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检索条件"任意字段=International Conference on Soft Computing and Pattern Recognition"

共 7572 条记录，以下是841-850 订阅

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Poisson and Logistic Regressions for Inhomogeneous Multivariate Point Processes: A Case Study in the Barro Colorado Island Plot 6th

Poisson and Logistic Regressions for Inhomogeneous Multivari...

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6th international conference on soft computing in Data Science (SCDS)

作者： Husain, Ahmad Choiruddin, Achmad Inst Teknol Sepuluh Nopember Dept Stat Surabaya Indonesia

ISBN: (纸本)9789811673344;9789811673337

This study aims to extend the estimating equations based on the Poisson and logistic regression likelihoods to model the intensity of a multivariate point process. The proposed approaches result in a framework equivalent to the estimation procedure for generalized linear model. The estimation is different from the existing methods where repetition independently with respect to the number of types of point process is obliged. Our approach does not require repetition and hence could be computationally faster. We implement our method to analyze the distribution of 9-species of trees in the Barro Colorado Island rainforest with respect to 11-environmental variables.

关键词： Logistic regression Multivariate point pattern Poisson regression

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Utilizing AI to Advance Data Science Research

Utilizing AI to Advance Data Science Research

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international conference on computing and Networking Technology (ICCNT)

作者： Bharat Bhushan Akhilendra Pratap Singh Sonal Sharma K Divya Ratnmala N. Bhimanpallewar Ravi Kant Pareek Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Engineering Jain (Deemed to be University) Bangalore Karnataka India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Information Technology Vishwakarma Institute of Technology Pune INDIA Department of Civil Engineering Vivekananda Global University Jaipur India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The emerging field of artificial Intelligence (AI) offers tremendous capability for advancing studies and improvement in the location of data science. AI is capable of automating and enhancing the method of obtaining, organizing, and deciphering records that may growth the accuracy of facts evaluation and strengthen records technological know-how research tasks. This automation can keep time by streamlining responsibilities and loose up researchers’ time to focus on extra complicated components of research. AI can also provide insights into previously unknown records styles, permitting researchers to pursue deeper statistics exploration and find out surprising outputs. Further, AI-based strategies can reveal significant and actionable information from conventional datasets, taking into consideration extra green and correct decisions.

关键词： Automation Accuracy Data science Market research pattern recognition Artificial intelligence Business

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An Enhanced Local Descriptor (ELD) for Face recognition 3

An Enhanced Local Descriptor (ELD) for Face Recognition

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3rd international conference on Inventive Research in computing Applications, ICIRCA 2021

作者： Karanwal, Shekhar Graphic Era Deemed to Be University Cse Department Uttarakhand Dehradun India

ISBN: (纸本)9780738146270

The influence of light changes makes the task of feature extraction more difficult for the local descriptors. Most of local descriptors sacrifices their performance in harsh lightning variations. Some uses pre-processing approach some uses gradient based methods (with local descriptors) to improve accuracy. In this work, a novel Enhanced Local Descriptor (ELD) is introduced by taking advantages of two well behaved descriptors in harsh lightning changes. These 2 are Compound Local Binary pattern (CLBP) Median Robust Extended LBP based on Neighborhood Intensity (MRELBP-NI). CLBP is characterized by Sign Magnitude details, and MRELBP-NI is characterized by Median Mean statistics. Both of them are very essential in controlling harsh light variations. By merging features of both a discriminant descriptor ELD is gained. FLDA is taken further for size contraction SVMs is used for matching. ELD achieves stupendous outcomes on Extended Yale B (EYB) dataset. ELD wholly outstrip the singly implemented descriptors many methods from literature. ELD secure best accuracy of 93.42%. There is no pre-processing the gradient based methods are used. © 2021 IEEE.

关键词： Local binary pattern

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ScrapeAI: A Multi-Modal Approach to Detect Dark patterns

ScrapeAI: A Multi-Modal Approach to Detect Dark Patterns

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international conference on computing and Networking Technology (ICCNT)

作者： Pruthvi S Kodmurgi Srihari Adiga Srikrshna Parthasarthy R Thanushree Varun Vishwanatha Avabratha Preet Kanwal Prasad B Honnavalli Department of Computer Science & Engineering PES University Bengaluru India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This study proposes a multi-modal architecture to detect dark patterns, leveraging the usage of textual, visual, and temporal contexts. Dark patterns are deceptive elements used in websites and apps that manipulate users into making decisions that benefit the company, often at the expense of the user. In today’s world, with a significant rise in the adoption of technology across the globe, detecting dark patterns becomes important. This study is more focused on the dark patterns in the e-commerce space. We propose using three modules to detect this task, each of which processes different types of data. For textual data, we leverage Large Language Models to detect potential dark patterns. For visual data, we use object detection models to detect any visual cues that might reveal potential dark patterns. For the temporal context, we track and analyze the states of the website. Using these three modules makes our detection process robust and versatile. Furthermore, we created an image dataset Darkpattern-Capture (DPC), which has images of potentially deceptive elements; our object detection models are trained and tested on this dataset.

关键词： Visualization Computational modeling Large language models Object detection Computer architecture Companies Data models pattern recognition Electronic commerce

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Design and implementation of parking system using feature extraction and pattern recognition technique 3rd

Design and implementation of parking system using feature ex...

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3rd international conference on Big-Data and Cloud computing, ICBDCC 2019

作者： Varun Chand, H. Karthikeyan, J. School of Information Technology and Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9789811552847

With the development of industrial automation, there is a growth in number of vehicles resulted to demand of parking space, which is costly in metropolitan areas. For finding vacant parking facilities, drivers spend more time on roads which causes additional fuel consumption, traffic congestion, and pollution. For addressing parking issues, this study presents a novel framework based on real-time monitoring and image recognition technique. The major contribution of this study is threefold: Initially, analyze the input images which are composed from the event recorders in currently driving cars toward determining the parking spaces availability. Second, this image is preprocessed using a hybrid algorithm, which is a combination of feature extraction (local binary pattern) and pattern recognition (Bayes classifier) technique. With the help of image recognition technique, it can track the availability of parking spaces with images on weather condition. Also, image filtering technique is applied to remove noisy information;hence, we can detect the park lots in any weather condition. Third, consider the utilization of parking facilities, distance to the recommended parking facility, and time to reach from source to destination. Finally, the performance of the suggested technique is validated by the measure of classification accuracy, precision, recall, and f-measure. © Springer Nature Singapore Pte Ltd 2021.

关键词： Feature extraction

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Two Confirmation Bias Models for Analyzing Biased pattern Classification Processes 11

Two Confirmation Bias Models for Analyzing Biased Pattern Cl...

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Joint 11th international conference on soft computing and Intelligent Systems and 21st international Symposium on Advanced Intelligent Systems (SCIS-ISIS)

作者： Fujimoto, Kazunori Kindai Univ Fac Business Adm Osaka Japan

ISBN: (纸本)9781728197326

This paper presents a mathematical model of the two types of the confirmation biases, Z- and E-types, for analyzing the pattern classification processes where the decision maker suffers from a confirmation bias. Persons suffering from Z-type receive a signal and perceive it incorrectly as a different signal with a certain probability, while those suffering from E-type fail to receive a signal with a certain probability. In contrast to our previous models, which assume the signals and the options basically as the binary random variables, the models presented in this paper are based on the pattern classification processes, where (i) the state of world that maximizes the posterior probability is selected from more than or equal to two possible states and (ii) the time-series of the continuous-valued signals are used for the probability calculation. The proposed models enable us to analyze the dynamical properties of the confirmation biases in the context of the pattern classification processes.

关键词： cognitive model cognitive bias confirmation bias pattern classification

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Automated Classification of Wheat Varieties Using soft computing Techniques 8th

Automated Classification of Wheat Varieties Using Soft Compu...

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8th international conference on Cognition and recognition, ICCR 2021

作者： Chini, Shridhar Yakkundimath, Rajesh Malvade, Naveen N. Gadagin, Nagaraj Department of Computer Science and Engineering K. L. E. Institute of Technology Karnataka Hubballi580030 India Department of Information Science and Engineering Smt. Kamala and Sri. Venkappa M. Agadi College of Engineering and Technology Karnataka Lakshmeshwar582116 India Department of Information Science and Engineering K. L. E. Institute of Technology Karnataka Hubballi580030 India Visvesvaraya Technological University Karnataka Belagavi590018 India

ISBN: (纸本)9783031224041

Identification of wheat seed varieties is crucial for meeting market demands. The automated image-based approaches proposed in this paper are used to identify wheat seeds from three different types, namely Canadian, Rosa, and Kama. The effective classification methods, namely Artificial Neural Network with Back Propagation (BPNN), Support Vector Machine (SVM), and k-Nearest Neighbor (k-NN) are adopted for wheat variety identification. The classifiers are trained using morphological features derived from the singleton wheat kernel images. The k-NN, BPNN, and SVM classifiers have yielded the classification efficiencies of 94.23%, 90.35% and 83.57%, respectively. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Backpropagation

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Development of a Predictive System for Customer Buying pattern Using Apriori Algorithm

Development of a Predictive System for Customer Buying Patte...

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IEEE international conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Peter Oluwasheyi Oluokun Gbemisola Olutosin Babalola Adebusola Modupeola Tope-Oke Stephen Eyitayo Obamiyi Olalekan Ismail Araoye Computer Science Department Afe Babalola University Ado-Ekiti Ado-Ekiti Nigeria Department of Computer Science The Federal Polytechnic Ado-Ekiti Ado-Ekiti Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

A lot of retailers face the challenge of how to understand their customers’ buying habits, and this makes stocking products, arrange items on shelves, and making customers to come back again a difficult task. Without understanding what the customer typically wants to buy, retail stores can miss out on opportunities to increase sales and improve customer satisfaction. To address this, this study developed a system using the Apriori algorithm to analyze past shopping data from a supermarket. The developed system identifies patterns in the items of customers that are frequently bought together. This allows the business to predict future purchases. By using these method, stores can now manage their stock better to create better marketing strategies, and to improve their customers overall shopping experience. The results that were obtained from this study also show that the system can help businesses stay competitive by understanding customer needs and acting on them more effectively.

关键词： Humanities Consumer behavior Itemsets Customer satisfaction Inventory management Prediction algorithms pattern recognition Faces Business

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international conference on Image Processing and Capsule Networks, ICIPCN 2020

International Conference on Image Processing and Capsule Net...

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international conference on Image Processing and Capsule Networks, ICIPCN 2020

ISBN: (纸本)9783030518585

The proceedings contain 72 papers. The special focus in this conference is on Image Processing and Capsule Networks. The topics include: Developing a framework to identify potential firms for job assignment;developing a framework for trend prediction of stocks prices;machine learning based diagnosis of alzheimer’s disease;iot based vehicle (car) theft detection;emg signal classification with effective features for diagnosis;eye fatigue algorithm for driver drowsiness detection system;an analytical approach for recognizing the occupational gender bias in the data systems;development of an algorithm for vertebrae identification using speeded up robost features (surf) technique in scoliosis x-ray images;highly protective framework for medical identity theft by combining data hiding with cryptography;improving the prediction accuracy of asd using class imbalance mitigation technique;stock price prediction based on technical indicators with soft computing models;credit card fraud detection technique based on hybrid classification;improved fast block matching motion estimation using multiple frames;efficient framework for identification of soybean disease using machine learning algorithms;brain image visualization;a framework for degraded kannada character recognition;classification of soybean diseases using pre-trained deep convolutional neural networks;feedforward back propagation neural network (ffbpnn) based approach for the identification of handwritten math equations;comparison of machine learning algorithms for smart license number plate detection system;ritchie’s smart watch data analytics and visualization;sentiment analysis for product rating using classification;face recognition system using a hybrid scale invariant feature transform based on local binary pattern;sign language identification using image processing techniques;foreword;preface.

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A New Head Pose Estimation Method Using Vision Transformer Model 2021

A New Head Pose Estimation Method Using Vision Transformer M...

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7th international conference on computing and Artificial Intelligence, ICCAI 2021

作者： Ling, Xufeng Wang, Dong Yang, Jie Shanghai Normal University Tianhua College Ai School No. 1661 North Sheng Xin Road China Institute of Image Processing and Pattern Recognition Shanghai Normal University Tianhua College China

ISBN: (纸本)9781450389501

In this paper, a self-attention-based Vision Transformer (VIT) method is introduced into estimate human head pose parameters. Firstly, the head pose image is divided into 32X32 patches, each image patch is regarded as a word, and the whole image is treated as a paragraph composed of n words by the VIT. Image recognition can be regarded as the semantic recognition of this paragraph. Next, we redesign the regression VIT to estimate the parameters. Then we select Head Pose Database as the training and validation dataset. The VIT is trained on the enhanced and normalized dataset. Finally, the trained VIT is used to regress the head pose parameters on testing samples. Experimental results show that VIT has high accuracy and good generalization ability for head pose estimation. © 2021 ACM.

关键词： Image recognition

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