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This paper presents the intruder detection system for rapid transit using CCTV surveillance based on the histogram shapes. In this paper, researchers proposed intruder detection algorithm of yellow line located on the ground next to rapid transit railway for preventing passengers from any harmful train incidents by using CCTV surveillance system based histogram shape that is incredibly convenient...
Face recognition is an automated process with the ability to identify individuals by their facial characteristics. Currently there is a problem in which the process requires several examples of the person of interest's face in order to produce accurate outcome, and the process is intolerant to the variation in facial expression and the condition of lighting of the face image needed to be identify...
An improvement in framework for unseen place categorization using scene text is proposed. Category score calculation using visual saliency weighting method is proposed to cope with problem of different importance of word locations on scene images. Additionally, a HOG feature extraction using sliding window is proposed to obtain better holistic word recognition on scene images. As the result, the proposed...
Collaborative filtering methods are utilized to provide personalized recommendations for users in order to alleviate information overload problem in different domains. Traditional collaborative filtering methods operate on a user-item matrix in which each user reveal her admiration about an item based on a single criterion. However, recent studies indicate that recommender systems depending on multi-criteria...
Particle Swarm Optimization (PSO) is one of many optimization techniques used to find a solution in many areas not limited to engineering or mathematics. It can discover the solution to a problem of finding input to a program based on the similarity of program's execution. However, identifying such solutions with standard PSO is not very efficient or in a few cases, not possible. There is a high probability...
In an ad-hoc social network (ASNET), users normally require scheduling popular data packet first. However, ASNET users have some limitations due to the scarce bandwidth and unreliability in wireless connection. Traditional algorithms use First In First Out (FIFO) order for scheduling, which is not suitable in ASNETs and cannot work properly with congested environments. To overcome the above mentioned...
This paper presents a new method for vehicle logo detection and recognition from images of front and back views of vehicle. The proposed method is a two-stage scheme which combines Convolutional Neural Network (CNN) and Pyramid of Histogram of Gradient (PHOG) features. CNN is applied as the first stage for candidate region detection and recognition of the vehicle logos. Then, PHOG with Support Vector...
Currently, multimedia data has become increasingly more important with the growth of the Internet. Images are one example of sharing across the internet, especially through social media applications. More specifically, nearly every website consists of a considerable amount of image data. Some pictures are stored in multiple resolutions to be displayed as desired. When the same image is stored in different...
Room utilization monitoring system is an interesting application towards optimized facility usage. Due to its cost effectiveness and robustness, a camera-based system for room utilization is focused. This paper presents a multiple camera based process for room utilization monitoring system. The system is composed with three parts of processes that are single-camera processing, multi-camera processing...
Real time monitoring of data streams can be used for monitoring performance, availability or system anomaly detection which can analyze and correlate events from logs file. However, due to the increasing complexity of modern distributed systems, the size of logs can become very large. Monitoring withtiming constraint becomes more important in facilitating the enforcement of conditional guarantees...
Ultrasound (US) breast cancer images is one of the most complicated medical images to extract the desired area of interest. It is often difficult to separate the tumor region from the background tissues. Therefore, tumor segmentation is the challenging problems in the computed aided diagnosis. Among many image segmentation techniques, a generalized gradient vector flow (GGVF) method is one of the...
This paper presents a method to estimate the uncertainty in the calibration of two sensors, a laser rangefinder and a multicamera-system. Both sensors were used in urban environment reconstruction tasks. A new calibration pattern, visible to both sensors is proposed. By this means, correspondence between each laser point and its position in the camera image is obtained so that texture and color of...
In this work, prosodic features of the Turkish Broadcast News (BN) data are extracted using an open source prosodic feature extraction tool based on Praat. The profiles and effectiveness of these features are also investigated for the sentence segmentation task on the Turkish BN data. We not only used some combinations of the feature sets but also collected some of them in one prosodic feature model...
Naturalness is an important issue in the Text-To-Speech (TTS) system. To support arbitrarily defined pitch contours for any synthesized syllables, a TTS should be able to maintain the naturalness of the synthetic speech. This work proposed an automatic evaluation of pitch contours in order to determine the level of naturalness of synthesized syllables when perceived by human listeners. By analyzing...
Automatic generation of narrative sentences from unordered word sets is desirable in Augmentative and Alternative Communication (AAC) systems for children with certain learning disabilities (LD). Regardless of the complexity of the Natural Language Processing deployed in sentence generation procedures, the qualities of language models always affect the generation results. This work compared sentence...
Hierarchical classification has been becoming a popular research topic nowadays, particularly on the web as text categorization. For a large web corpus, there can be a hierarchy with hundreds of thousands of topics, so it is common to handle this task using a flat classification approach, inducing a binary classifier only for the leaf-node classes. However, it always suffers from such low prediction...
In this research, I proposed Emotion Classification of Thai Text based Using Term weighting and Machine Learning Techniques focusing on the comparison of various common term weighting schemes. I found Boolean weighting with Support Vector Machine is most effective in our experiments. I also discovered that the Boolean weighting is suitable for combination with the Information gain feature selection...
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