Neural Nets(NN) have been described as a solution looking for a problem. In the last conference, Artificial InteIligence(A1) was considered in the accelerator context. While good for local surveillance and control, its use for large complex systems(LCS) was much more restricted. By contrast, NN provide a good metaphor for LCS. It can be argued that they are logically equivalent to multi-loop fe...

Identification of affine deformed and simultaneously blur degraded images is an important task in pattern analysis. Use of global moment features has been one of the most popular techniques for pattern recognition and classification. In this paper, we introduce an approach to derive blur and affine combined moment invariants(BACIs). A neural network(NN) model is then employed to classify object...

In recent years, collaborative research between academia and industry has intensified in finding a successful approach to take the information from a computer generated drawings of products such as casting dies, and produce optimal manufacturing process plans. Core to this process is feature recognition. Artificial neural networks have a proven track record in pattern recognition and there abil...

image classification is an issue which utilizes image processing, pattern recognition and classification methods. automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing ...

ABSTRACT: In this paper we present moment invariant and neural network to classify airport pavement distress images. The moment invariant has been extracting images feature that published two-dimensional pattern recognition application method in 1962. The image pattern can be reduced to number of values such that they are description of the translation, scale, and rotation of an object in the i...

In this paper, a new type of neural network model——PARCONE (Partially Connected Neural Evolutionary) was proposed, which can overcome the disadvantage that the previous neural networks can not accept more than thousands of inputs. With this new model, no feature extraction is needed before target identification and all of the pixels of a sample image can be used as the inputs of the neural netw...

A new approach of constructing and training neural networks for pattern classi$cation is proposed. Data clusters are generated and trained sequentially based on distinct local subsets of the training data. Obtained clusters are then used to construct a feed-forward network, which is further trained using standard algorithms operating on the global training set. The network obtained using this a...

bioelectrical signal, which records the heart’s electrical activity versus time, is an electrocardiogram (ECG). It is an important diagnostic tool for assessing heart functions. The interpretation of ECG signal is an application of pattern recognition. signal pre-processing, QRS detection, feature extraction and neural network for signal classification are those techniques which used in this pa...

Optical Character Recognition (OCR) is an area of research that has attracted the interest of researchers for the past forty years. Although the subject has been the center topic for many researchers for years, it remains one of the most challenging and exciting areas in pattern recognition. Since Arabic is one of the most widely used languages in the world, the demand for a robust OCR for this...

This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the pro...