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Bangladeshi License Plate recognition Using Adaboost Classifier 8

Bangladeshi License Plate Recognition Using Adaboost Classif...

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Joint 8th international conference on Informatics, Electronics and Vision (ICIEV) / 3rd international conference on Imaging, Vision and pattern recognition (icIVPR) / international conference on Activity and Behavior computing (ABC)

作者： Dhar, Prashengit Abedin, Md Zainal Karim, Razuan Fatema-Tuj-Johora Hossain, Mohammad Shahadat Univ Sci & Technol Chittagong Dept Comp Sci & Engn Chattogram Bangladesh Univ Chittagong Dept Comp Sci & Engn Chittagong 4331 Bangladesh

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 machine learning 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 machine learning 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.

关键词： License Plate recognition (LPR) RGB Color Model Distance to Borders (DtBs) Character Segmentation HOG (Histogram of Oriented Gradient) Local Binary pattern (LBP) Adaboost

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A Systematic Literature Review of the Mobile Application for Object recognition for Visually Impaired People 8

A Systematic Literature Review of the Mobile Application for...

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8th international conference on Information Technology and Multimedia, ICIMU 2020

作者： Nor Hisham, Zulfadhlina Amira Faudzi, Masyura Ahmad Ghapar, Azimah Abdul Rahim, Fiza Abdul College of Computing and Informatics Universiti Tenaga Nasional Department of Informatics Malaysia

ISBN: (纸本)9781728173108

Nowadays, mobile applications or also known as mobile apps are one of the most important sources of communication and gives a lot of benefits to a person. Mobile technology advancements have brought an excessive change in people's daily lifestyles which has led to high demand for developing software that can give benefit to a person that runs on a mobile device. Mobile apps are represented visually on a smartphone, which it is not user-friendly for visually impaired people. the number of visually impaired people are growing in each of the countries in the world. Most technologies are being developed to help people with visual impairment because they still have difficulties in using assistive technologies. this systematic literature review attempts to provide findings on the project for visually impaired people to recognize objects using their smartphones. Systematic Literature Review (SLR) method was used to collect and review the current state of analysis concerning object recognition for visually impaired people on mobile platforms. Overall, this research covered articles published in three databases which are ScienceDirect, IEEE Xplore and Google Scholar and the articles selected are between 2013 until 2019. this paper is based on the Kitchenham methodology where the keyword search and exclusion criteria to select the articles about the topic were used. After reading the total of 371 titles of articles based on keywords, 323 abstracts were examined thoroughly. then, 21 full-text articles were chosen for the final review. the findings show the techniques, tools used and methods on how the system was implemented to recognize object. © 2020 IEEE.

关键词： Object recognition

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Accelerated Algorithm for Computation of All Prime patterns in Logical Analysis of Data 8th

Accelerated Algorithm for Computation of All Prime Patterns ...

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8th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Chambon, Arthur Lardeux, Frederic Saubion, Frederic Boureau, Tristan Univ Angers LERIA Angers France Univ Angers UMR1345 IRHS Angers France

ISBN: (纸本)9789897583513

the analysis of groups of binary data can be achieved by logical based approaches. these approaches identify subsets of relevant Boolean variables to characterize observations and may help the user to better understand their properties. In logical analysis of data, given two groups of data, patterns of Boolean values are used to discriminate observations in these groups. In this work, our purpose is to highlight that different techniques may be used to compute these patterns. We present a new approach to compute prime patterns that do not provide redundant information. Experiments are conducted on real biological data.

关键词： Logical Analysis of Data pattern Generation Logical Characterization of Data

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End-to-End Speech recognition Models for a Low-Resourced Indonesian Language 8

End-to-End Speech Recognition Models for a Low-Resourced Ind...

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8th international conference on Information and Communication Technology, ICoICT 2020

作者： Suyanto, Suyanto Arifianto, Anditya Sirwan, Anis Rizaendra, Angga P. Telkom University School of Computing Bandung Indonesia PT Telekomunikasi Indonesia Advanced Tech. Business Research Divisi Digital Service Bandung Indonesia PT. Telkom Akses Mechanic Electronics Divisi IT Jakarta Indonesia

ISBN: (纸本)9781728161426

Recent automatic speech recognition (ASR) is commonly developed using deep learning (DL), instead of the Hidden Markov Model (HMM). Many researchers show that DL is much better than HMM in noisy environments. However, DL needs a huge speech corpus but does not require any dictionary as well as the concept of either phonemes or syllables. Many DL-based tools are developed and claimed as a language-independent ASR, such as Mozma DeepSpeech (MDS) and Kaituoxu SpeechTransformer (KST). Both MDS and KST are classified as End-to-End ASR (E2EASR), but MDS uses a Recurrent Neural Network (RNN) while KST exploits a Transformer Network. In this paper, two Indonesian ASR (INASR) are developed using both MDS and KST to see their performances to handle a low-resourced language. Evaluation using a small speech corpus of Bahasa Indonesia containing 40 k utterances shows that KST is slightly better than MDS, where it gives a word error rate (WER) of 22.00% while MDS produces a WER of 23.10%. © 2020 IEEE.

关键词： Hidden Markov models

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Emotion Estimation Using Body Expression Types Based on LMA and Sensitivity Analysis 8

Emotion Estimation Using Body Expression Types Based on LMA ...

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作者： Ono, Yuki Aoyagi, Saizo Yamazaki, Yoichi Yamamoto, Michiya Nagata, Noriko Kwansei Gakuin Univ Sch Sci & Technol Sanda Hyogo 6691337 Japan Toyo Univ Fac Informat Networking Innovat & Design Kita Ku Tokyo 1150053 Japan

ISBN: (纸本)9781728107882

the authors have been working on methods of estimating emotions from spontaneous body movements during a collaborative fabrication task. In this study, the authors propose a novel method of grouping emotional expressions on the basis of body movements to create type-specific emotion estimation models. We assume that there are typical expression types that are idiosyncratic characteristics for each person. We propose a method of grouping people by expression types using body movements only, based on Laban Movement Analysis (LMA) and the concept of sensitivity analysis. We perform an experiment to measure body movements and emotions during a fabrication task. Finally, we evaluate the accuracy of estimation and type-specific estimation models. the accuracy was, on average, 67.92%, which was 18% higher than that of person-independent models and superior to existing studies.

关键词： emotion recognition affective computing

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Bibliometric analysis of smart logistics research based on citespace: From 2010 to 2019 8

Bibliometric analysis of smart logistics research based on c...

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8th international Symposium on Project Management, ISPM 2020

作者： Yang, Nan Xia, Meimei School of Economics and Management Beijing Jiaotong University Beijing China

ISBN: (纸本)9781921712722

Smart logistics refers to the new industrial situation based on the Internet of things, big data, cloud computing and other new generation information technologies. Since the concept of smart logistics was put forward in 2009, it has aroused great concern from scholars in various fields. Based on the sample data of academic papers on the theme of "smart logistics" in China national knowledge infrastructure(CNKI) database from 2010 to 2019, this paper used the bibliometric analysis method to assess the current state and explore the development trends of smart logistics domain. We displayed the visualization network from the aspects of literature quantity, core authors, research institutions, keyword co-occurance and keyword clustering, etc. the results show that the research on smart logistics are becoming increasingly concerned and the research results are remarkable;the cooperation among authors or institutions are not close enough and should be strengthened in the future. Research hot topics include smart logistics, Internet of things, logistics industry reform and enterprise innovation, artificial intelligence and Logistics big data, etc. the research trend is toward smart logistics theory innovation research, artificial intelligence technology practice and application, enterprise transformation and upgrading, talent training and other directions. © 8th international Symposium on Project Management, ISPM 2020. All rights reserved.

关键词： Internet of things

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SOCRatES: A Database of Realistic Data for SOurce Camera recognition on Smartphones 8th

SOCRatES: A Database of Realistic Data for SOurce Camera REc...

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8th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Galdi, Chiara Hartung, Frank Dugelay, Jean-Luc EURECOM Dept Digital Secur 450 Route Chappes F-06410 Biot France FH Aachen Dept Multimedia Technol Eupener Str 70 D-52066 Aachen Germany

ISBN: (纸本)9789897583513

SOCRatES: SOurce Camera recognition on Smartphones, is an image and video database especially designed for source digital camera recognition on smartphones. It answers to two specific needs, the need of wider pools of data for the developing and benchmarking of image forensic techniques, and the need to move the application of these techniques on smartphones, since, nowadays, they are the most employed devices for image capturing and video recording. What makes SOCRatES different from all previous published databases is that it is collected by the smartphone owners themselves, introducing a great heterogeneity and realness in the data. SOCRatES is currently made up of about 9.700 images and 1000 videos captured with 103 different smartphones of 15 different makes and about 60 different models. With 103 different devices, SOCRatES is the database for source digital camera identification that includes the highest number of different sensors. In this paper we describe SOCRatES and we present a baseline assessment based on the Sensor pattern Noise computation.

关键词： Sensor pattern Noise PRNU Source Camera Identification Video Smartphone Database

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Real-time pattern recognition for Hand Gesture Based on ANN and Surface EMG 8

Real-time Pattern Recognition for Hand Gesture Based on ANN ...

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IEEE 8th Joint international Information Technology and Artificial Intelligence conference (ITAIC)

作者： Yang, Kuo Zhang, Zhen Shanghai Univ Shanghai Sch Mechatron Engn & Automat Shanghai Peoples R China

ISBN: (纸本)9781538681787

Hand gesture recognition has many applications in engineering and medical fields. this paper proposes a real-time hand gesture recognition method using the surface electromyographic (sEMG) signal on the forearm, we apply a sliding window which allow us to observe a segment of the signals. Features are extracted from the signals of each sliding window, and then are inputted into a feed-forward artificial neural network (ANN) classifier which is trained at first. When the number of one hand gesture type of identified features reaches the threshold, it would be considered that the hand gesture is identified. Experiments show that the classification accuracy of real-time systems reaches 96%, and hand gestures can be recognized before they are completed.

关键词： real-time ANN feature extraction hand gesture recognition sEMG

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A New Distance Measure Between Atanassov’s Intuitionistic Fuzzy Sets Based on Mapping 15th

A New Distance Measure Between Atanassov’s Intuitionistic F...

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15th international conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th international conference on Harmony Search, Soft computing and Applications, ICHSA 2019

作者： Su, Fang Li, Jing Xiao, Dongxuan Duan, Chengrui School of Information and Telecommunication Engineering Beijing University of Posts and Telecommunication No. 10 Xitucheng Road Haidian District Beijing100876 China

ISBN: (纸本)9783030324551

A new trapezoidal approximation of Atanassov’s intuitionistic fuzzy sets (AIFSs) and a new distance measure between AIFSs based on the area relations of membership function graphs of their corresponding trapezoidal fuzzy sets are proposed. By the conversion from Atanassov’s intuitionistic fuzzy numbers (AIFNs) to trapezoidal fuzzy numbers, the measurement of distance between AIFSs can be transformed into the calculation of area relations of the corresponding trapezoidal fuzzy sets. then the new distance measurement can integrate continuous information rather than only taking discrete variables into consideration as before. the main innovation of our distance is that it can integrate comprehensive and continuous information in calculation instead of partial discrete variables, which can efficiently avoid information loss. the contrastive tests demonstrate the efficiency and practicality of the approach. © Springer Nature Switzerland AG, 2020.

关键词： pattern recognition

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Fixed Feature with Attention Based on Recurrent Criss-Cross Salient Object Detection Network 8

Fixed Feature with Attention Based on Recurrent Criss-Cross ...

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8th international conference on Digital Home, ICDH 2020

作者： Lin, Zhenyang Li, Peiting Huang, Wenjun Yuan, Junbin Wattanachote, Kanoksak Gong, Yongyi Guangdong University of Foreign Studies Intelligent Health and Visual Computing Lab Guangzhou510006 China School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou510006 China School of Computer Science South China Normal University Guangzhou510631 China

ISBN: (纸本)9781728192345

Salient object detection (SOD) is a basic research direction in the computer vision task. Its main work is to simulate the human visual system by establishing a visual-aware model. However, most of existing models have suffered from two challenges. First, edge-aware models only use edge feature to improve segmentation features but lack of utilizing the complementarity of them. Second, the problem of losing part of information in the process of extracting features in Convolutional Neural Networks (CNN) leads to the incompleteness of final result. In this paper, we proposed a criss-cross refined salient object detection method based on hybrid attention to solve these problems. Specifically, we applied a Criss-Cross Attention module (CCA) to capture useful contextual information of surrounding pixels from long-range dependencies effectively. Fully considering the complementary between salient detection and edge information, our model simultaneously refines multilevel features of SOD and edge detection by overlapping a Cross Refinement Unit (CRU). And finally we used a U-Net to output the refined result. Extensive experiments conducted on five benchmark datasets demonstrate that our method can significantly improve the performance of low-contrast scenes, optimize the problem of partial missing and error detection of salient objects. Besides, our method achieved state-of-the-art performance in three different indicators. © 2020 IEEE.

关键词： Computer vision

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