Taiebeh Askari - Academia.edu (original) (raw)

Papers by Taiebeh Askari

Research paper thumbnail of Reぼけ過程に基づく正則化を用いた非ブラインド画像デコンボリューション【Powered by NICT】

Computer Vision and Image Understanding, 2017

Research paper thumbnail of A Decision Support System For Parkinsons Disease Diagnosis Using Classification And Regression Tree

Journal of Mathematics and Computer Science, Feb 29, 2012

Parkinson's disease (PD) is a progressive disorder of the nervous system that affects movement. I... more Parkinson's disease (PD) is a progressive disorder of the nervous system that affects movement. It develops gradually, often starting with a barely noticeable tremor in just one hand. But while tremor may be the most well-known sign of Parkinson's disease, the disorder also commonly causes a slowing or freezing of movement. Parkinson's disease is the second most common Neurodegenerative action only surpassed by Alzheimer's disease. However, a proper diagnosis at an early stage can result in significant life saving. A system for automated medical diagnosis would enhance the accuracy of the diagnosis and reduce the cost effects. The present study compares the accuracy of several machine learning methods including Bayesian Networks, Regression, Classification and Regression Trees (CART), Support Vector Machines (SVM), and Artificial Neural Networks (ANN) for proposing a decision support system for diagnosis of parkinson's disease. The proposed system achieved an accuracy of 93.7% using classification and regression tree. Sensitivity analysis via classification and regression tree was also used to find importance of input variables.

Research paper thumbnail of Implementation Of A System For 3d Face Detection And Recognition

Journal of Mathematics and Computer Science

This paper provides a method for detection and recognition face of man using 3D face extracting a... more This paper provides a method for detection and recognition face of man using 3D face extracting and applying 3D features. In this paper, it is used from the Bio-ID package contained 1520 images of man face. A number of these images were used for 2D face modeling; another number was used for 3D face modeling, and another number was used for test. At first, the landmarks on the face image are determined, semi automatically. Then the shape, texture and appearance model of face images is constructed. Using these models and the fast Active Appearance Model search, the landmarks on the test image are determined. More ever, from 24 3D images, obtained by a 3D scanner, the variations of shape, texture and appearance are modeled. Using the 3D models, 2D landmarks and an 3D Initialized Active Appearance Model Search method (3D IAAMS), the 3D frame of face (this frame is described by 3D landmarks) in an image is constructed. These 3D frames with the texture are used for face recognition.

Research paper thumbnail of Implementation Of A System For 3d Face Detection And Recognition

This paper provides a method for detection and recognition face of man using 3D face extracting a... more This paper provides a method for detection and recognition face of man using 3D face extracting and applying 3D features. In this paper, it is used from the Bio-ID package contained 1520 images of man face. A number of these images were used for 2D face modeling; another number was used for 3D face modeling, and another number was used for test. At first, the landmarks on the face image are determined, semi automatically. Then the shape, texture and appearance model of face images is constructed. Using these models and the fast Active Appearance Model search, the landmarks on the test image are determined. More ever, from 24 3D images, obtained by a 3D scanner, the variations of shape, texture and appearance are modeled. Using the 3D models, 2D landmarks and an 3D Initialized Active Appearance Model Search method (3D IAAMS), the 3D frame of face (this frame is described by 3D landmarks) in an image is constructed. These 3D frames with the texture are used for face recognition.

Research paper thumbnail of Reぼけ過程に基づく正則化を用いた非ブラインド画像デコンボリューション【Powered by NICT】

Computer Vision and Image Understanding, 2017

Research paper thumbnail of A Decision Support System For Parkinsons Disease Diagnosis Using Classification And Regression Tree

Journal of Mathematics and Computer Science, Feb 29, 2012

Parkinson's disease (PD) is a progressive disorder of the nervous system that affects movement. I... more Parkinson's disease (PD) is a progressive disorder of the nervous system that affects movement. It develops gradually, often starting with a barely noticeable tremor in just one hand. But while tremor may be the most well-known sign of Parkinson's disease, the disorder also commonly causes a slowing or freezing of movement. Parkinson's disease is the second most common Neurodegenerative action only surpassed by Alzheimer's disease. However, a proper diagnosis at an early stage can result in significant life saving. A system for automated medical diagnosis would enhance the accuracy of the diagnosis and reduce the cost effects. The present study compares the accuracy of several machine learning methods including Bayesian Networks, Regression, Classification and Regression Trees (CART), Support Vector Machines (SVM), and Artificial Neural Networks (ANN) for proposing a decision support system for diagnosis of parkinson's disease. The proposed system achieved an accuracy of 93.7% using classification and regression tree. Sensitivity analysis via classification and regression tree was also used to find importance of input variables.

Research paper thumbnail of Implementation Of A System For 3d Face Detection And Recognition

Journal of Mathematics and Computer Science

This paper provides a method for detection and recognition face of man using 3D face extracting a... more This paper provides a method for detection and recognition face of man using 3D face extracting and applying 3D features. In this paper, it is used from the Bio-ID package contained 1520 images of man face. A number of these images were used for 2D face modeling; another number was used for 3D face modeling, and another number was used for test. At first, the landmarks on the face image are determined, semi automatically. Then the shape, texture and appearance model of face images is constructed. Using these models and the fast Active Appearance Model search, the landmarks on the test image are determined. More ever, from 24 3D images, obtained by a 3D scanner, the variations of shape, texture and appearance are modeled. Using the 3D models, 2D landmarks and an 3D Initialized Active Appearance Model Search method (3D IAAMS), the 3D frame of face (this frame is described by 3D landmarks) in an image is constructed. These 3D frames with the texture are used for face recognition.

Research paper thumbnail of Implementation Of A System For 3d Face Detection And Recognition

This paper provides a method for detection and recognition face of man using 3D face extracting a... more This paper provides a method for detection and recognition face of man using 3D face extracting and applying 3D features. In this paper, it is used from the Bio-ID package contained 1520 images of man face. A number of these images were used for 2D face modeling; another number was used for 3D face modeling, and another number was used for test. At first, the landmarks on the face image are determined, semi automatically. Then the shape, texture and appearance model of face images is constructed. Using these models and the fast Active Appearance Model search, the landmarks on the test image are determined. More ever, from 24 3D images, obtained by a 3D scanner, the variations of shape, texture and appearance are modeled. Using the 3D models, 2D landmarks and an 3D Initialized Active Appearance Model Search method (3D IAAMS), the 3D frame of face (this frame is described by 3D landmarks) in an image is constructed. These 3D frames with the texture are used for face recognition.