One aspect of constructing secure networks is identifying unauthorized use of those networks. Intrusion Detection systems look for unusual or suspicious activity, such as pattems of network trafic that are likely indicators of unauthorized activity. However, normal operation often produces trafic that matches likely “attack signatures”, resulting in false alarms. We are using data mining techni...

One aspect of constructing secure networks is identifying unauthorized use of those networks. Intrusion Detection systems look for unusual or suspicious activity, such as pattems of network trafic that are likely indicators of unauthorized activity. However, normal operation often produces trafic that matches likely “attack signatures”, resulting in false alarms. We are using data mining techni...

Traffic sign recognition is an important and active research topic of intelligent transport system. With a constant increasing of the training database size, not only the recognition accuracy, but also the computation complexity should be considered in designing a feasible recognition approach. In this paper, an effective and efficient algorithm based on a relatively new artificial neural netwo...

-This paper proposes a multi-classified and self-directed learning method used for sign language recognition, which adopts statistical template matching methods to recognize sign language. As sign language expressions consist of many frames, SIFT algorithm is used to position key frames and eigenvectors of sign language vocabulary. According to these key frames, the hierarchical discriminate re...

The sign language recognition is the most popular research area involving computer vision, pattern recognition and image processing. It enhances communication capabilities of the mute person. In this paper, I present an object based key frame selection. Forward Algorithm is used for shape similarity for one and two handed gesture recognition. That recognition is with feature and without feature...

The recognition of human activities from video sequences is currently one of the most active areas of research because of its many applications in video surveillance, multimedia communications, medical diagnosis, forensic research and sign language recognition. The work described in this paper describes a new method designed to precisely identify human gestures for Sign Language recognition. Th...

Several types of network trafic have been shown to exhibit long-range dependence (LRD). In this work, we show that the busy period of an ATM system driven by a long-range dependent process can be very large. We introduce a new trafjic model based on a fractional Brownian motion envelope process. We show that this characterization can be used to predict queueing dynamics. Furthermore, we derive ...

Traffic sign recognition plays an important role in intelligent transportation systems. Motivated by the recent success of deep learning in the application of traffic sign recognition, we present a shallow network architecture based on convolutional neural networks (CNNs). The network consists of only three convolutional layers for feature extraction, and it learns in a backward optimization wa...

Indian Sign Language (ISL) or Indo-Pakistani Sign Language is possibly the prevalent sign language variety in South Asia used by at least several hundred deaf signers. It is different in the phonetics, grammar and syntax from other country’s sign languages. Since ISL got standardized only recently, there is very little research work that has happened in ISL recognition. Considering the challeng...

This paper presents a Chinese sign language dialog system (CSLDS) based on the technique of large vocabulary continuous Chinese sign language recognition (CSLR) and Chinese sign language synthesis (CSLS). This system can show the advance technology on gesture recognition and synthesis well and can apply to more powerful system combined with speech recognition and synthesis technology, which the...