A crucial task in hyperspectral image(HSI)taxonomy is exploring effective methodologies to effusively practice the 3-D and spectral data delivered by the statistics cube.For classification of images,3-D data is adjudg...A crucial task in hyperspectral image(HSI)taxonomy is exploring effective methodologies to effusively practice the 3-D and spectral data delivered by the statistics cube.For classification of images,3-D data is adjudged in the phases of pre-cataloging,an assortment of a sample,classifiers,post-cataloging,and accurateness estimation.Lastly,a viewpoint on imminent examination directions for proceeding 3-D and spectral approaches is untaken.In topical years,sparse representation is acknowledged as a dominant classification tool to effectually labels deviating difficulties and extensively exploited in several imagery dispensation errands.Encouraged by those efficacious solicitations,sparse representation(SR)has likewise been presented to categorize HSI’s and validated virtuous enactment.This research paper offers an overview of the literature on the classification of HSI technology and its applications.This assessment is centered on a methodical review of SR and support vector machine(SVM)grounded HSI taxonomy works and equates numerous approaches for this matter.We form an outline that splits the equivalent mechanisms into spectral aspects of systems,and spectral–spatial feature networks to methodically analyze the contemporary accomplishments in HSI taxonomy.Furthermore,cogitating the datum that accessible training illustrations in the remote distinguishing arena are generally appropriate restricted besides training neural networks(NNs)to necessitate an enormous integer of illustrations,we comprise certain approaches to increase taxonomy enactment,which can deliver certain strategies for imminent learnings on this issue.Lastly,numerous illustrative neural learning-centered taxonomy approaches are piloted on physical HSI’s in our experimentations.展开更多
Securing large amounts of electronic medical records stored in different forms and in many locations, while making availability to authorized users is considered as a great challenge. Maintaining protection and privac...Securing large amounts of electronic medical records stored in different forms and in many locations, while making availability to authorized users is considered as a great challenge. Maintaining protection and privacy of personal information is a strong motivation in the development of security policies. It is critical for health care organizations to access, analyze, and ensure security policies to meet the challenge and to develop the necessary policies to ensure the security of medical information. The problem, then, is how we can maintain the availability of the electronic medical records and at the same time maintain the privacy of patients’ information. This paper will propose a novel architecture model for the Electronic Medical Record (EMR), in which useful statistical medical records will be available to the interested parties while maintaining the privacy of patients’ information.展开更多
文摘A crucial task in hyperspectral image(HSI)taxonomy is exploring effective methodologies to effusively practice the 3-D and spectral data delivered by the statistics cube.For classification of images,3-D data is adjudged in the phases of pre-cataloging,an assortment of a sample,classifiers,post-cataloging,and accurateness estimation.Lastly,a viewpoint on imminent examination directions for proceeding 3-D and spectral approaches is untaken.In topical years,sparse representation is acknowledged as a dominant classification tool to effectually labels deviating difficulties and extensively exploited in several imagery dispensation errands.Encouraged by those efficacious solicitations,sparse representation(SR)has likewise been presented to categorize HSI’s and validated virtuous enactment.This research paper offers an overview of the literature on the classification of HSI technology and its applications.This assessment is centered on a methodical review of SR and support vector machine(SVM)grounded HSI taxonomy works and equates numerous approaches for this matter.We form an outline that splits the equivalent mechanisms into spectral aspects of systems,and spectral–spatial feature networks to methodically analyze the contemporary accomplishments in HSI taxonomy.Furthermore,cogitating the datum that accessible training illustrations in the remote distinguishing arena are generally appropriate restricted besides training neural networks(NNs)to necessitate an enormous integer of illustrations,we comprise certain approaches to increase taxonomy enactment,which can deliver certain strategies for imminent learnings on this issue.Lastly,numerous illustrative neural learning-centered taxonomy approaches are piloted on physical HSI’s in our experimentations.
文摘Securing large amounts of electronic medical records stored in different forms and in many locations, while making availability to authorized users is considered as a great challenge. Maintaining protection and privacy of personal information is a strong motivation in the development of security policies. It is critical for health care organizations to access, analyze, and ensure security policies to meet the challenge and to develop the necessary policies to ensure the security of medical information. The problem, then, is how we can maintain the availability of the electronic medical records and at the same time maintain the privacy of patients’ information. This paper will propose a novel architecture model for the Electronic Medical Record (EMR), in which useful statistical medical records will be available to the interested parties while maintaining the privacy of patients’ information.
