License plate recognition (LPR) is a technology for the authentication of a vehicle by locating and recognizing the license plate number in an image through computer vision techniques and machinelearning models. To d...
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ISBN:
(纸本)9781728107882
License plate recognition (LPR) is a technology for the authentication of a vehicle by locating and recognizing the license plate number in an image through computer vision techniques and machinelearning models. To develop intelligent traffic management such as vehicle monitoring, LPR is a key component. However, due to the diversity of layouts and characters of plates, universal solution is not possible. So, this research focuses on development of an algorithm for the recognition of license plate of Bangladesh by using image processing's and machinelearning model. This algorithm executes in three steps: detection of the plate with shape verification, tilt correction and recognition of the number. For detection, RGB color space, median filtering, binarization, morphological analysis, region properties for filtering are applied. To discard noisy object, shape verification is done through robust distances to borders vectors. Before character segmentation, horizontal tilt correction is applied. Then, characters are extracted by using bounding box parameters from the extracted plate. Finally, the recognition is implemented by using the blending of Histogram Oriented Gradient (HOG) and Local Binary pattern (LBP) features and adaptive boosting (Adaboost) classifier is used to categorize the characters. The proposed algorithm is simulated on the images which are captured from different roads of Bangladesh. The experimental result shows that the detection and recognition accuracy is noteworthy.
These papers on Intelligent data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of discipl...
ISBN:
(数字)9789400772939
ISBN:
(纸本)9789400772922;9789400772939
These papers on Intelligent data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machinelearning, neural nets, fuzzy logic, statistical patternrecognition, knowledge filtering, and post-processing, etc.
Detecting, recognizing and modelling patterns of observed examinee behaviors during assessment is a topic of great interest for the educational research community. In this paper we investigate the perspectives of proc...
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ISBN:
(纸本)9783319394831;9783319394824
Detecting, recognizing and modelling patterns of observed examinee behaviors during assessment is a topic of great interest for the educational research community. In this paper we investigate the perspectives of process-centric inference of guessing behavior patterns. The underlying idea is to extract knowledge from real processes (i.e., not assumed nor truncated), logged automatically by the assessment environment. We applied a three-step process mining methodology on logged interaction traces from a case study with 259 undergraduate university students. The analysis revealed sequences of interactions in which low goal-orientation students answered quickly and correctly on difficult items, without reviewing them, while they submitted wrong answers on easier items. We assumed that this implies guessing behavior. From the conformance checking and performance analysis we found that the fitness of our process model is almost 85 %. Hence, initial results are encouraging towards modelling guessing behavior. Potential implications and future work plans are also discussed.
During our work, we developed Automatic recognition system of emotions expressed through the face. This system will be adapted to judicial police interrogation or interviews simulation. This system is based on a funct...
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ISBN:
(纸本)9781728135786
During our work, we developed Automatic recognition system of emotions expressed through the face. This system will be adapted to judicial police interrogation or interviews simulation. This system is based on a functional division: detection and follow-up the face, acquisition of facial expressions starting from video images sequences, and finally, characteristics extraction and emotions expressed recognition. The deep convolution network model is formed primarily on FER2013. It is used to train and validate the model. We use OpenCV library and its implementation of the Viola and Jones algorithm for face detection.
The diabetes is one of lethal diseases in the world. It is additional a inventor of various varieties of disorders foe example: coronary failure, blindness, urinary organ diseases etc. In such case the patient is requ...
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ISBN:
(纸本)9781538678084
The diabetes is one of lethal diseases in the world. It is additional a inventor of various varieties of disorders foe example: coronary failure, blindness, urinary organ diseases etc. In such case the patient is required to visit a diagnostic center, to get their reports after consultation. Due to every time they have to invest their time and currency. But with the growth of machinelearning methods we have got the flexibility to search out an answer to the current issue, we have got advanced system mistreatment information processing that has the ability to forecast whether the patient has polygenic illness or not. Furthermore, forecasting the sickness initially ends up in providing the patients before it begins vital. Information withdrawal has the flexibility to remove unseen data from a large quantity of diabetes associated information. The aim of this analysis is to develop a system which might predict the diabetic risk level of a patient with a better accuracy. Model development is based on categorization methods as Decision Tree, ANN, Naive Bayes and SVM algorithms. For Decision Tree, the models give precisions of 85% for Naive Bayes 77% and 77.3% for Support Vector machine. Outcomes show a significant accuracy of the methods.
The citrus greening infection detection algorithm is performed via computer vision techniques and deep learning for the purpose of extracting sub-images of fruit from a tree image and using a trained machinelearning ...
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ISBN:
(纸本)9781450366359
The citrus greening infection detection algorithm is performed via computer vision techniques and deep learning for the purpose of extracting sub-images of fruit from a tree image and using a trained machinelearning function to determine if the fruit shows signs of a citrus greening infection disease called Huanglongbing. We trained our deep learning inception model with 4000 iterations and achieved validation accuracy 93.3%. The computer vision fruit sub-image extraction resulted in at worst around 80% accuracy in tree images and was manually calibrated to detect a specific range of orange color values.
Traditional English teaching evaluation has problems such as subjectivity, limitations, quantitative bias, and lacks feedback and support. The evaluation algorithm based on data analysis technology provides an accurat...
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Based on the text data of authoritative skin care community, this study analyzes the user's needs and summarizes six topics on the premise that it has the option of repurchase intention. We need to calculate the e...
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The paper presents the application of multidimensional data visualization to obtain the views of 5-dimensional space of features created by recognition of printed characters. On the basis of these views it was stated ...
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ISBN:
(纸本)9783319023090
The paper presents the application of multidimensional data visualization to obtain the views of 5-dimensional space of features created by recognition of printed characters. On the basis of these views it was stated that the features chosen to construction of features space are sufficient to correct recognition process. This is the significant help by constructing the recognition systems because the correct selection of objects properties on the basis of which the recognition should occur is one of the hardest stages.
This paper contains a brief description of a new computer programming tool for supervised machinelearning, designed to generate production rules from data. The research tool described - named NGTS - was used for pred...
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ISBN:
(纸本)9781424475629
This paper contains a brief description of a new computer programming tool for supervised machinelearning, designed to generate production rules from data. The research tool described - named NGTS - was used for prediction of the Glasgow Outcome Scale and Rankin Scale for patients affected by severe brain damage.
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