Trim5 TAKes on Pattern Recognition

Hands-On Pattern Recognition

We organized a series of challenge for the conferences IJCNN/WCCI 2006, NIPS 2006 and IJCNN 2007 to explore various aspects of machine learning, ranging from the choice of data representation to the selection of the best model. The class of problems addressed are classification problems encountered in pattern recognition (classification of images, speech recognition), medical diagnosis, marketi...

A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures

We propose a winner-takes-all (WTA) classifier for structures represented by graphs. WTA classification follows the principle elimination of competition. The input structure is assigned to the class corresponding to the winner of the competition. In experiments we investigate the performance of the WTA classifier and compare it with the canonical maximum similarity (MS) classifier.

pattern recognition in maintenance data using methodologies data minitng (cade study isfahan regional power electric company)

فعالیت های نگهداری و تعمیرات اطلاعاتی را تولید می کند که می تواند در تعیین زمان های بیکاری و ارایه یک برنامه زمان بندی شده یا تعیین هشدارهای خرابی به پرسنل نگهداری و تعمیرات کمک کند. وقتی که مقدار داده های تولید شده زیاد باشند، فهم بین متغیرها بسیار مشکل می شوند. این پایان نامه به کاربردی از داده کاوی برای کاوش پایگاه های داده چندبعدی در حوزه نگهداری و تعمیرات، برای پیدا کردن خرابی هایی که موجب...

Pattern Recognition

Pattern Recognition

Closely related to the concept of Machine Learning, Pattern Recognition is the assignment of an output value, termed a label, to a given input value, termed an instance. This is achieved through the application of an algorithm, which usually falls into one of two general categories (although mixed techniques are beginning to be developed): supervised (requires a training set), and unsupervised,...