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An investigation of machine learning and neural computation paradigms in the design of clinical decision support systems (CDSSs) 1

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8th international conference on Brain Inspired Cognitive Systems, BICS 2016

作者： Wajid, Summrina K. Hussain, Amir Luo, Bin Huang, Kaizhu Computing Science and Mathematics School of Natural Sciences University of Stirling Stirling United Kingdom School of Computing Science and Technology Anhui University Hefei China Xi’an Jiaotong-Liverpool University Suzhou China

ISBN: (数字)9783319496856

ISBN: (纸本)9783319496849

This paper reviews the state of the art techniques for designing next generation CDSSs. CDSS can aid physicians and radiologists to better analyse and treat patients by combining their respective clinical expertise with complementary capabilities of the computers. CDSSs comprise many techniques from inter-desciplinary fields of medical image acquisition, image processing and pattern recognition, neural perception and pattern classifiers for medical data organization, and finally, analysis and optimization to enhance overall system performance. This paper discusses some of the current challenges in designing an efficient CDSS as well as some of the latest techniques that have been proposed to meet these challenges, primarily, by finding informative patterns in the medical dataset, analysing them and building a descriptive model of the object of interest, thus aiding in enhanced medical diagnosis. © Springer international Publishing AG 2016.

关键词： Decision support systems

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A 1 TOPS/W Analog Deep machine-learning Engine With Floating-Gate storage in 0.13 μm CMOS

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IEEE JOURNAL OF SOLID-stATE CIRCUITS 2015年第1期50卷 270-281页

作者： Lu, Junjie Young, steven Arel, Itamar Holleman, Jeremy Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

An analog implementation of a deep machine-learning system for efficient feature extraction is presented in this work. It features online unsupervised trainability and non-volatile floating-gate analog storage. It utilizes a massively parallel reconfigurable current-mode analog architecture to realize efficient computation, and leverages algorithm-level feedback to provide robustness to circuit imperfections in analog signal processing. A 3-layer, 7-node analog deep machine-learning engine was fabricated in a 0.13 mu m standard CMOS process, occupying 0.36 mm(2) active area. At a processing speed of 8300 input vectors per second, it consumes 11.4 mu W from the 3 V supply, achieving 1x10(12) operation per second per Watt of peak energy efficiency. Measurement demonstrates real-time cluster analysis, and feature extraction for pattern recognition with 8-fold dimension reduction with an accuracy comparable to the floating-point software simulation baseline.

关键词： Analog signal processing current mode arithmetic deep machine learning floating gate neuromorphic engineering translinear circuits

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Jewelry stones Classification: Case study 7

Jewelry Stones Classification: Case Study

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7th international conference of Soft Computing and pattern recognition (SoCPaR)

作者： Hurtik, Petr Vajgl, Marek Burda, Michal Univ Ostrava Ctr Excellence IT4Innovat Inst Res & Applicat Fuzzy Modeling 30 Dubna 22 CZ-70103 Ostrava 1 Czech Republic

ISBN: (纸本)9781467393607

The paper introduces a real-life industrial problem: a jewelry stones classification. The stones are represented by their camera images. The goal of the contract was to evaluate stones into two (or more) specified classes according to their quality. Given requirements include very high processing speed and success rate of the classification. The goal of this paper is to publish a report of this contract and show a way how this task can be solved. In this paper we aim to usage of machine learning with respect to the image processing. We also design own learning and classification algorithm and answer the question if there is a place for a new machine learning algorithm. As an output of this paper a benchmark of the proposed algorithm with 81 state-of-the-art machine learning methods is presented.

关键词： image classification machine learning image processing perceptron separation tree

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Blind path obstacle detector using smartphone camera and line laser emitter

Blind path obstacle detector using smartphone camera and lin...

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international conference on Technology and Innovation in Sports, Health and Wellbeing (TISHW)

作者： Rimon Saffoury Peter Blank Julian Sessner Benjamin H. Groh Christine F. Martindale Eva Dorschky Joerg Franke Bjoern M. Eskofier Digital Sports Group Pattern Recognition Lab Department of Computer Science Institute for Factory Automation and Production Systems Friedrich-Alexander University Erlangen-Numberg (FAU) Erlangen Germany

ISBN: (纸本)9781509057283

Visually impaired people find navigating within unfamiliar environments challenging. Many smart systems have been proposed to help blind people in these difficult, often dangerous, situations. However, some of them are uncomfortable, difficult to obtain or simply too expensive. In this paper, a low-cost wearable system for visually impaired people was implemented which allows them to detect and locate obstacles in their locality. The proposed system consists of two main hardware components, a laser pointer ($12) and an android smart phone, making our system relatively cheap and accessible. The collision avoidance algorithm uses image processing to measure distances to objects in the environment. This is based on laser light triangulation. This obstacle detection is enhanced by edge detection within the captured image. An additional feature of the system is to recognize and warn the user when stairs are present in the camera's field of view. Obstacles are brought to the user's attention using an acoustic signal. Our system was shown to be robust, with only 5 % false alarm rate and a sensitivity of 90 % for 1 cm wide obstacles.

关键词： Measurement by laser beam Laser feedback Cameras Lasers Smart phones Navigation

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FAst HAND DETECTION AND GEstURE recognition 14

FAST HAND DETECTION AND GESTURE RECOGNITION

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international conference on machine learning and Cybernetics (ICMLC)

作者： Wang, Yuh-Rau Syu, Jia-Liang Li, Hsin-Ting Yang, Ling St Johns Univ Dept Comp Sci & Informat Engn Taipei Taiwan Tamkang Univ Dept Elect Engn Taipei Taiwan St Johns Univ Dept Mkt & Logist Management Taipei Taiwan

ISBN: (纸本)9781467372206

A fast hand detection and gesture recognition method is proposed in this paper. To reduce the computation time, we employ symmetric mask-based discrete wavelet transform (SMDWT) to reduce the image resolution and then utilize the extracted characteristics to perform hand detection and gesture recognition. The proposed method reduces about 66% of the overall computation time. Experimental results show that the proposed real time hand detection and gesture recognition methods can detect fast and accurately, and can be implemented on embedded system easily. The average gesture recognition rate is around 97.5%.

关键词： Discrete wavelet transform Hand detection Skin color detection Gesture recognition

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Odia Braille: Text Transcription via image processing 1

Odia Braille: Text Transcription via Image Processing

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international conference On Futuristic Trends in Computational Analysis and Knowledge Management

作者： Parvathi, K. Samal, Bijet Maynoher Das, Jitendra Kumar KIIT Univ Sch Elect Engn Bhubaneswar Odisha India

ISBN: (纸本)9781479984336

Braille-a model introduced to reduce the illiteracy rate among the visually challenged people. There has been a lot of scope for the conversion of English language to Braille but, the problem arises when the masses are unable to understand the communication by the visually challenged people. This paper focuses on the conversion of the Braille code representing Odia language(a language widely spoken in East India) into Odia word as text. For this, image processing using MATLAB technique provides a suitable platform to perform the segmentation of Braille cell for pattern selection and hence, Odia letter and word recognition. Braille Data Base creation acts as a storage system for the process and its accuracy is also tested which is explained in this paper.

关键词： visually challenged image processing image segmentation Braille Data Base Odia braille pattern recognition Histogram

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A 1 TOPS/W Analog Deep machine-learning Engine With Floating-Gate storage in 0.13 μm CMOS

A 1 TOPS/W Analog Deep Machine-Learning Engine With Floating...

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1st IEEE international Solid-state Circuits conference (ISSCC)

作者： Lu, Junjie Young, steven Arel, Itamar Holleman, Jeremy Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

ISBN: (纸本)9781479909186

关键词： Analog signal processing current mode arithmetic deep machine learning floating gate neuromorphic engineering translinear circuits

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Face recognition of Blurred images Using image Enhancement and Texture Features 1

Face Recognition of Blurred Images Using Image Enhancement a...

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1st international conference on Next Generation Computing Technologies (NGCT)

作者： Kapil, Deeksha Abhilasha Dept Comp Sci GZS PTU Campus Bathinda India CSE Dept Bathinda India

ISBN: (纸本)9781467368094

Face recognition is an existing and one of most prominent technique of biometrics that includes processing of an image and to be matched with different database. In this procedure, the user matches one person identity with several database images. Various approaches like Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), Local Ternary pattern (LTP) have been used for the purpose of face recognition. These approaches use different features for face recognition purpose. The features used for face recognition are shape, distance between two traits of face and texture features. Texture features are particularly susceptible to the resolution of images, when the resolution changes the calculated textures are not accurate. Texture features computed for low resolution images does not provide better feature information. So there is a big issue in face recognition for low resolution images. In the proposed work, EULBP (Equalized Uniform Local binary pattern) has been implemented for the purpose of low resolution images, but it does not provide better results up to an extent. To improve the recognition accuracy, the aim of this research is to study various approaches and development of new approach used for recognition purpose on low resolution images using texture features of an image which can provide better results.

关键词： DCT DWT LTP EULBP ORL database face recognition feature extraction

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image processing, Computer Vision, and pattern recognition

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2015年

作者： Arabnia, Hamid R. Deligiannidis, Leonidas C. S. R. E. A.

Proceedings of the 2019 international conference on image processing, Computer Vision, and pattern recognition (IPCV'19) held July 29th - August 1st, 2019 in Las Vegas, Nevada.

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A Privacy-preserving Crowd Movement Analysis by k-member Clustering of Face images 4

A Privacy-preserving Crowd Movement Analysis by <i>k</i>-mem...

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4th international conference on Informatics, Electronics & Vision (lCIEV)

作者： Honda, Katsuhiro Omori, Masahiro Ubukata, Seiki Notsu, Akira Osaka Prefecture Univ Grad Sch Engn Sakai Osaka 5998531 Japan

ISBN: (纸本)9781467369022

Crowd movement analysis is an important issue in social design. This paper studies an machine learning approach to crowd movement estimation through face image recognition. Although high performance face recognition is a powerful tool in individual authentication with surveillance camera images in public spaces, utilization of personal information is often hesitated under fear of privacy violation. In this paper, a privacy preserving framework for crowd movement analysis is proposed considering k-anonymization of face image features. k-anonymity is a quantitative measure of secureness in data mining and is expected to enhance the utility of personal information. An experimental result demonstrates the applicability of the secure framework in capturing crowd movement characteristics even if individual features are k-aonymized so that each individual is not distinguishable from others k - 1 ones.

关键词： cameras data mining data privacy face recognition learning (artificial intelligence) parallel processing high performance face image recognition k-anonymization k-member clustering machine learning approach privacy violation privacy-preserving crowd movement analysis surveillance camera image Cameras Data privacy Face Face recognition image recognition Logic gates pattern matching Data privacy Facial recognition Cameras data mining image recognition Face Face pattern matching Logic gates PARALLEL processing (COMPUTERS) Movements

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