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Full-Text Articles in Systems and Communications
Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj
Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj
Electrical & Computer Engineering Faculty Research
The manual interpretation of MRI slices based on visual examination by radiologist/physician may lead to missing diagnosis when a large number of MRIs are analyzed. To avoid the human error, an automated intelligent classification system is proposed. This research paper proposes an intelligent classification technique to the problem of classifying four types of brain abnormalities viz. Metastases, Meningiomas, Gliomas, and Astrocytomas. The abnormalities are classified based on Two/Three/ Four class classification using statistical and textural features. In this work, classification techniques based on Least Squares Support Vector Machine (LS-SVM) using textural features computed from the MR images of patient are …
Efficient Scheduling For Sdmg Cioq Switches, Mei Yang, S. Q. Zheng
Efficient Scheduling For Sdmg Cioq Switches, Mei Yang, S. Q. Zheng
Electrical & Computer Engineering Faculty Research
Combined input and output queuing (CIOQ) switches are being considered as high-performance switch architectures due to their ability to achieve 100% throughput and perfectly emulate output queuing (OQ) switch performance with a small speedup factor S. To realize a speedup factor S, a conventional CIOQ switch requires the switching fabric and memories to operate S times faster than the line rate. In this paper, we propose to use a CIOQ switch with space-division multiplexing expansion and grouped input/output ports (SDMG CIOQ switch for short) to realize speedup while only requiring the switching fabric and memories to operate at the line …