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共 180 条记录，以下是91-100 订阅

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Optimized local discriminant basis algorithm

Optimized local discriminant basis algorithm

引用

4th international conference on Multimedia and Expo (ICME 2003)

作者： Hazaveh, K Raahemifar, K Ryerson Univ Dept Elect & Comp Engn Toronto ON Canada

ISBN: (纸本)0780379659

Local discriminant bases method is a powerful algorithmic framework for feature extraction and classification applications that is based on supervised training. It is considerably faster compared to more theoretically ideal feature extraction methods such as principal component analysis or projection pursuit. In this paper an optimization block is added to original local discriminant bases algorithm to promote the difference between disjoint signal classes. this is done by optimally weighting the local discriminant basis using steepest decent algorithm. the proposed method is particularly useful when background features in the signal space show strong correlation with regions of interest in the signal as in mammograms for instance.

关键词： best basis local discriminant basis local feature extraction the steepest decent method pattern recognition time-frequency analysis wavelet packet and mammography

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Mathematical Model for Absolute Magnetic Measuring Systems in Industrial applications 4

Mathematical Model for Absolute Magnetic Measuring Systems i...

引用

4th international conference on Mathematical Modeling in Physical Sciences (IC-MSquare)

作者： Fuegenschuh, Armin Fuegenschuh, Marzena Ludszuweit, Marina Mojsic, Aleksandar Sokol, Joanna Helmut Schmidt Univ Univ Fed Armed Forces Hamburg Dept Mech Engn Holstenhofweg 85 D-22043 Hamburg Germany Beuth Hsch Tech Berlin D-13353 Berlin Germany

Scales for measuring systems are either based on incremental or absolute measuring methods. Incremental scales need to initialize a measurement cycle at a reference point. From there, the position is computed by counting increments of a periodic graduation. Absolute methods do not need reference points, since the position can be read directly from the scale. the positions on the complete scales are encoded using two incremental tracks with different graduation. We present a new method for absolute measuring using only one track for position encoding up to micrometre range. Instead of the common perpendicular magnetic areas, we use a pattern of trapezoidal magnetic areas, to store more complex information. For positioning, we use the magnetic field where every position is characterized by a set of values measured by a hall sensor array. We implement a method for reconstruction of absolute positions from the set of unique measured values. We compare two patterns with respect to uniqueness, accuracy, stability and robustness of positioning. We discuss how stability and robustness are influenced by different errors during the measurement in real applications and how those errors can be compensated.

关键词： Magnetism

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Impulse noise removal using linear prediction model

Impulse noise removal using linear prediction model

引用

4th international conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, ITELSIKS 1999

作者： Prudyus, Ivan Voloshynovskiy, Sviatoslav Rytsar, Yuriy Holotyak, Taras Radio Engineering Faculty State University Lvivska Polytechnika 12 S.Bandery Str. Lviv 290646 Ukraine Coordinated Science Laboratory University of Illinois College of Engineering 1308 West Main Street Urbana IL 61801-2307 United States Department of Image Processing and Pattern Recognition Institute of Physics and Mechanics National Academy of Science of Ukraine 5 Naukova str. Lviv Ukraine

ISBN: (纸本)078035768X

Noise removal is an important problem in many applications. In this paper a new two-step scheme of the decision-based impulse noise removal method by means of contaminated pixel detection is proposed and comparison with direct order statistic filtering is given. the proposed methods satisfy both objective and subjective image quality. © 1999 IEEE.

关键词： Impulse noise

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Mushroom Classification Based on Deep Residual Network 4

Mushroom Classification Based on Deep Residual Network

引用

4th IEEE international conference on pattern recognition and Machine Learning, PRML 2023

作者： Feng, Ju Ling, Xufeng Wang, Yubo Yang, Jie Shanghai Normal University Tianhua College School of Artificial Intelligence Shanghai China Shanghai Acoustics Laboratory Chinese Academy of Sciences Shanghai China Inst. of Image Proc. and Pattern Recog. and Inst. of Medical Robotics Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9798350324303

Due to the similarity in mushroom features and the difficulty in distinguishing between poisonous and nonpoisonous varieties, mushrooms pose a threat to human health. To address the challenge of mushroom classification and identification, this paper proposes a mushroom classification method based on residual networks. Firstly, a network architecture with multiple residual blocks is designed, and it is trained using an image dataset. then, a transfer learning strategy is employed to initialize the network parameters from a pre-Trained model, followed by fine-Tuning to adapt to the mushroom classification task. Finally, multiple testing experiments are conducted to evaluate the effectiveness of the proposed method. the experimental results demonstrate excellent performance of the proposed method in mushroom classification tasks. Compared to traditional feature extraction methods, it can better capture the details and texture features of mushrooms, thereby improving classification accuracy. In conclusion, the mushroom classification method based on residual networks exhibits high accuracy and generalization capability. this method has potential applications in the field of mushroom classification, aiding in the better identification and differentiation of poisonous mushrooms, thereby protecting human health. © 2023 IEEE.

关键词： Convolutional neural networks

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IEEE 2015 international conference on Signal and Image Processing applications, ICSIPA 2015 - Proceedings

IEEE 2015 International Conference on Signal and Image Proce...

引用

4th IEEE international conference on Signal and Image Processing applications, ICSIPA 2015

ISBN: (纸本)9781479989966

the proceedings contain 106 papers. the topics discussed include: analyzing WirelessHART high-level data link control frame payload;evaluation of digital elevation model using rational polynomial coefficient based on HR Pleiades satellite stereo imagery;design and implementation computing unit for laser jamming system using spatial parallelism on FPGA;a low-complexity sphere detection technique for orthogonal frequency division multiplexing systems in selective fading channels;object identification and tracking for steady registration in mobile augmented reality;a knowledge based approach for colon segmentation in CT colonography images;object tracking using joint histogram of color and local rhombus pattern;action recognition in low quality videos by jointly using shape, motion and texture features;recognition of Iranian accidental notes based on the zoning feature and Hough transform;and underwater image restoration by red-dark channel prior and point spread function deconvolution.

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Processing of Surface EMG through pattern recognition Techniques Aimed at Classifying Shoulder Joint Movements 37

Processing of Surface EMG Through Pattern Recognition Techni...

引用

37th Annual international conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Rivela, Diletta Scannella, Alessia Pavan, Esteban E. Frigo, Carlo A. Belluco, Paolo Gini, Giuseppina Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy Politecn Milan Movement Biomech & Motor Control Lab I-20133 Milan Italy B10nix I-20131 Milan Italy Politecn Milan Artificial Intelligence & Robot Lab I-20133 Milan Italy

ISBN: (纸本)9781424492701

Artificial arms for shoulder disarticulation need a high number of degrees of freedom to be controlled. In order to control a prosthetic shoulder joint, an intention detection system based on surface electromyography (sEMG) pattern recognition methods was proposed and experimentally investigated. Signals from eight trunk muscles that are generally preserved after shoulder disarticulation were recorded from a group of eight normal subjects in nine shoulder positions. After data segmentation, four different features were extracted (sample entropy, cepstral coefficients of the 4th order, root mean square and waveform length) and classified by means of linear discriminant analysis. the classification accuracy was 92.1% and this performance reached 97.9% after reducing the positions considered to five classes. To reduce the computational cost, the two channels with the least discriminating information were neglected yielding to a classification accuracy diminished by just 4.08%.

关键词： sEMG Processing Surface

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Using emerging patterns and decision trees in rare-class classification

Using emerging patterns and decision trees in rare-class cla...

引用

4th IEEE international conference on Data Mining

作者： Alhammady, H Ramamohanarao, K Univ Melbourne Dept Comp Sci & Software Engn Parkville Vic 3052 Australia

ISBN: (纸本)0769521428

the problem of classifying rarely occurring cases is faced in many real life applications. the scarcity of the rare cases makes it difficult to classify them correctly using traditional classifiers. In this paper, we propose a new approach to use emerging patterns (EPs) [3] and decision trees (DTs) in rare-class classification (EPDT). EPs are those itemsets whose supports in one class are significantly higher than their supports in the other classes. EPDT employs the power of EPs to improve the quality of rare-case classification. To achieve this aim, we first introduce the idea of generating new non-existing rare-class instances, and then we over-sample the most important rare-class instances. Our experiments show that EPDT outperforms many classification methods.

关键词： pattern recognition

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Convolutional Neural Network Based Desktop applications to Classify Dermatological Diseases 4

Convolutional Neural Network Based Desktop Applications to C...

引用

4th IEEE international conference on Image Processing, applications and Systems, IPAS 2020

作者： Goceri, Evgin Akdeniz University Biomedical Engineering Department Antalya Turkey

ISBN: (纸本)9781728175744

Convolutional Neural Networks (CNNs) have the potential to assist medical doctors in diagnosis and treatment stage. this paper has been prepared to help dermatologists by presenting (i) fundamental information on deep learning and CNNs, and (ii) applications of CNN s for skin diseases classification. Also, this work shows that although CNN based methods have a strong potential for automated diagnosis, further researches and new techniques are still required in image processing and pattern recognition area to provide diagnosis of dermatological diseases with higher performances. In this work, these two groups of applications of CNN s in dermatology have been handled: (i) disease classification from medical images (e.g., dermoscopy and pathological images);(ii) disease classification from digital photographs. therefore, important contributions of this work are two-fold: First, main concepts of deep learning and CNNs are presented, which will be helpful for dermatologists to understand and follow up CNN based computerized methods. Second, the state-of-the-Art applications developed for lesion classifications from medical images and colored photographs are presented. Also, disadvantages or limitations of these applications are explained. In addition, this paper indicates shortage of desktop applications developed for other dermatological diseases except skin cancer. © 2020 IEEE.

关键词： Convolutional neural networks

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Wood Species recognition Using Machine Learning 4

Wood Species Recognition Using Machine Learning

引用

4th international conference on Microelectronics, Signals and Systems, ICMSS 2021

作者： Neethu, S. Baby Syla, L. A P J Abdul Kalam Technical University Department of Computer Applications CET Trivandrum India

ISBN: (纸本)9781665448857

Although a computer vision-based automated wood species detection system is not extensively employed today, it is in high demand in a range of industries. Because each species of wood has distinct features and traits that determine how it is used and implemented. Human experts have traditionally been used nearly entirely in the identifying process, which is based on a variety of features of wood, such as texture, structure, and colour. Even competent scientists have difficulties distinguishing between different species of wood found in nature. the most difficult aspect of wood recognition is that some wood species have a texture that is identical to that of others, hence feature extraction is the most important step in the process. So in this work, two statistical feature extraction techniques are used 1) Local Binary pattern (LBP) 2) Gray Level Co-Occurrence Matrix (GLCM). Features extracted from both methods are combined to see whether they increase classification accuracy or not. Multi-SVM is used for classification. For this study, a new dataset is created which includes the three most common tree species in Indian territory. this study found that integrating LBP and GLCM features enhanced classification accuracy. Proposed system produces a result of 97.2%, which is better than individual approaches. © 2021 IEEE.

关键词： Local binary pattern

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An approach to the 2D Hilbert Transform for image processing applications

引用

4th international conference on Image Analysis and recognition

作者： Lorenzo-Ginori, Juan Valentin Univ Cent Las Villas Ctr Studies Elect & Informat Technol Santa Clara 54830 VC Cuba

ISBN: (纸本)9783540742586

the Hilbert Transform (HT) and the analytic signal (AS) are widely used in their one-dimensional version for various applications. However, in the bi-dimensional (2D) case as occur for images, the definition of the 2D-HT is not unique and several approaches to it have been developed, having as one of the main goals to obtain a meaningful 2D-AS or analytic image, which can be used for various practical applications. In this work, one particular approach to the 2D-HT is introduced that allowed the calculation of analytic images which satisfy the basic properties that these functions have in the ID case, and that produces a 2D spectrum equal to zero in one quadrant. the methods for calculation of the discrete version of the 2D-HT and the associated AS are presented and analyzed, as well as two applications, for edge detection and for envelope detection in a 2D AM modulated radial chirp.

关键词： Hilbert spaces

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