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Adaptive stochastic resonance and fuzzy approximation

Adaptive stochastic resonance and fuzzy approximation

引用

ieee International symposium on Intelligent Control (ISIC)

作者： S. Mitaim B. Kosko Signal and Image Processing Institute Department of Electrical Engineering-Systems University of Southern California Los Angeles CA USA

The paper derives the stochastic resonance (SR) optimality conditions that any stochastic learning system should try to achieve. The adaptive system learns the SR effect as the system performs a stochastic gradient ascent on the signal-to-noise ratio. The stochastic learning scheme does not depend on a fuzzy system or any other adaptive system. The learning process is slow and noisy and can require heavy computation. Robust noise suppressors can improve the learning process when we can estimate the impulsiveness of the noise or of other learning terms. Simulations test this SR learning scheme on the popular quartic-bistable dynamical system for many types of noise. The simulation test results suggest that fuzzy techniques and perhaps other "intelligent" techniques can induce SR in many cases when users cannot state the exact form of the dynamical systems.

关键词： Stochastic resonance Strontium Stochastic systems Adaptive systems Fuzzy systems computational modeling System testing Learning systems signal to noise ratio Noise robustness

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A commixed modified Gram-Schmidt and region growing mechanism for white blood cell image segmentation

A commixed modified Gram-Schmidt and region growing mechanis...

引用

ieee International symposium on Intelligent signal processing

作者： Khaled A. Abuhasel Chastine Fatichah Abdullah M. Iliyasu College of Engineering Salman Bin Abdulaziz University Al-Kharj Kingdom of Saudi Arabia Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Computational Intelligence and Systems Science Tokyo Institute of Technology Japan

A modified Gram-Schmidt orthogonalisation method has been commixed with a region growing method for efficient white blood cell image segmentation. The modified Gram-Schmidt method is used to segment the nucleus of white blood cells, while the region growing method is employed to segment the cytoplasm of white blood cells. To evaluate the performance of WBC image segmentation, the 100 samples of the microscopic WBC images is used. The segmentation results from the proposed mechanism are compared with manually segmented images, which are considered to be the correct segmentation result. Accuracy of the results reaches 95.21% and 92.31% for the Lymphocyte and Neutrophil cell types for the modified Gram-Schmidt and region growing methods, respectively. The results suggest that the proposed mechanism could be used for WBC classification in other applications such as cancer diagnosis.

关键词： image segmentation White blood cells Microscopy Accuracy Morphology Diseases

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Panoramic mosaicing with image interpolation

Panoramic mosaicing with image interpolation

引用

International symposium on Intelligent Multimedia, Video and Speech processing

作者： Zong-Cai Ruan Dong Liang Sui Wei Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University of Science and Technology Hefei China

ISBN: (纸本)9628576623

Panoramic mosaics methods based on an 8-parameter planar homography matrix have to overcome the accumulated errors when a sequence of images loops back on itself. Usual methods are computationally intensive, and cannot ensure complete consistency of homographies. The paper presents a simple method which does not require the consistency of homographies. The method mainly exploits an un-calibrated image perspective interpolation technique (B. Yuan et al., 1998). It is therefore simple to calculate and easy to implement.

关键词： Interpolation Transmission line matrix methods Matrix decomposition Equations Error correction computational intelligence signal processing Nonlinear optics Optical signal processing image motion analysis

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Mining visual complexity of images based on an enhanced feature space representation

Mining visual complexity of images based on an enhanced feat...

引用

ieee International symposium on Intelligent signal processing

作者： Abdullah M. Iliyasu Awad Kh. Al-Asmari Mohamed A. AbdelWahab Ahmed S. Salama Mohamed A. Al-Qodah Asif R. Khan Phuc Q. Le Fei Yan Department of Computational Intelligence & Systems Science Tokyo Institute of Technology Japan Salman Bin Abdul-Aziz University Al Kharj Kingdom of Saudi Arabia Image and Signal Processing Lab King Saud University Kingdom of Saudi Arabia

An enhanced feature space to represent visual complexity of images, as would the HVS, is presented. Specifically, the ratio between the coherent and incoherent pixels in an image was used as a measure of the chromatic contributions to the visual complexity of an image. Similarly, the contrast, energy, entropy and homogeneity were modelled as the textural attributes of an image's visual complexity. Integrated into the SND feature space, these new (chromatic and textural) features facilitate a better and enhanced representation of visual complexity. Using the Corel 1000A dataset to validate the veracity of the proposal, the enhanced visual complexity space, the SND + space, improves the capability to better represent visual complexity by a 16.7% increase in the exact correlation with a subjective (human) evaluation of the same dataset over the original SND space. Pursued further, the effective representation of visual complexity would have profound impacts in many areas of image processing and computer vision.

关键词： Complexity theory Visualization Feature extraction image color analysis Computer vision Noise Correlation

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Fuzzy networks: What happens when fuzzy people are connected through social networks

Fuzzy networks: What happens when fuzzy people are connected...

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ieee symposium on Foundations of computational intelligence, FOCI

作者： Li-Xin Wang Jerry M. Mendel Department of Automation Science and Technology Xian Jiaotong University Xian China Signal and Image Processing Institute University of Southern California Los Angeles CA USA

A fuzzy node is a fuzzy set whose membership function contains some uncertain parameters. Two fuzzy nodes are connected if the uncertain parameter of one node is provided by the fuzzy set from the other node. A fuzzy network is a connection of a number of fuzzy nodes. We define Gaussian Fuzzy Networks and study a number of basic connections in details, including basic center, basic standard deviation (sdv), basic center-sdv, chain-in-center, chain-in-sdv, self-feedback and some other connections. We derive the membership functions resulting from these connections that reveal how the fuzziness is propagated through the networks, and we explain what the mathematical results mean with respect to human behaviors.

关键词： Fuzzy sets Standards Uncertainty Bayes methods Social network services Network theory (graphs) Pragmatics

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Variational Inference of Finite Generalized Gaussian Mixture Models

Variational Inference of Finite Generalized Gaussian Mixture...

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ieee symposium Series on computational intelligence (SSCI)

作者： Srikanth Amudala Samr Ali Fatma Najar Nizar Bouguila Concordia Institute for Information Systems Engineering Concordia University Montreal Canada Department of Electrical and Computer Engineering Concordia University Montreal Canada

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

This paper presents a variational learning framework to analyze finite g eneralized G aussian m ixture models (GGMM). The model incorporates several mixtures that are widely used in signal and image processing applications. The motivation behind this work is the shape flexibility characteristics of the generalized Gaussian distribution (GGD) because of which it can be applied to different types of data. We present a method to evaluate the posterior distribution and Bayes estimators using the variational expectation-maximization algorithm. The effective number of components of the GGMM is determined automatically. The test results show the adequacy of the proposed algorithm by applying it to medical, astrological, and image segmentation applications; while comparing it with various other approaches.

关键词： Shape Gaussian mixture model Gaussian distribution Inference algorithms image segmentation Information systems

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Design of a Digital Architecture for Real-Time Video, Enhancement Based on Illuminance-Reflectance Model

Design of a Digital Architecture for Real-Time Video, Enhanc...

引用

Midwest symposium on Circuits and Systems (MWSCAS)

作者： Hau T. Ngo Ming Z. Zhang Li Tao Vijayan K. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

A design of a high performance digital architecture for a nonlinear image enhancement technique is presented in this paper. The image enhancement is based on illuminance-reflectance model which improves the visual quality of digital images and video captured under insufficient or non-uniform lighting conditions [1]. Systolic, pipelined and parallel design techniques are utilized effectively in the proposed FPGA-based architectural design to achieve real-time performance. Estimation and folding techniques are used in the hardware algorithmic design to achieve faster, simpler and more efficient architecture. The video enhancement system is implemented using Xilinx's multimedia development board that contains a VirtexII-X2000 FPGA and it is capable of processing approximately 66 Mega-pixels (Mpixels) per second.

关键词： signal processing algorithms image enhancement Field programmable gate arrays Digital signal processing Computer architecture image coding Streaming media Parallel processing Reflectivity Algorithm design and analysis

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An efficient color compensation scheme for skin color segmentation

An efficient color compensation scheme for skin color segmen...

引用

ieee International symposium on Circuits and Systems (ISCAS)

作者： Kwok-Wai Wong Kin-Man Lam Wan-Chi Siu Centre for Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China

ISBN: (纸本)0780377613

Skin color is a useful means for human face detection. In this paper, we propose an efficient color compensation method for skin color segmentation under varying lighting conditions. One of the major problems of using skin color is that a face region may not be detected under poor or uneven lighting conditions. Our approach considers the distribution of the color components of skin pixels and the color response of capturing machines under different illuminations. Experimental results show that this algorithm can improve the performance of face segmentation under poor or strong lighting conditions.

关键词： Skin Face detection image segmentation Humans Color signal processing Lighting signal processing algorithms computational intelligence Machine intelligence

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Design of Deep Convolutional Neural Network Architectures for Denoising Electrocardiographic signals

Design of Deep Convolutional Neural Network Architectures fo...

引用

ieee symposium on computational intelligence and Bioinformatics and computational Biology (CIBCB)

作者： Corneliu Arsene University of Manchester Manchester United Kingdom

ISBN: (数字)9781728194684

ISBN: (纸本)9781728194691

Deep Learning (DL) models have been used extensively in image processing and other domains with great success but only very recently have been used in processing electrocardiogram (ECG) signals. Effective and powerful methods for denoising real ECG signals are important for wearable sensors and devices. This paper presents the design of a DL model, the Convolutional Neural Networks (CNNs), together with the more conventional filtering methods (low pass filtering, high pass filtering, Notch filtering) and the standard wavelet-based technique for denoising ECG signals. This combination shows to produce better results than using only the CNN models. The methods are trained, tested and evaluated on real ECG datasets taken from the MIT PhysioNet database. The results show the CNN model is a performant model that can be used for denoising ECG signals, and also that before applying the CNN model, standard filtering of the original ECG signal has a beneficial effect for the final results. All CNN models used an NVIDIA TITAN V Graphical processing Unit (GPU) with 12 GB RAM, which reduces drastically the computational times.

关键词： Electrocardiography signal to noise ratio Noise reduction Noise measurement Filtering Filtering algorithms Databases

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Generated Compressed Domain images to the Rescue: Cross Distillation from Compressed Domain to Pixel Domain

Generated Compressed Domain Images to the Rescue: Cross Dist...

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ieee International symposium on Circuits and Systems (ISCAS)

作者： Reyhan Kevser Keser Muhammet Sebul Beratoğlu Behçet Uğur Töreyin Signal Processing for Computational Intelligence Research Group (SP4CING) Informatics Institute İstanbul Technical University İstanbul Türkiye Dept. of Artificial Intelligence and Data Engineering Signal Processing for Computational Intelligence Research Group (SP4CING) İstanbul Technical University İstanbul Türkiye

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Data are the essential component in the pipeline of training a model that determines the performance of the model. However, there may not be enough data that meet the requirements of some tasks. In this paper, we introduce a knowledge distillation-based approach that mitigates the disadvantages of data scarcity. Specifically, we propose a method that boosts the pixel domain performance of a model, by utilizing compressed domain knowledge via cross distillation between these two modalities. To evaluate our approach, we conduct experiments on two computer vision tasks which are object detection and recognition. Results indicate that compressed domain features can be utilized for a task in the pixel domain via our approach, where data are scarce or not completely available due to privacy or copyright issues.

关键词： Training Data privacy Computer vision image coding computational modeling Pipelines Object detection

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