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An improved KPLS-KELM method for breast cancer detection 9

An improved KPLS-KELM method for breast cancer detection

9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

作者： Bacha, Sawssen Taouali, Okba Liouane, Noureddine National Engineering School of Monastir Research Laboratory of Automation Signal Processing and Image Monastir5019 Tunisia University of Tabuk Faculty of Computers and Information Technology Department of Computer Engineering Tabuk Saudi Arabia

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

The conception of a computer-Aided Diagnosis system (CAD) using Artificial Intelligence (AI) is a hot topic in the domain of medical diagnosis. Recently, many approaches have been developed. In the proposed work, a novel classification technique from mammograms based on Kernel Extreme Learning Machine (KELM) and Kernel Partial Least Square (KPLS) method is introduced. The suggested algorithm first used the KPLS algorithm to extract features from the images. The extracted characteristics were then sent to the KELM classifier. In order to improve the generalization of the proposed approach, the cross-validation strategy was used. The simulation results were tested on the Mammographic image Analysis Society (MIAS) dataset and measured using accuracy, F score, sensitivity, and specificity analysis. These results were compared to existing approaches tested on the same dataset and it was observed that the proposed work is the most efficient. © 2022 IEEE.

关键词： Mammography

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Reduced CAD system for classifications of cancer types based on microarray gene expression data 9

Reduced CAD system for classifications of cancer types based...

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9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

Cancer is one of the deadliest diseases for human health. The classification of cancers poses many challenges in biomedical research because it allows an accurate and effective diagnosis and guarantees the success of medical treatments. In this paper, a new reduced computer-Aided Diagnosis (CAD) system is implemented under the MATLAB (version R2016a) environment to classifying four cancer subtypes. The results of the experiment are carried out with four sets of baseline data on the expression of cancer genes. To validate the proposed CAD system, different performance metrics such as sensitivity, specificity, accuracy, and F-Score are measured. The experimental analysis justifies the effectiveness of the proposed model and, therefore, this model can be considered as an effective tool to help radiologists for a better diagnosis. © 2022 IEEE.

关键词： Gene expression

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Age classification based on gait using HMM

Age classification based on gait using HMM

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2010 20th International Conference on Pattern Recognition, ICPR 2010

作者： Zhang, De Wang, Yunhong Bhanu, Bir Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing 100191 China Center for Research in Intelligent Systems University of California Riverside CA 92521 United States

ISBN: (纸本)9780769541099

In this paper we propose a new framework for age classification based on human gait using Hidden Markov Model (HMM). A gait database including young people and elderly people is built. To extract appropriate gait features, we consider a contour related method in terms of shape variations during human walking. Then the image feature is transformed to a lower-dimensional space by using the Frame to Exemplar (FED) distance. A HMM is trained on the FED vector sequences. Thus, the framework provides flexibility in the selection of gait feature representation. In addition, the framework is robust for classification due to the statistical nature of HMM. The experimental results show that video-based automatic age classification from human gait is feasible and reliable. © 2010 IEEE.

关键词： Hidden Markov models

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Semi-automated extraction of retinal blood vessel network with Bifurcation and crossover points 12th

Semi-automated extraction of retinal blood vessel network wi...

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12th International Symposium on Visual Computing, ISVC 2016

作者： Nougrara, Z. Kihal, N. Meunier, J. Faculty of Mathematics and Computer Science Department of Mathematics University of Sciences and Technology of Oran Oran Algeria Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB Algiers Algeria Department of Computer Science and Operations Research University of Montreal Montreal Canada

ISBN: (纸本)9783319508313

Among different retinal analysis tasks, blood vessel extraction plays an important role as it is often the first essential step before any measurement can be made for various applications such as biometric authentication or diagnosis of retinal vascular diseases. In this paper, we present a new method for extraction of blood vessel network with its nodes (bifurcation and crossover points) from retinal images. The first step is to identify pixels with homogeneous vessel elements with a set of four directional filters. Then another step is applied to extract local linear components assuming that a vessel is a set of short linear segments. Through an optimization process this information is combined to extract the vessel network and its nodes. The proposed algorithm was tested on the publicly available DRIVE retinal fundus image database. The experimental results show good precision, recal. The proposed algorithm was tested on the publicly available DRIVE retinal fundus image database. The experimental results show good precision, recall and F-measure compared to ground truth and a state-of-the-art algorithm for the same dataset. © Springer International Publishing AG 2016.

关键词： Blood vessels

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Real-Time 6-DoF Object Pose Estimation Network Based on 2D-3D Coordinate Correspondence 3rd

Real-Time 6-DoF Object Pose Estimation Network Based on 2D-3...

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3rd International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2023

作者： Li, Shuai Chen, Jinlong Yang, Minghao Su, Jianhua Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guangxi Guilin541004 China Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guangxi Guilin541004 China Beijing100190 China HuaiRou Beijing101400 China Beijing100190 China

ISBN: (纸本)9789819721993

Object 6D pose estimation is essential for a variety of applications, including autonomous driving, robotic manipulation, and automated harvesting. Due to the influence of different lighting conditions and occlusions, objects with different poses may exhibit significant variations in appearance in different views. This makes the estimation of the 6D pose of objects from a single RGB image a challenging task. This paper proposes a deep learning network capable of simultaneously detecting and estimating the 6D pose (3D rotation + 3D translation) of target objects. As establishing a large-scale dataset using real data is extremely challenging, this paper introduces an automatic collection scheme based on virtual data generated from real images. We conducted experiments on the generated astronaut dataset using our data collection scheme for 6D pose estimation. The experimental results show that the accuracy of 6D pose estimation based on the ADD metric is 96%. Therefore, this method has significant potential and can be extended to other downstream tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning

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Text line detection based on mutation analysis

Text line detection based on mutation analysis

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2013 5th International Conference on Computational and Information Sciences, ICCIS 2013

作者： Hou, Dewen Wang, Xichang Liu, Jiang Chen, Xia Key Laboratory for Distributed Computer Software School of Information and Science Engineering Shandong Normal University Shandong China Shandong Oumasoft Co. Ltd Research Institute of Digital Image Processing Shandong China

ISBN: (纸本)9780769550046

A text line detection method based on wavelet transformation and mutation analysis is proposed in this paper. First the character density image is acquired from the input document image by the project function with strips, and then the density image is analyzed by wavelet transformation where the Gaussian or its derivative function is used as the wavelet basis. The local peak positions indicate the line texture which will be continuous and single pixel. Because of the statistical properties of project function and wavelet transformation of mutations signal detection, this algorithm is not sensitive to noise and warped distortions. Experiments show that this algorithm is accurate and robust. © 2013 IEEE.

关键词： Signal analysis

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Parameters For Geometric Fidelity Of Geocoded Sar Products

Parameters For Geometric Fidelity Of Geocoded Sar Products

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： G. Schreier J. Raggam D. Strobl DLR WT-DA German Aerospace Research Establishment Oberpfaffenhofen Germany Joanneum Research Institute of Image Processing and Computer Graphics Graz Austria

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Evaluating the similarity degree of digital watermarks

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Journal of Information and Computational Science 2010年第6期7卷 1417-1422页

作者： Li, Li Ruan, Liuzhao Zhang, David Institute of Computer Graphics and Image Processing Hangzhou Dianzi University Hangzhou 310018 China Centre for Multimedia Signal Processing Biometrics Research Centre Hong Kong Polytechnic University Hong Kong

The popular formulas currently used to evaluate the similarity of digital watermarks have serious drawbacks: when the similarity degree is 1, the watermarks are not unique. This paper firstly analyze the drawbacks in the popular formulas. Then proposes a new formula similarity degree, which eliminates the shortcomings of the existing formulas and overcome the lack of uniqueness in theory. From the experiment results the new formula not only does well in evaluating the watermark's similarity degree, also is in good accordance with visual perception. © 2010 Binary Information Press.

关键词： Digital watermarking

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Morphological geodesic active contour based automatic aorta segmentation in thoracic CT images

Morphological geodesic active contour based automatic aorta ...

引用

International Conference on computer Vision and image processing, CVIP 2016

作者： Dasgupta, Avijit Mukhopadhyay, Sudipta Mehre, Shrikant A. Bhattacharyya, Parthasarathi Computer Vision and Image Processing Laboratory Department of Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur West Bengal721302 India Institute of Pulmocare & Research KolkataWest Bengal700156 India

ISBN: (纸本)9789811021060

Automatic aorta segmentation and quantification in thoracic computed tomography (CT) images is important for detection and prevention of aortic diseases. This paper proposes an automatic aorta segmentation algorithm in both contrast and non-contrast CT images of thorax. The proposed algorithm first detects the slice containing the carina region. Circular Hough Transform (CHT) is applied on the detected slice to localize ascending and descending aorta (circles with lowest variances) followed by a morphological geodesic active contour to segment the aorta from CT stack. The dice similarity coefficients (DSC) between the ground truth and the segmented output were found to be 0.8845 ± 0.0584 on LIDC-IDRI dataset. © Springer Science+Business Media Singapore 2017.

关键词： image segmentation

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Construction of practical teaching system for integration of specialism and innovation based on virtual simulation technology 29th

Construction of practical teaching system for integration of...

引用

29th National Conference on computer Science Technology and Education, NCCSTE 2019

作者： Wang, Yangping Dang, Jianwu Yong, Jiu Wang, Wenrun Yue, Biao School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou China National Computer Science and Technology Experimental Teaching Demonstration Center Lanzhou Jiaotong University Lanzhou China Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics and Image Processing Lanzhou China

ISBN: (纸本)9789811553899

The practical teaching for the majors of rail transit in colleges and universities involves a large number of high-cost, high-consumption, large-scale or comprehensive training. It will often encounter high-risk or extreme environment, inaccessible or irreversible operation, which seriously affects the cultivation of students professional engineering ability. In this paper, a practical teaching system based on virtual simulation technology is constructed for rail transit specialty. The system integrates the professional advantages and practical platform in the university, develops virtual simulation experimental teaching resources and practical teaching cases, and enables students to carry out "independent, cooperative and inquiry" learning in an open, safe, realistic and interactive virtual environment. This system will enhance students professional engineering practice ability and innovation ability, promote the training level of rail transit professionals and the overall quality of students. And for students, it can achieve the goal of strengthening the basic principles of curriculum, training design and research thinking, and enhancing innovation and entrepreneurship ability. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Students

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