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In this paper, the problem of queue in convenient stores is considered. We propose a low cost automatic queue length monitoring system by using an Internet-of-Things (IoT) platform. This system can detect the length of queue and the number of people that enqueue and leave the queue. If the length of queue is critical, the system will alert to staff via LINE Notify. Experimental results indicate that...
This paper proposes the sentiment analysis system in Thai language. It aims to use for the three business types (Retail, Banking and Telecommunication) to monitor their brand image via social media. Pantip.com is the most popular online community in Thailand, which many customers posted the comments about their business. Normally, three sentiments must be identified (positive, negative and neutral),...
Social media is widely used as a channel of communication in general purposes, including the comment that are related to retail business. It is a highly effective communication tool for direct interacting with their customers. Growth rate of the users is rapidly increasing, because they use this channel to receive information and share something interesting. In this paper, we present a comparison...
In survey research, the offline paper-based questionnaire still necessary for data collection. Although the online survey is more convenient, internet system and portable device are needed for operating. That is not practical for some surveys. Furthermore, the paper-based questionnaire requires data entry by human which will take long time and easy to mistake. Therefore, this paper proposes the automated...
Network Security is always a major concern in any organizations. To ensure that the organization network is well prevented from attackers, vulnerability assessment and penetration testing are implemented regularly. However, it is a highly time-consuming procedure to audit and analysis these testing results depending on administrator's expertise. Thus, security professionals prefer proactive-automatic...
We propose a two-phase classification method. Specifically, in the first phase, a set of patterns (data) are clustered by the k-means algorithm. In the second phase, outliers are constructed by a distance-based technique and a class label is assigned to each pattern. The Knowledge Discovery Databases (KDD) Cup 1999 data set, which has been utilized extensively for development of intrusion detection...
Determination of content importance is very important in achieving high quality classification. Term weighting schemes in text classification will be applied to classify videos by measuring importance of video contents. In other words, a video sequence can be treated as a document, and frames of a video are considered as words or terms which identify contents of a video. And to enhance the efficiency...
Generally, the dimension of feature vector in text classification depends on the number of words in the specific domain. Many documents of considered categories make it numerous. Therefore, the dimension of feature vector is very high that makes it consumes a lot of time and memory to process. Moreover, it is a cause of the small sample size problem when the number of available training documents...
Due to the inaccuracy of image registration between each frame of observed sequence, especially in a very complex motion frame, almost Video Super Resolution Reconstruction (SRR) frameworks found in review literatures cannot be worked well to real sequences with arbitrary scene content and/or arbitrary motion. Moreover, the observed system noise is typically assumed to be a Gaussian distribution thus...
Signal of humming sound is the input which is important for the Query-by-Humming system. This input signal which has variable dimension depend on humming time interval will always affect the feature vector. It cannot be used with some classifiers, which require non-variable dimension of feature vector, such as Artificial Neural Network (ANN) or Support Vector Machine (SVM). Especially, SVM is good...
One of the most important issues for measuring video similarity is the difficulty in identifying the optimal frame similarity threshold, which often tends to vary in an unpredictable pattern, and has to be manually determined. Moreover, most video data are huge files, which vary in terms of length and amount of data, resulting in time-consuming data processing. In this paper, we propose video similarity...
In this paper, we propose a new face hallucination using Eigen transformation with error regression model. Normally in the traditional methods, a high-resolution (HR) face image is reconstructed only from low-resolution (LR) face image. Nevertheless, none of these works interested to take advantage of reconstruction error. Therefore, the error information is included in our framework to correct the...
In this paper, the two-dimensional random projection (2DRP) is proposed to directly project the image matrix from high-dimensional space to low-dimensional space for recognition task. In traditional random projection framework, the projection matrix does not depend on the training data hence it can avoid the principal classification problems such as over-fitting, Small Sample Size (SSS), and singularity...
In this paper, we proposed a novel technique for face recognition using Image Cross-Covariance Analysis (ICCA), based on the Two-Dimensional Principal Component Analysis (2DPCA) technique. In conventional 2DPCA, the image covariance matrix is directly calculated via 2D images in matrix form, by concept of the covariance of a random variable. We found that it is not the optimal solution for 2DPCA framework...
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