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检索条件"任意字段=8th International Conference on Computing and Pattern Recognition, ICCPR 2019"

共 394 条记录，以下是71-80 订阅

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Parallel computing Scheme for Graph Grammar-Based Syntactic pattern recognition

Parallel Computing Scheme for Graph Grammar-Based Syntactic ...

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8th international conference on Parallel Processing and Applied Mathematics

作者： Flasinski, Mariusz Jurek, Janusz Myslinski, Szymon Jagiellonian Univ IT Syst Dept PL-31110 Krakow Poland

ISBN: (纸本)9783642143892

Real-time syntactic pattern recogniton imposes strict computing time constraints on new techniques developed. Recently, a method for an analysis of hand postures of the Polish Sign Language based on the ETPL(k) graph grammars (Flasinski: Patt. Recogn. 26 (1993);1-16;theor. Comp. Sci. 201 (1998), 189-231) has been constructed. In order to make a system implemented more feasible for the users, a research into parallelization of a pattern recognition process has been led. Possible techniques of tasks distribution have been tested. It has allowed us to define an optimum strategy of parallelization. the results are presented in the paper.

关键词： parallel computing syntactic pattern recognition graph grammar

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Approaches to developing an audio system as part of a smart house 8

Approaches to developing an audio system as part of a smart ...

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8th IEEE international conference on Energy Smart Systems, ESS 2022

作者： Bevz, Svitlana Voitko, Viktoriia Burbelo, Sergii Stavytskyi, Pavlo Vinnytsia National Technical University Vinnytsia Ukraine

ISBN: (数字)9798350334418

ISBN: (纸本)9798350399202

Approaches to the development of the system of music synthesis and recognition are considered. In addition, such audio software as part of the smart house system can bring additional benefits and increased experience for its users. It is important to consider an audio recognition state that considers fingerprint creation and optimization. Moreover, an approach of parallel GPU computing is considered as a solution to the fingerprint matching process optimization. © 2022 IEEE.

关键词： pattern matching

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ECG Analysis and Heartbeat Classification Based on Shallow Neural Networks 8

ECG Analysis and Heartbeat Classification Based on Shallow N...

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8th international conference on Modern Circuit and System Technologies (MOCAST)

作者： Balaskas, Konstantinos Siozios, Kostas Aristotle Univ Thessaloniki Dept Phys Thessaloniki Greece

ISBN: (纸本)9781728111841

Accurate detection of cardiac pathological events is an important part of electrocardiogram (ECG) evaluation and subsequent correct treatment of the patient. For this purpose, several adaptive filter structures were proposed during the past decades for noise cancellation and arrhythmia detection. Currently there are a lot of devices on the market that analyze ECGs, such as patient monitors, stress test systems, and Holter analysis systems, that are able to detect beats and classify arrhythmia. this paper proposes a system for ECG analysis and heartbeat classification. the proposed solution relies on a combination of machine learning algorithm and a wavelet transformation in order to maximize its performance with the minimum possible training phase. Experimental results with public available data for arrhythmia indicate the efficiency in classifying heartbeats, whereas its low-computational and memory requirements makes it suitable for being implemented as part of an embedded (IoT) system.

关键词： Neural Network ECG pattern recognition Discrete Wavelet Transform Feature Extraction

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Emotion recognition in Dementia: Advancing technology for multimodal analysis of emotion expression in everyday life 8

Emotion Recognition in Dementia: Advancing technology for mu...

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8th international conference on Affective computing and Intelligent Interaction (ACII)

作者： Nazareth, Deniece S. Univ Twente Psychol Hlth & Technol Human Media Interact Enschede Netherlands

ISBN: (纸本)9781728138916

this paper provides an overview of my PhD project that focuses on recognizing emotions in dementia by analyzing multi-modal expressions in autobiographical memories of older adults with dementia. the project aims for a better understanding how dementia influences emotional expressions and how dementia differs from the normal aging process. For this reason, spontaneous emotions will be elicited in autobiographical memories in two groups of older adults, one with dementia the other without, for comparison. Audio, video and physiological data will be collected at their home resulting in real-life environments. the emotional expressions can then be analyzed by extracting verbal, non-verbal, facial and gestural features from the audio, video and physiological data collected. In addition, a longitudinal study will be conducted with the older adults with dementia to investigate the longitudinal effect of dementia on emotions. A database of the emotional memories of these vulnerable groups will then be developed to contribute to the advancement of technologies for (automatic) multi-modal emotion recognition. the database will then be made available for the research community. Lastly, we will also develop visualization and statistical models to assess multi-modal patterns of emotion expression in these groups.

关键词： emotions spontaneous older adults dementia multi-modal old age autobiographical memories affective computing

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Hardware-Efficient Ultrasonic Entrance Counting: Comparing Different Machine Learning Approaches 26

Hardware-Efficient Ultrasonic Entrance Counting: Comparing D...

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26th international conference on pattern recognition / 8th international Workshop on Image Mining - theory and Applications (IMTA)

作者： Langer, Tim Waschneck, Bernd Partzsch, Johannes Kelber, Florian Mayr, Christian Infineon Technol Dresden GmbH Co KG Dresden Germany Fraunhofer Inst Integrated Circuits Div Engn Adapt Syst Dresden Dresden Germany Tech Univ Dresden Chair Highly Parallel VLSI Syst & Neuro Microelec Dresden Germany

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

In this work, the classification of walking direction based on ultrasonic signals has been examined for entrance counting. Feed-forward and recurrent neural network architectures as well as simpler machine learning techniques have been investigated and compared with classical signal processing techniques. Using only a single ultrasonic receiver, the focus was set on the development of a hardware-efficient system concept. Different ultrasonic measurement methods in time and frequency domain have been compared with the perspective of a holistic energy optimization. the analysis of the system's hardware efficiency was completed by an estimation of algorithmic latency, energy and storage consumption based on the arithmetic of the classification algorithms. All algorithms showed an estimated energy consumption of less than 10 mu J for a single inference on a state-of-the-art implementation of an ARM (R) Cortex (R) M4F micro-controller, which was found to be negligible compared to the energy of the measurement principle. Compared to other sensor types and multi-sensor systems, a state-of-the-art test accuracy of 99.72% could be achieved for differentiating between the two entrance directions of a present person and the absence of a person.

关键词： Entrance Counting Ultrasound Machine Learning Edge computing Low Power TinyML Smart Buildings

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Deep Learning-based Method for Classifying and Localizing Potato Blemishes 8th

Deep Learning-based Method for Classifying and Localizing Po...

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

作者： Marino, Sofia Beauseroy, Pierre Smolarz, Andre Univ Technol Troyes Inst Charles Delaunay M2S FRE 2019 Troyes France

ISBN: (纸本)9789897583513

In this paper we address the problem of potato blemish classification and localization. A large database with multiple varieties was created containing 6 classes, i.e., healthy, damaged, greening, black dot, common scab and black scurf. A Convolutional Neural Network was trained to classify face potato images and was also used as a filter to select faces where more analysis was required. then, a combination of autoencoder and SVMs was applied on the selected images to detect damaged and greening defects in a patch-wise manner. the localization results were used to classify the potato according to the severity of the blemish. A final global evaluation of the potato was done where four face images per potato were considered to characterize the entire tuber. Experimental results show a face-wise average precision of 95% and average recall of 93%. For damaged and greening patch-wise localization, we achieve a False Positive Rate of 4.2% and 5.5% and a False Negative Rate of 14.2% and 28.1% respectively. Concerning the final potato-wise classification, we achieved in a test dataset an average precision of 92% and average recall of 91%.

关键词： Deep Learning Potato Blemishes Classification Localization Autoencoder SVM

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Historical recall and precision: Summarizing generated hypotheses

Historical recall and precision: Summarizing generated hypot...

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8th international conference on Document Analysis and recognition (ICDAR 2005)

作者： Zanibbi, R Blostein, D Cordy, JR Concordia Univ Ctr Pattern Recognit & Machine Intelligence Montreal PQ Canada

ISBN: (纸本)0769524206

Document recognition involves many kinds of hypotheses: segmentation hypotheses, classification hypotheses, spatial relationship hypotheses, and so on. Many recognition strategies generate valid hypotheses which are eventually rejected, but current evaluation methods consider only accepted hypotheses. As a result, we have no way to measure errors associated with rejecting valid hypotheses. We propose describing hypothesis generation in more detail, by collecting the complete set of generated hypotheses and computing the recall and precision of this set: we call these the ' historical recall ' and ' historical precision.' Using table cell detection examples, we demonstrate how historical recall and precision along with the complete set of generated hypotheses assist in the evaluation, debugging, and design of recognition strategies..

关键词： pattern recognition systems

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Local directional intensity pattern for facial expression recognition 8

Local directional intensity pattern for facial expression re...

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8th international conference on Control, Automation and Information Sciences (ICCAIS)

作者： Huang, Weijia Zhang, Zhengyan Liu, Huaming Jiangsu Univ Sci & Technol Sch Elect & Informat Zhenjiang Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Sch Telecommun & Informat Engn Nanjing Peoples R China Fuyang Normal Univ Sch Comp & Informat Engn Fuyang Peoples R China

ISBN: (纸本)9781728123110

this paper presents a new face descriptor, local directional intensity pattern (LDIP), for human facial expression recognition. Considering the edge information and pixel intensity changes of face images, local features extracted from not only frequency domain but also spatial domain are encoded in a compact way, which makes features complementary to each other and much more discriminative. Additionally, the histogram refinement further reduces the feature dimensions while enhancing the performance of the texture descriptor. Extensive experiments are conducted to verify the effectiveness of our proposed method. the experimental results demonstrate that the LDIP is a discriminative and efficient facial expression descriptor, which achieves higher recognition rate than other descriptors.

关键词： local directional intensity pattern facial expression recognition feature extraction face descriptor

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Automatic keyphrase extraction from Chinese books

Automatic keyphrase extraction from Chinese books

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8th ACIS international conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed computing/3rd ACIS international Workshop on Self-Assembling Wireless Networks

作者： Chen, Yijiang Shi, Xiaodong Zhou, Changle Su, Chang Xiamen Univ Dept Comp Sci Xiamen Univ Box 342 Xiamen 361005 Peoples R China

ISBN: (纸本)0769529097

this paper presents an approach of Automatic Keyphrase Extraction from Chinese Books. In this paper the Local Reoccurrence Measure is proposed to greatly improve the automatic keyphrase recognition. this measure can also be applied to enhance keyphrase extraction of foreign language. the approach is tested on 1740 Chinese books and the experiment results are satisfactory.

关键词： pattern recognition

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An Improved three-dimensional Indoor Positioning Algorithm Based on Pedestrian Dead Reckoning 8

An Improved Three-dimensional Indoor Positioning Algorithm B...

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8th international conference on Intelligent computing and Signal Processing, ICSP 2023

作者： Dong, Xuezhi Xiao, Jiaxun Central South University School of Physics and Electronics Changsha China

ISBN: (纸本)9798350302455

Due to the complex indoor environment of the buildings, Two-dimensional (2D) indoor positioning is difficult to meet the needs of people. therefore, it is necessary to make some improvements in three-dimensional (3D) indoor positioning. In this paper, a 3D indoor positioning algorithm based on improved pedestrian dead-reckoning (PDR) is proposed. the PDR was improved in motion pattern recognition and step detection. For motion pattern recognition, an improved support vector machine (SVM) method is proposed, which use the confidence threshold to improve the recognition accuracy of the SVM in continuous motion state. For step detection, an improved step detection method is proposed, which sets the peak threshold and valley threshold for acceleration, and the idea of zero-crossing detection method is also used to improve the accuracy of peak detection method. the experimental result of 3D environment shows that the accuracy of motion pattern recognition and step detection is 96.43% and 99.87% respectively and the mean error of the positioning result is 0.63m, which has a reduction of 75.8% compared to the traditional PDR algorithm. © 2023 IEEE.

关键词： pattern recognition

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