Statistical Method Used for Doing Better Corneal Junction Operation

Rezaeiye, Payam Porkar; Rezaeiye, Pasha Porkar; Karbalayi, Elahe; Gheisari, Mehdi

doi:10.4028/www.scientific.net/amr.548.762

Cited by 7 publications

(4 citation statements)

References 6 publications

(5 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The result is that to map V the classes of i and j that will projection i ≠ j to one cluster high overlapping of classification between the classes that is required to increase the rate of classification error in the projection space. Therefore, from this example, we can conclude that in the estimate of between the class matrixes of Chernoff's criterion all pairs of classes, without being separate in original space are considered that this process leads to a bad performance in separating the classes [35][36][37][38][39][40][41][42][43].…”

Section: Chernoff's Multi-class Criteriamentioning

confidence: 99%

Improve Heteroscedastic Discriminant Analysis by Using CBP Algorithm

Alzubi

Yaghoubi

Gheisari

et al. 2018

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Linear discriminant analysis is considered as current techniques in feature extraction so, LDA, by discriminant information which obtains in mapping space, does the classification act. When the classes' distribution is not normal, LDA, to perform classification, will face problem and will resulted the poor performance of criteria in performing the classification act. One of the proposed ways is the use of other measures, such as Chernoff's distance so, by using Chernoff's measure LDA has been spreading to its heterogeneous states and LDA in this state, in addition to use information among the medians, uses the information of the classes' Covariance matrices. By defining scattering matrix , based on Boundary and non-Boundary samples and using these matrices in Chernoff's criteria, the decrease of the classes' overlapping in the mapping space in as result, the rate of classification correctness increases. Using Boundary and non-Boundary samples in scattering matrices causes improvement over the result. In this article, we use a new discovering multi-stage Algorithm to choose Boundary and non-Boundary samples so, the results of the conducted experiments shows promising performance of the proposing method.

show abstract

Section: Chernoff's Multi-class Criteriamentioning

confidence: 99%

Improve Heteroscedastic Discriminant Analysis by Using CBP Algorithm

Alzubi

Yaghoubi

Gheisari

et al. 2018

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…These types of backgrounds are referred to as background quasi-constants. After removing the shadows, the "particle filter" method has been used to distinguish the moving objects in the image from each other [43], [24] as shown in Figure 1. In an attempt to determine a dynamic object in a video is the background subtraction method.…”

Section: Methodsmentioning

confidence: 99%

A novel enhanced algorithm for efficient human tracking

Gheisari

Majid²,

Almasi³

et al. 2022

IJ-ICT

Self Cite

View full text Add to dashboard Cite

<p><span>Tracking moving objects has been an issue in recent years of computer vision and image processing and human tracking makes it a more significant challenge. This category has various aspects and wide applications, such as autonomous deriving, human-robot interactions, and human movement analysis. One of the issues that have always made tracking algorithms difficult is their interaction with goal recognition methods, the mutable appearance of variable aims, and simultaneous tracking of multiple goals. In this paper, a method with high efficiency and higher accuracy was compared to the previous methods for tracking just objects using imaging with the fixed camera is introduced. The proposed algorithm operates in four steps in such a way as to identify a fixed background and remove noise from that. This background is used to subtract from movable objects. After that, while the image is being filtered, the shadows and noises of the filmed image are removed, and finally, using the bubble routing method, the mobile object will be separated and tracked. Experimental results indicated that the proposed model for detecting and tracking mobile objects works well and can improve the motion and trajectory estimation of objects in terms of speed and accuracy to a desirable level up to in terms of accuracy compared with previous methods.</span></p>

show abstract

“…Hard-coding assumptions about the world in programming-language code makes these assumptions not only hard to find and understand but also hard to change, in particular for someone without programming expertise. In addition, explicit specifications of domain knowledge are useful for new users who must learn what terms in the domain mean [103].…”

Section: B11 Defining the Scopementioning

confidence: 99%

An IoT Approach to Personalised Remote Monitoring and Management of Epilepsy

Mchale

Pereira

Weishmann

et al. 2017

2017 14th International Symposium on Pervasive Systems, Algorithms and Networks &Amp; 2017 11th International Conference on Fro

View full text Add to dashboard Cite

I am grateful to the individuals that participated in the clinical studies described in this thesis. I would like to thank them for their patience, generosity, and courage. Thanks to Dr. Udo Weishmann his mentorship and input while I carried out this project; our initial fortuitous meeting was to make-way for this influential collaboration. Thanks, Udo, for sharing the passion to help epilepsy patients which has motivated us throughout. Thanks to Becky Higginbottom and Amy Ibbotson, and all the Clinical Physiologists' at the Walton Centre for assisting me with patient profile collection and teaching me valuable epilepsy terminology and the methods at the Neurophysiology Department.Thanks to the NRES committee London-Dulwich (HEALTH RESEARCH AUTHORITY) for supporting me in the design of clinical studies, and for helping me with the NHS IRAS (Integrated Research Approval System). Thanks to Dave Watling for making the ethical aspects of the studies at The Walton Centre possible. The App system used in these studies could not have been built without the help of my colleague and fellow PhD researcher Oladotun Omosebi: his determination, positivity and skill will long live in the memory. I am hugely thankful for the input from my supervisory team; Professor

show abstract

Statistical Method Used for Doing Better Corneal Junction Operation

Cited by 7 publications

References 6 publications

Improve Heteroscedastic Discriminant Analysis by Using CBP Algorithm

Improve Heteroscedastic Discriminant Analysis by Using CBP Algorithm

A novel enhanced algorithm for efficient human tracking

An IoT Approach to Personalised Remote Monitoring and Management of Epilepsy

Contact Info

Product

Resources

About