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检索条件"任意字段=1st International Conference on Image Processing Machine Learning and Pattern Recognition"

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A Comparative Analysis of machine learning Algorithms for Credit Card Fraud Detection 1

A Comparative Analysis of Machine Learning Algorithms for Cr...

引用

1st IEEE international conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024

作者： Raturi, Anshul Pal, Maahi Narang, Harshit Vats, Satvik Sharma, Vikrant Yadav, Satya Prakash Graphic Era Hill University Computer Science and Engineering Dehradun India Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350371802

The introduction and availability of credit cards in the modern world have transformed the transaction or payment process from the typical cash payment to modernized cashless payment. Due to the rapid growth and development of e-commerce platforms and improved accessibility to the Internet, a notable increase in the use of credit cards for purchases has occurred. Regrettably, this surge has also been accompanied by an upswing in fraudulent activities, demanding heightened vigilance. The phrase 'credit card fraud' describes a wide rangeof illicit actions in which individuals utilize credit card details to get money through deception. Effectively combating this multifaceted threat necessitates a deep understanding of the mechanisms involved in identifying and preventing credit card fraud. Since sophisticated techniques for preventing and detecting fraud have been developed over time, the effects of credit card fraud have decreased, and the sector has become more stable. While previous research in this field has largely depended on machine learning algorithms such as random forest and logistic regression for credit card fraud detection, this study introduces a groundbreaking approach. We present the use of convolutional Neural network (CNN) models, a method commonly used in image processing and image recognition, to evaluate heatmaps generated from credit card transaction data. © 2024 IEEE.

关键词： image recognition

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image Retrieval Using Schwarz Representation

Image Retrieval Using Schwarz Representation

引用

4th international conference on Computer Science and Informatics, JCIS 1998, 1st international Workshop on High Performance, 1st international Workshop on Computer Vision, pattern recognition and image processing Volume 4

作者： Ding, Xianfeng Yang, Qing Ma, SongDe Natl. Lab. of Pattern Recognition Institute of Automation Chinese Academy of Sciences P.O.Box 2728 Beijing 100080 China

Color and shape retrieval are two important retrieval methods in content based image database. Recently we developed a new method which use Schwarz representation to match one-dimensional signal. It can obtain closed form match function and similarity measure without optimization. Color histogram is a natural one-dimensional signal. Contour can be converted into onedimensional signal using its tangent angle. In this paper, we introduce this method to image retrieval based on the color and shape, respectively. Experimental results show its efficiency and accuracy.

关键词： Content based retrieval

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Wavelet image Compression using Pruned Quadtrees

Wavelet Image Compression using Pruned Quadtrees

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作者： Morales, Eduardo Shih, Frank Y. Department of Computer Science New Jersey Institute of Technology Newark NJ 07102

The paper is to cluster the significant coefficients and then efficiently represent the shape of the clusters through quadtrees. A pruning algorithm is presented for those especial cases where the encoded representati... 详细信息

关键词： image compression

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1st international conference on Computational Intelligence for Engineering and Management Applications, CIEMA 2022

1st International Conference on Computational Intelligence f...

引用

1st international conference on Computational Intelligence for Engineering and Management Applications, CIEMA 2022

ISBN: (纸本)9789811984921

The proceedings contain 68 papers. The special focus in this conference is on Computational Intelligence for Engineering and Management Applications. The topics include: strokes-Related Disease Prediction Using machine learning Classifiers and Deep Belief Network Model;analysis and Detection of Fraudulence Using machine learning Practices in Healthcare Using Digital Twin;prediction and Analysis of Polycystic Ovary Syndrome Using machine learning;feature Selection for Medical Diagnosis Using machine learning: A Review;convolutional Neural Network Architectures Comparison for X-Ray image Classification for Disease Identification;Secure Shift-Invariant ED Mask-Based Encrypted Medical image Watermarking;fusion-Based Feature Extraction Technique Using Representation learning for Content-Based image Classification;a Comparative study on Challenges and Solutions on Hand Gesture recognition;design a Computer-Aided Diagnosis System to Find Out Tumor Portion in Mammogram image with Classification Technique;a Novel Soft-Computing Technique in Hydroxyapatite Coating Selection for Orthopedic Prosthesis;performance Analysis of Panoramic Dental X-Ray images Using Discrete Wavelet Transform and Unbiased Risk Estimation;efficient image Retrieval Technique with Local Edge Binary pattern Using Combined Color and Texture Features;texture and Deep Feature Extraction in Brain Tumor Segmentation Using Hybrid Ensemble Classifier;A Systematic Review on Sentiment Analysis for the Depression Detection During COVID-19 Pandemic;vehicular Adhoc Networks: A Review;the Data Vortex Switch Architectures—A Review;survey on Genomic Prediction in Biomedical Using Artificial Intelligence;a Brief Review on Right to Recall Voting System Based on Performance Using machine learning and Blockchain Technology;sentiment Analysis Techniques: A Review;network Traffic Classification Techniques: A Review;remote Production Monitoring System.

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A relational distance-based framework for hierarchical image understanding

A relational distance-based framework for hierarchical image...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Antanas, Laura Van Otterlo, Martijn Jośe Oramas, M. Tuytelaars, Tinne De Raedt, Luc Katholieke Universiteit Leuven Leuven Belgium

ISBN: (纸本)9789898425980

Understanding images in terms of hierarchical and logical structures is crucial for many semantic tasks, including image retrieval, scene understanding and robot vision. This paper combines compositional hierarchies, qualitative spatial relations, relational instance-based learning and robust feature extraction in one framework. For each layer in the hierarchy, substructures in the images are detected, classified and then employed one layer up the hierarchy to obtain higher-level semantic structures, by making use of qualitative spatial relations. The approach is applied to street view images. We employ a four-layer hierarchy in which subsequently corners, windows and doors, and individual houses are detected.

关键词： Edge detection

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A Hybrid Approach for Hyper Spectral image Segmentation Using SMLR and PSO Optimization 1st

A Hybrid Approach for Hyper Spectral Image Segmentation Usin...

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1st international conference on Recent Trends in image processing and pattern recognition (RTIP2R)

作者： Karchi, Rashmi P. Nagesh, B. K. Bharathiar Univ Deaprtment Comp Sci Coimbatore 641046 Tamil Nadu India SIT Dept Comp Sci & Engn Mangalore 574143 Karnataka India

ISBN: (纸本)9789811048593;9789811048586

A hybrid approach for hyperspectral image segmentation is presented in this paper. The contribution of the proposed work is in two folds. First, learning of the class posterior probability distributions with Quadratic Programming or joint probability distribution by employing sparse multinomial logistic regression (SMLR) model. Secondly, estimation of the dependencies using spatial information and edge information by minimum spanning forest rooted on markers by acquiring the information from the first step to segment the hyper spectral image using a Markov Random field segments. The particle swarm optimization (PSO) is performed based on the SMLR posterior probabilities to reduce the large number of training data set. The performance of the proposed approach is illustrated in a number of experimental comparisons with recently introduced hyperspectral image analysis methods using both simulated and real hyper spectral data sets of Mars.

关键词： Feature selection Hyperspectral image classification Particle swarm optimization Spatio-spectral analysis

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Automatic Tomato Leaf Diseases Classification and recognition using Transfer learning Model with image processing Techniques 1

Automatic Tomato Leaf Diseases Classification and Recognitio...

引用

1st international conference on Smart Technologies Communication and Robotics, stCR 2021

作者： Hemalatha, A. Vijayakumar, J. Bharathiar University Department of Electronics and Instrumentation Tamilnadu Coimbatore India

ISBN: (纸本)9781665418065

In agriculture, manual approaches to recognize tomato plant diseases are often time-consuming. The diseases spread throughout the plant, affecting the quality and yield. In this research work, a transfer learning model (DenseNet201) was designed to conduct the symptom-wise recognition of three tomato diseases such as leaf mold, early blight, and late blight are compared with healthy leaves. The transfer learning model has been trained, tested, and validated. Our trained model can recognize the category of disease. Once the images are classified, the regions are segmented, and features are extracted using k-means clustering and ORB keypoints. The transfer learning model achieved an excellent recognition result with an average accuracy of 99.688%. © 2021 IEEE.

关键词： Fruits

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Facial Attractiveness Classification using Deep learning 1

Facial Attractiveness Classification using Deep Learning

引用

1st international conference of the Indonesian-Association-for-pattern-recognition (INAPR)

作者： Anderson, Ricky Gema, Aryo Pradipta Suharjito Isa, Sani M. Bina Nusantara Univ Sch Comp Sci Dept Comp Sci Jakarta 11480 Indonesia Bina Nusantara Univ BINUS Grad Program Dept Comp Sci Comp Sci Jakarta 11480 Indonesia

ISBN: (纸本)9781538694220

Facial attractiveness classification application has many various usabilities, including photo editing, photo beautification, photo grading and dataset labeling. While face attractiveness classification seems to be related to personal preference, building a robust attractiveness classifier is not impossible. There are several studies that have developed a classification system of facial attractiveness using a convolutional neural network and provide satisfactory results. The use of image-net pre-trained convolutional neural network has been largely used by face-related research, yet none of them are related to facial attractiveness. This study aims to compare the famous deep learning architecture, such as VGG, Inception, and ResNet models. This research also aims to analyze the effect of using the Viola-Jones algorithm, as a preprocessing method, to the classification result of the built model. Viola-Jones algorithm will detect faces in image data, and 2 types of cropping will be done to extract the face region from the image, namely loose-crop and tight-crop. This research produces the highest accuracy value of 82.52% by using ResNet50 model and loose-crop preprocessing method.

关键词： Deep learning Facial Attractiveness Face recognition

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The application of BEMD to multi-spectral image fusion

The application of BEMD to multi-spectral image fusion

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5th international conference on Wavelet Analysis and pattern recognition

作者： Xu, Xiangnan Li, Hua Wang, Anna Air Force Aviation University of PLA Collage of Information Science and Engineering Northeastern University

ISBN: (纸本)9781424410651

Multi-spectral linage Fusion is a new research field in image processing. In this paper, for achieving a better fusion result, a image fusion method based on the intensity;-hue-saturation(IHS) Transform and Bidimensional Empirical Mode Decomposition(BEMD) is proposed. Firstly, the multi-spectral image is transformed into IHS component. Secondly, the histogram-matched panchromatic image and intensity component are decomposed into a set of BIMFs respectively by means of BEMD. Thirdly, the new intensity component can be obtained by merging the BIMFs of histogrant-matched panchromatic image and intensity component. Finally, the new intensity, hue, and saturation components are transformed back to RGB. Experimental results show that this new method can preserve the spectral information it? the fusion image;meanwhile, it can merge the spatial details of the panchromatic image.

关键词： image fusion BEMD IHS

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Sufficient statistics Feature Mapping over Deep Boltzmann machine for Detection 22

Sufficient Statistics Feature Mapping over Deep Boltzmann Ma...

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22nd international conference on pattern recognition (ICPR)

作者： Zhang, Chao Li, Xiong Yan, Junchi Chu, stephen Wang, Yu Tian, Chunhua Zhao, Yuming Shanghai Jiao Tong Univ Shanghai 200030 Peoples R China

ISBN: (纸本)9781479952083

As an important and fundamental methodology in the fields of pattern recognition and image processing, learning middle level feature has attracted increasing interest during the recent years, where generative feature mapping has shown highly completive performance in diverse applications. In this paper, a middle level feature representation is proposed based on Deep Boltzmann machine (DBM) and sufficient statistics (SS) feature mapping for detection. In the approach, DBM is employed to model data distribution and the hidden information inferred by DBM together with other informative variables are then exploited by SS to form the middle level features. The features, learnt from data, can be fed to standard classifiers for classification. In order to evaluate the performance of our method, we apply our feature mapping method to two challenging tasks: (1) contour detection through distinguishing border and non-border pixels;(2) sales pipeline prediction, which predicts the winning propensity of the ongoing sales opportunity in the pipeline. In comparison with other leading methods in the literature on the Berkeley Segmentation Dataset and Sales Pipeline Database (SPDB), our proposed algorithm performs favorably against state-of-the-art methods in terms of effectiveness and efficiency.

关键词： Pipelines

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