in cloud testing. It offers a clear comparative view between web-based software testing and cloud-based application testing. In addition, it examines the major issues, challenges, and needs in testing cloud-based software applications. Furthermore, it also summarizes and compares different commercial products and solutions supporting cloud testing as services.]]>
Cloud computing not only changes the way of obtaining computing resources (such as computers, infrastructures, data storage, and application services), but also changes the way of managing and delivering computing services, technologies, and solutions. Cloud computing leads an opportunity in offering testing as a service (TaaS) for SaaS and clouds. Meanwhile, it causes new issues, challenges and needs in software testing, particular in testing clouds and cloud-based applications. This paper provides a comprehensive tutorial on cloud testing and cloud-based application testing. It answers the common questions raised by engineers and managers, and it provides clear concepts, discusses the special objectives, features, requirements, and needs in cloud testing. It offers a clear comparative view between web-based software testing and cloud-based application testing. In addition, it examines the major issues, challenges, and needs in testing cloud-based software applications. Furthermore, it also summarizes and compares different commercial products and solutions supporting cloud testing as services.]]> Fri, 12 Jun 2015 06:20:08 GMT /slideshow/a-surveyreportoncloudcomputingtestingenvironment/49300236 shritosh@slideshare.net(shritosh) A survey-report-on-cloud-computing-testing-environment shritosh Cloud computing not only changes the way of obtaining computing resources (such as computers, infrastructures, data storage, and application services), but also changes the way of managing and delivering computing services, technologies, and solutions. Cloud computing leads an opportunity in offering testing as a service (TaaS) for SaaS and clouds. Meanwhile, it causes new issues, challenges and needs in software testing, particular in testing clouds and cloud-based applications. This paper provides a comprehensive tutorial on cloud testing and cloud-based application testing. It answers the common questions raised by engineers and managers, and it provides clear concepts, discusses the special objectives, features, requirements, and needs in cloud testing. It offers a clear comparative view between web-based software testing and cloud-based application testing. In addition, it examines the major issues, challenges, and needs in testing cloud-based software applications. Furthermore, it also summarizes and compares different commercial products and solutions supporting cloud testing as services. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/a-survey-report-on-cloud-computing-testing-environment-150612062008-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Cloud computing not only changes the way of obtaining computing resources (such as computers, infrastructures, data storage, and application services), but also changes the way of managing and delivering computing services, technologies, and solutions. Cloud computing leads an opportunity in offering testing as a service (TaaS) for SaaS and clouds. Meanwhile, it causes new issues, challenges and needs in software testing, particular in testing clouds and cloud-based applications. This paper provides a comprehensive tutorial on cloud testing and cloud-based application testing. It answers the common questions raised by engineers and managers, and it provides clear concepts, discusses the special objectives, features, requirements, and needs in cloud testing. It offers a clear comparative view between web-based software testing and cloud-based application testing. In addition, it examines the major issues, challenges, and needs in testing cloud-based software applications. Furthermore, it also summarizes and compares different commercial products and solutions supporting cloud testing as services.
A survey-report-on-cloud-computing-testing-environment from shritosh kumar
]]> 179 4 https://cdn.slidesharecdn.com/ss_thumbnails/a-survey-report-on-cloud-computing-testing-environment-150612062008-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Performance of Gabor Mean Feature Extraction Techniques for Ear Biometrics Recognition /slideshow/24-052015481-v2e6072-49299751/49299751 24-05-2015481v2-e6-072-150612060255-lva1-app6891
Abstract Ear biometric recognition is used in a lot of applications as person identification in criminal cases, investigation, and security purpose. Feature optimization stage has an important role for accuracy of correct recognition. Gabor filter have a problem of high dimension and high redundancy. Sampling filter is a problem of not reducing features optimum way. In the proposed Gabor feature extraction technique the Gabor features are filtered using proposed mean filter and obtained optimum features for ear biometric dataset.]]>
Abstract Ear biometric recognition is used in a lot of applications as person identification in criminal cases, investigation, and security purpose. Feature optimization stage has an important role for accuracy of correct recognition. Gabor filter have a problem of high dimension and high redundancy. Sampling filter is a problem of not reducing features optimum way. In the proposed Gabor feature extraction technique the Gabor features are filtered using proposed mean filter and obtained optimum features for ear biometric dataset.]]> Fri, 12 Jun 2015 06:02:54 GMT /slideshow/24-052015481-v2e6072-49299751/49299751 shritosh@slideshare.net(shritosh) Performance of Gabor Mean Feature Extraction Techniques for Ear Biometrics Recognition shritosh Abstract Ear biometric recognition is used in a lot of applications as person identification in criminal cases, investigation, and security purpose. Feature optimization stage has an important role for accuracy of correct recognition. Gabor filter have a problem of high dimension and high redundancy. Sampling filter is a problem of not reducing features optimum way. In the proposed Gabor feature extraction technique the Gabor features are filtered using proposed mean filter and obtained optimum features for ear biometric dataset. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/24-05-2015481v2-e6-072-150612060255-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Abstract Ear biometric recognition is used in a lot of applications as person identification in criminal cases, investigation, and security purpose. Feature optimization stage has an important role for accuracy of correct recognition. Gabor filter have a problem of high dimension and high redundancy. Sampling filter is a problem of not reducing features optimum way. In the proposed Gabor feature extraction technique the Gabor features are filtered using proposed mean filter and obtained optimum features for ear biometric dataset.
Performance of Gabor Mean Feature Extraction Techniques for Ear Biometrics Recognition from shritosh kumar
]]> 398 4 https://cdn.slidesharecdn.com/ss_thumbnails/24-05-2015481v2-e6-072-150612060255-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Review of Detection & Recognition Techniques for 2D Ear Biometrics System /shritosh/24-052015481-v2e6072 24-05-2015481v2-e6-072-150612055917-lva1-app6891
Abstract Authentication of a person's identity is a very old but challenging problem. There are three common ways which are used for authentication. First one is based on what a person has (Possession) such as keys, identity cards etc. Second mode of authentication is based on what a person knows or remembers (Knowledge) such as passwords, PINs etc. Third way of authentication is based on what a person carries, i.e. the characteristics of a human being (Biometrics). Biometrics is the science of establishing human identity by using physical or behavioural traits such as face, fingerprints, palm prints, iris, hand geometry, ear, and voice. There are some significant works which have been carried out in past few years in the field of ear biometrics. In this survey discusses various technique of ear Detection & Recognition for 2D ear biometric, and provides good future prospects for the upcoming researchers in the field of ear biometric.]]>
Abstract Authentication of a person's identity is a very old but challenging problem. There are three common ways which are used for authentication. First one is based on what a person has (Possession) such as keys, identity cards etc. Second mode of authentication is based on what a person knows or remembers (Knowledge) such as passwords, PINs etc. Third way of authentication is based on what a person carries, i.e. the characteristics of a human being (Biometrics). Biometrics is the science of establishing human identity by using physical or behavioural traits such as face, fingerprints, palm prints, iris, hand geometry, ear, and voice. There are some significant works which have been carried out in past few years in the field of ear biometrics. In this survey discusses various technique of ear Detection & Recognition for 2D ear biometric, and provides good future prospects for the upcoming researchers in the field of ear biometric.]]> Fri, 12 Jun 2015 05:59:17 GMT /shritosh/24-052015481-v2e6072 shritosh@slideshare.net(shritosh) Review of Detection & Recognition Techniques for 2D Ear Biometrics System shritosh Abstract Authentication of a person's identity is a very old but challenging problem. There are three common ways which are used for authentication. First one is based on what a person has (Possession) such as keys, identity cards etc. Second mode of authentication is based on what a person knows or remembers (Knowledge) such as passwords, PINs etc. Third way of authentication is based on what a person carries, i.e. the characteristics of a human being (Biometrics). Biometrics is the science of establishing human identity by using physical or behavioural traits such as face, fingerprints, palm prints, iris, hand geometry, ear, and voice. There are some significant works which have been carried out in past few years in the field of ear biometrics. In this survey discusses various technique of ear Detection & Recognition for 2D ear biometric, and provides good future prospects for the upcoming researchers in the field of ear biometric. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/24-05-2015481v2-e6-072-150612055917-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Abstract Authentication of a person&#39;s identity is a very old but challenging problem. There are three common ways which are used for authentication. First one is based on what a person has (Possession) such as keys, identity cards etc. Second mode of authentication is based on what a person knows or remembers (Knowledge) such as passwords, PINs etc. Third way of authentication is based on what a person carries, i.e. the characteristics of a human being (Biometrics). Biometrics is the science of establishing human identity by using physical or behavioural traits such as face, fingerprints, palm prints, iris, hand geometry, ear, and voice. There are some significant works which have been carried out in past few years in the field of ear biometrics. In this survey discusses various technique of ear Detection &amp; Recognition for 2D ear biometric, and provides good future prospects for the upcoming researchers in the field of ear biometric.
Review of Detection & Recognition Techniques for 2D Ear Biometrics System from shritosh kumar
]]> 535 5 https://cdn.slidesharecdn.com/ss_thumbnails/24-05-2015481v2-e6-072-150612055917-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds document 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Ear Biometrics shritosh kumar /slideshow/ear-biometrics-shritosh-kumar/49299628 1-7shritoshkumar-150612055708-lva1-app6891
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.]]>
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.]]> Fri, 12 Jun 2015 05:57:07 GMT /slideshow/ear-biometrics-shritosh-kumar/49299628 shritosh@slideshare.net(shritosh) Ear Biometrics shritosh kumar shritosh ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1-7shritoshkumar-150612055708-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Ear Biometrics shritosh kumar from shritosh kumar
]]> 748 4 https://cdn.slidesharecdn.com/ss_thumbnails/1-7shritoshkumar-150612055708-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-shritosh-48x48.jpg?cb=1522973203 https://cdn.slidesharecdn.com/ss_thumbnails/paper244-150612063554-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/paper244/49300861 Artificial Neural Netw... https://cdn.slidesharecdn.com/ss_thumbnails/a-survey-report-on-cloud-computing-testing-environment-150612062008-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/a-surveyreportoncloudcomputingtestingenvironment/49300236 A survey-report-on-clo... https://cdn.slidesharecdn.com/ss_thumbnails/24-05-2015481v2-e6-072-150612060255-lva1-app6891-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/24-052015481-v2e6072-49299751/49299751 Performance of Gabor M...