Fereshteh Falah Chamasemani

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The paper presents a Multi-class Support Vector Machine classifier and its application to hypothyroid detection and classification. Support Vector Machines (SVM) have been well known method in the machine learning community for binary classification problems. Multi-class SVMs (MCSVM) are usually implemented by combining several binary SVMs. The objective of(More)
Recently, various conferences and journals have published articles related to Video Surveillance Systems, indicating researchers‘ attention. The goal of this review is to examine the latest works were published in journals, propose a new classification framework of video surveillance systems and investigate each aspect of this classification framework. This(More)
The goal of surveillance video abstraction is to generate a video abstract that includes important events and object by eliminating the redundant frames, lacking from activity in original video. Although many research and progresses have been done in video abstraction, the developed approaches either fail to accurately and effectively cover the overall(More)
The huge volume of videos produced by surveillance cameras has increased the demand for the fast and effective video surveillance indexing and retrieval systems. Although environmental condition such as light reflection, illumination changes, shadow, and occlusion can affect the indexing and retrieval result of any video surveillance system, nevertheless(More)
The exponential growth in the number of surveillance videos makes the search and retrieval of their contents an extensive, time-consuming, and tedious task. Video abstraction is a general solution to alleviate this problem by generating a short and concise version of the original video. The existing abstraction approaches have commonly relied on global(More)
In this paper, a baseline phoneme recognition system for Kannada language is built using MFCC and Deep Belief Networks (DBNs). Phonemes are segmented from continuous Kannada speech and MFCC features are extracted from each speech frame. These features are further used as input to the recognizer. DBNs are probabilistic generative model which are constructed(More)
Nowadays, Multimodal biometrics has created a substantial interest in the field of identification management due to higher recognition performance. This paper presents a comparative analysis of different fusion levels like feature level, score level and decision level in multimodal biometrics using fingerprint and face. Histogram of Oriented Gradients (HOG)(More)
The manual search through the surveillance video archives for a specific object or event is very timeconsuming and tedious task due to the large volume of video data captured by many installed surveillance cameras. Therefore, the solution to accelerate and facilitate this process is to design an automatic video surveillance with the efficient and effective(More)
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