رضا قادری
دانشگاه شهید بهشتی - دانشکده مهندسی هسته‌ای
[ 1 ] - قطعه‌بندی تصویر مبتنی بر برش نرمالیزه گراف از دیدگاه میزان اطلاعات جداکننده
قطعه‌بندی تصویر، یک مسئله پایه در بینایی ماشین است. در روش مبتنی بر برش نرمالیزه گراف (Ncut)، حل این مسئله به انتخاب بردار ویژه متناظر با دومین کوچک‌ترین مقدار ویژه یک ماتریس خاص می‌انجامد. در این مقاله، ضمن بیان هم‌ارزی رابطه ریاضی حاکم بر مسئله بدون مربیِ Ncut با معیار Fisher-Rao در طبقه‌بندیِ با مربی، از نگاهی نو به مسئله انتخاب بردار ویژه پرداخته شده است. در این مقاله با پیشنهاد معیاری کـارا ...
[ 2 ] - REGION MERGING STRATEGY FOR BRAIN MRI SEGMENTATION USING DEMPSTER-SHAFER THEORY
Detection of brain tissues using magnetic resonance imaging (MRI) is an active and challenging research area in computational neuroscience. Brain MRI artifacts lead to an uncertainty in pixel values. Therefore, brain MRI segmentation is a complicated concern which is tackled by a novel data fusion approach. The proposed algorithm has two main steps. In the first step the brain MRI is divided to...
[ 3 ] - Face Recognition using an Affine Sparse Coding approach
Sparse coding is an unsupervised method which learns a set of over-complete bases to represent data such as image and video. Sparse coding has increasing attraction for image classification applications in recent years. But in the cases where we have some similar images from different classes, such as face recognition applications, different images may be classified into the same class, and hen...
[ 4 ] - Determination of Fiber Direction in High Angular Resolution Diffusion Images using Spherical Harmonics Functions and Wiener Filter
Diffusion tensor imaging (DTI) MRI is a noninvasive imaging method of the cerebral tissues whose fibers directions are not evaluated correctly in the regions of the crossing fibers. For the same reason the high angular resolution diffusion images (HARDI) are used for estimation of the fiber direction in each voxel. One of the main methods to specify the direction of fibers is usage of the spher...
[ 5 ] - Perfect Tracking of Supercavitating Non-minimum Phase Vehicles Using a New Robust and Adaptive Parameter-optimal Iterative Learning Control
In this manuscript, a new method is proposed to provide a perfect tracking of the supercavitation system based on a new two-state model. The tracking of the pitch rate and angle of attack for fin and cavitator input is of the aim. The pitch rate of the supercavitation with respect to fin angle is found as a non-minimum phase behavior. This effect reduces the speed of command pitch rate. Control...
[ 6 ] - Classification of EEG-based motor imagery BCI by using ECOC
AbstractAccuracy in identifying the subjects’ intentions for moving their different limbs from EEG signals is regarded as an important factor in the studies related to BCI. In fact, the complexity of motor-imagination and low amount of signal-to-noise ratio for EEG signal makes this identification as a difficult task. In order to overcome these complexities, many techniques such as variou...