Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter. Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome ...

In medical Image analysis, the parallel segmentation is the core technology. As one of the classical methods, regional growth algorithms have some problems: it is hard to confirm the feed points automatically. To solve this defect, a new parallel segmentation algorithm with regional growth and support vector machine (SVM) is proposed. SVMs have a good result in segmentation (classification) but...

internet applications spreading and its high usage popularity result insignificant increasing of cyber-attacks. consequently, network security has becomea matter of importance and several methods have been developed for these attacks.for this purpose, intrusion detection systems (ids) are being used to monitor theattacks occurred on computer networks. data mining techniques, machinelearning, ne...

porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. nowadays, using intelligent techniques has become a popular method for porosity estimation. support vector machine (svm) a new intelligent method with a great generalization potential of modeling non-linear relationships has been introduced fo...

segmentation and three‑dimensional (3d) visualization of teeth in dental computerized tomography (ct) images are of dentists’ requirements for both abnormalities diagnosis and the treatments such as dental implant and orthodontic planning. on the other hand, dental ct image segmentation is a difficult process because of the specific characteristics of the tooth’s structure. this paper presents ...

Multiple people detection and tracking is a challenging task in real-world crowded scenes. In this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. We have detected objects with deformable part models and a visual background extractor. In the tracking phase we have used a combination of support vector machine (SVM) person-specific classifie...

The term intelligent systems is spreading beyond the data mining and machine learning communities. This presents new challenges that are fundamental to classical problems within object oriented programming and analysis. In this paper we investigate the use of a popular intelligent algorithm on a Java-based processor. The processor is a realtime enabled processor implemented on an FPGA, and we d...

We describe in this work a Core Generator for Pattern Recognition tasks. This tool is able to generate, according to user requirements, the hardware description of a digital architecture, which implements a Support Vector Machine, one of the current state–of– the–art algorithms for pattern recognition. The output of the Core Generator consists of a high–level language hardware core description,...

We present an algorithm to schedule basic blocks of vector three-address-instructions. This algorithm is suited for a special class of vector processors containing a buuer (register le) which may be partitioned arbitrarily into vector registers by the user. The algorithm computes the best ratio of vector register spilling to strip mining, taking the vector length and the buuer size into conside...