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ieee SSCI 2014: 2014 ieee symposium Series on computational intelligence - CIVTS 2014: 2014 ieee symposium on computational intelligence in Vehicles and Transportation Systems, Proceedings

IEEE SSCI 2014: 2014 IEEE Symposium Series on Computational ...

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2014 ieee symposium on computational intelligence in Vehicles and Transportation Systems, CIVTS 2014

ISBN: (纸本)9781479944989

The proceedings contain 21 papers. The topics discussed include: traffic information extraction from a blogging platform using knowledge-based approaches and bootstrapping;multi-objective selection of input sensors for travel times forecasting using support vector regression;predicting bikeshare system usage up to one day ahead;dynamic ridesharing with intermediate locations;an evolutionary approach to traffic assignment;evolving the topology of subway networks using genetic algorithms;driver distraction detection by in-vehicle signal processing;trust-based controller for convoy string stability;cloud aided semi-active suspension control;exploring the Mahalanobis-Taguchi approach to extract vehicle prognostics and diagnostics;and robust obstacle segmentation based on topological persistence in outdoor traffic scenes.

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Customized EfficientNet for Histopathology image Representation

Customized EfficientNet for Histopathology Image Representat...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Mazaheri, Pooria Bidgoli, Azam Asilian Rahnamayan, Shahryar Dehkharghanian, Taher Tizhoosh, Hamid R.

ISBN: (纸本)9781665487689

In recent years, and amplified by the COVID-19 pandemic, the digitization of pathology has gained a considerable attention. Digital pathology provides crucial advantages compared to conventional light microscopy, including more efficient workflows, more accurate diagnosis and treatment planning, and easier collaboration. Despite promising progress, there are some critical challenges related to classifying images in digital pathology, such as huge input sizes (e.g., gigapixels) and expensive processing time. Most of the existing models for classification of histopathology images are very large and accordingly have many parameters to be learned/optimized. In addition, due to the large size of Whole Slide images (WSIs), e.g., 100,000 x 100,000 pixels, models require enormous computational times to achieve reliable results. In order to address these challenges, we propose a more compact network which is customized to classify cancer subtypes with lower computation time and memory complexity. This model is based on EfficientNet topology, but it is tailored for classifying histopathology images. The utilized model is evaluated over three tumor types brain, lung, and kidney from The Cancer Genome Atlas (TCGA) public repository. Since the pre-trained EfficientNet works properly with the specific size of images, an effective approach is proposed to adjust the size of input images. The proposed model can be trained with a much smaller training set for applications such as image search that require robust and compact representations. The results show that the proposed model, compared to state-of-the-art models, i.e., KimiaNet, can classify cancer subtypes more accurately and provides superior results. In addition, the proposed model achieves memory and computational efficiency in the training phase and is a more compact deep topology compared to KimiaNet.

关键词： EfficientNet Patch Extraction Histopathology images Classification image Search KimiaNet image Representation Deep Neural Network

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Adaptive Multiple Subtraction Based on an Accelerating Iterative Curvelet Thresholding Method

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ieee TRANSACTIONS ON image processing 2021年 30卷 806-821页

作者： Jiang, Bowu Lu, Wenkai Tsinghua Univ Inst Artificial Intelligence THUAI State Key Lab Intelligent Technol & Syst Beijing Natl Res Ctr Informat Sci & Technol BNRis Beijing 100084 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

In the seismic exploration, recorded data contain primaries and multiples, where primaries, as signals of interest, can be used to image the subsurface geology. Surface-related multiple elimination (SRME), one important class of multiple attenuation algorithms, operates in two stages, multiple prediction and subtraction. Due to the phase and amplitude errors in the predicted multiples, adaptive multiple subtraction (AMS) is the key step of SRME. The main challenge of this technique resides in removing multiples without distorting primaries. The curvelet-based AMS methods, which exploit the sparsity of primary and multiple in curvelet domain and the misfit between the original and estimated signals in data domain, have shown outstanding performances in real seismic data processing. These methods are realized by using the iterative curvelet thresholding (ICT), which has heavy computation burden since it includes two forward/inverse curvelet transform (CuT) pairs in each iteration. To ameliorate the computational cost, we propose an accelerating ICT method by exploiting the misfit between the original and estimated signals in curvelet domain directly. Since the proposed method only needs do one forward/inverse CuT pair, it is faster than the traditional ICT method. Considering that the error of the predicted multiple is frequency-dependent, we furthermore introduce the joint constraints within different frequency bands to stabilize and improve the multiple attenuation. Synthetic and field examples demonstrate that the proposed method outperforms the traditional ICT method. In addition, the proposed method has shown to be suitable for refining other AMS methods' results, yielding a SNR improvement of 0.5-2.8 dB.

关键词： Curvelet transform geophysical signal processing sparsity iterative thresholding signal separation

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Gradient-based optical flow: A critical review

Gradient-based optical flow: A critical review

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5th International symposium on signal processing and Its Applications, ISSPA 1999

作者： Mesbah, Mostefa Signal Processing Research Centre Queensland University of Technology GPO Box 2343 Brisbane QLD 4001 Australia

ISBN: (纸本)1864354518

Optical flow, or the distribution of the apparent movement of the brightness pattern in an image, proved to be an important tool in image sequence analysis. A class of techniques that received a special interest for its simplicity and computational efficiency is the one based on the idea of conservation of image intensity. This class of techniques is known as the gradient-based techniques and is composed of two sub-classes, namely, global and local. This paper presents a critical review from the theoretical point of the main directions within the global subclass. © 1999 ieee.

关键词： Optical flows

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PLh transform and its application to image processing

PLh transform and its application to image processing

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1991 ieee International symposium on Circuits and Systems Part 4 (of 5)

作者： Nohara, Kazuo Dept of Electron Univ of Osaka Prefecture Sakai Osaka Japan

New piecewise-linear basis functions called PLh functions are proposed. Using the PLh functions a new digital signal processing transform, PLh transform, is derived. The PLh transform has an attractive feature of the economy of computational effort both in computation time and in storage size. Thus the new transform is suitable for image processing and other applications in which a large number of data need to be processed. Application of the PLh transform to edge detection of two dimensional image is also discussed.

关键词： image processing

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Leveraging Lanczos Algorithm for Computation of Eigenbasis in Type i Discrete Sine Transform 20

Leveraging Lanczos Algorithm for Computation of Eigenbasis i...

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20th CSI International symposium on Artificial intelligence and signal processing, AISP 2024

作者： Raeisi, Mehrnaz Yazdanpanah, Taher Bardi, Ali Bagheri Persian Gulf University Facalty of Intelligent Systems Engineering and Data Science Boushehr*** Iran

ISBN: (纸本)9798350383942

The main contribution lies in presenting an application of the Lanczos algorithm to provide an eigenbasis for a specific type of discrete Sine transform, referred to the signal processing literature as DST of type one. This method, suggesting a new approach, opens up new possiblilities for finding the eigenbasis of other discrete trigonometric transforms, which serve as the key tool in image and video compression. © 2024 ieee.

关键词： image compression

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A Method of Identifying and Locating Encoded Artificial Points Automatically in Close Range Digital Photogrammetry

A Method of Identifying and Locating Encoded Artificial Poin...

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ieee 5th International Conference on Advanced computational intelligence (ICACI)

作者： Wang, Yongwang Wu, Yiming Zhao, Xiaojin Yao, Zhen Li, Chunyan Chinese Acad Sci Xian Inst Opt & Precis Mech Xian 710119 Peoples R China

ISBN: (纸本)9781467317443

Using coding artificial point can match the homonymy points during multiple images automatically in the photogrammetry. A method of identifying and locating 8 bits encoded points automatically has been presented in this paper. The experimental results show that the accuracy of center coordinate of encoding point reaches sub-pixel level. And decoding method is simple. The robust of decoding and recognition rate is high. So it can meet the requirements of close range photogrammetry fully.

关键词： cameras image coding photogrammetry signal processing equipment spatial variables measurement

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Automated Blood Vessel Segmentation of Fundus images Using Region Features of Vessels

Automated Blood Vessel Segmentation of Fundus Images Using R...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Fan, Zhun Lu, Jiewei Rong, Yibiao Shantou Univ Dept Elect Engn Guangdong Prov Key Lab Digital Signal & Image Pro Shantou 515063 Guangdong Peoples R China Shantou Univ Dept Elect Engn Shantou 515063 Guangdong Peoples R China

ISBN: (纸本)9781509042401

This paper proposes a novel and simple unsupervised vessel segmentation algorithm using fundus images. At first, the green channel of a fundus image is preprocessed to extract a binary image after the isotropic undecimated wavelet transform, and another binary image from the morphologically reconstructed image. Secondly, two initial vessel images are extracted according to the vessel region features for the connected regions in binary images. Next, the regions common to both initial vessel images are extracted as the major vessels. Then all remaining pixels in two initial vessel images are processed with skeleton extraction and simple linear iterative clustering. Finally the major vessels are combined with the processed vessel pixels. The proposed algorithm outperforms its competitors when compared with other widely used unsupervised and supervised methods, which achieves a vessel segmentation accuracy of 95.8% and 95.8% in an average time of 9.7s and 14.6s on images from two public datasets DRIVE and STARE, respectively.

关键词： Binary images

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Effective implementation of ring artifacts removal filters for synchrotron radiation microtomographic images

Effective implementation of ring artifacts removal filters f...

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8th International symposium on image and signal processing and Analysis (ISPA)

作者： Brun, Francesco Accardo, Agostino Kourousias, George Dreossi, Diego Pugliese, Roberto Univ Trieste Dept Engn & Architecture Via A Valerio 10 I-34137 Trieste Italy Eletra Sincrotrone Trieste S CpA I-34149 Trieste Italy

ISBN: (纸本)9789531841948;9789531841870

The presence of ring artifacts in X-ray computed microtomography affects the qualitative and quantitative analyses of the reconstructed images. Although digital image processing approaches to ring artifacts removal via direct filtering of the reconstructed images exist, in synchrotron radiation microtomography this issue is usually faced during the actual reconstruction process by de-striping the sinogram image. In this work different de-striping algorithms are discussed and preliminary compared using a suitably created test image as well as actual imaged data. Because of the increasing need for fast reconstruction workflows, details of the implementation and the related computational aspects are also considered. Moreover, the hardware and software solution developed and deployed for the SYRMEP (SYnchrotron Radiation for MEdical Physics) microtomographic beamline of the Italian synchrotron radiation facility (Elettra - Sincrotrone Trieste S.C.p.A) is presented. This solution is based on a high-performance computing (HPC) cluster with the Oracle Grid Engine distributed resource management (DRM) system and Python code that takes advantage of the NumPy and SciPy libraries.

关键词： computerised tomography diagnostic radiography filtering theory image reconstruction medical image processing

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The performance analysis of image fusion algorithm

The performance analysis of image fusion algorithm

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1st International symposium on computational intelligence and Design

作者： Zhao, Chunling Ding, Quanxin Lie, Jianxun Key Lab Fire Control Technol Luoyang 471009 Peoples R China Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China

ISBN: (纸本)9780769533117

The property of Multiscale transform can be used to decompose a complex and highly correlated problem into a set of irrelevant or less correlated problems, which is very useful for processing the information of images for the purpose of fusion. In this paper, two representative multiscale image fusion methods, namely the Laplacian pyramid(LP) and the discrete wavelet transform(DWT), have been studied. The study is focused on the influence of the number of level, fusion rules and wavelet bases to the fusion performance for multi focus images fusion, since this type of studies was seldom proposed in previous research. The DWT is generally thought more powerful than the LP but the comparison of the fusion performance indicates that LP outperforms DWT

关键词： Discrete wavelet transforms

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