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image Segmentation Algorithm Based on statistical Properties

Image Segmentation Algorithm Based on Statistical Properties

引用

International conference on Research in Intelligent and Computing in Engineering, RICE 2020

作者： Alwazzan, Mohammed J. Alkhfagi, Alaa O. Alattar, Ashraf M. Al-Hussain University College Karbala Iraq Al-Farahidi University Baghdad Iraq

ISBN: (纸本)9789811575266

image segmentation, a technology that divides images into parts, is an important technique in image processing, and is used in various disciplines, such as remote sensing, medical imaging, and industrial fields. Several methods and known algorithms are used for image segmentation. This paper proposes a new algorithm for image segmentation that is based on statistical properties. The new algorithm depends on colour contrast between regions of the image, and uses a mathematical equation based on statistical properties (the maximum value, minimum value, and standard deviation) to automatically calculate a global threshold. We find that the algorithm successfully performs image segmentation when applied to two different test images. © 2021, Springer Nature Singapore Pte Ltd.

关键词： image segmentation

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Medicinal Plant Classification Using Transfer Learning Through Hybrid Machine Learning and image processing Techniques

Medicinal Plant Classification Using Transfer Learning Throu...

引用

Intelligent Systems for Cybersecurity (ISCS), International conference on

作者： A. Lakshmanarao Pathuri Sudeep Kumar Dighvijay Singh Chauhan M.Sai Venkat Shubham Kumar Raj Department of Information Technology Aditya University Surampalem India Department of IT Aditya University Surampalem India

ISBN: (数字)9798350375237

ISBN: (纸本)9798350375244

Medicinal plants play a crucial role in traditional medicine and healthcare systems worldwide. In this study, we proposed a comprehensive approach for the detection of medicinal plants using a combination of DL features extracted from VGG16 architecture, along with traditional methods encompassing shape, texture, statistical, and color features. Initially, we loaded a dataset of medicinal plant images from Kaggle, providing a diverse and representative collection of species. Next, features from VGG16 extracted for producing a feature vector. Additionally, we augmented these features with traditional methods to create final feature vector. Subsequently, ML models, including SVM, Random Forests, Decision Trees, logistic regression and KNN applied to final dataset to classify medicinal plant species. Through comparative analysis, it is identified the best-performing model as random forest with 98.3% accuracy and 98% of f1 score for medicinal plant classification. The findings shed light on the effectiveness of combining deep learning and traditional feature extraction methods for accurate and reliable medicinal plant detection, offering insights into potential applications in botanical research and healthcare.

关键词： Medicinal plants Support vector machines Accuracy Shape Medical services Feature extraction Vectors

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Bayesian learning via Q-exponential process 23

Bayesian learning via Q-exponential process

引用

Proceedings of the 37th International conference on Neural Information processing Systems

作者： Shuyi Li Michael O'Connor Shiwei Lan School of Mathematical & Statistical Sciences Arizona State University Tempe AZ

Regularization is one of the most fundamental topics in optimization, statistics and machine learning. To get sparsity in estimating a parameter u ∈ ℝd, an ℓq penalty term, ‖u‖q, is usually added to the objective function. What is the probabilistic distribution corresponding to such ℓq penalty? What is the correct stochastic process corresponding to ‖u‖q when we model functions u ∈ Lq? This is important for statistically modeling high-dimensional objects such as images, with penalty to preserve certain properties, e.g. edges in the image. In this work, we generalize the q-exponential distribution (with density proportional to) exp(-1/2|u|q) to a stochastic process named q-exponential (Q-EP) process that corresponds to the Lq regularization of functions. The key step is to specify consistent multivariate q-exponential distributions by choosing from a large family of elliptic contour distributions. The work is closely related to Besov process which is usually defined in terms of series. Q-EP can be regarded as a definition of Besov process with explicit probabilistic formulation, direct control on the correlation strength, and tractable prediction formula. From the Bayesian perspective, Q-EP provides a flexible prior on functions with sharper penalty (q < 2) than the commonly used Gaussian process (GP, q = 2). We compare GP, Besov and Q-EP in modeling functional data, reconstructing images and solving inverse problems and demonstrate the advantage of our proposed methodology.

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Recognition of micro-objects with adaptive models of image processing in a parallel computing environment 14

Recognition of micro-objects with adaptive models of image p...

引用

14th International Scientific and Technical conference on Applied Mechanics and Systems Dynamics, AMSD 2020

作者： Jumanov, I.I. Djumanov, O.I. Safarov, R.A. Samarkand State University 15 University Boulevard Samarkand Uzbekistan

Scientific and methodological foundations for optimizing the processing of micro-objects, in particular, pollen grains, have been developed on the basis of models and methods of preliminary information processing with mechanisms for filtering, identifying, and using textural, specific characteristics, and geometric features of images. The efficiency of image filtering mechanisms is investigated based on the use of statistical control rules, adaptive two-threshold control, trend functions, and control of the contour description error, traditional detectors of random noise, and interference. The mechanisms of image identification using biquadratic, orthogonal algebraic polynomials, 4th order splines are proposed. A technique for optimizing image identification by finding a function by its integrals in a family of straight lines based on the Mellin and Fourier transforms has been developed. Combined models with mechanisms for smoothing reference points, segmentation of contours, filtering with detection of changes in dynamics, optimization by the conjugate gradient method, time relaxation have been built. A software complex for the recognition and classification of images of pollen grains in C ++ has been developed, which includes testing identification algorithms based on the Daubechies spline function, orthogonal algebraic polynomials of 4, 8 orders in the parallel computing environment "CUDA". © Published under licence by IOP Publishing Ltd.

关键词： Fourier transforms

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Enhancing Medical Domain Data Security using Inbuilt Data Encryption and Steganography

Enhancing Medical Domain Data Security using Inbuilt Data En...

引用

International conference on Computing for Sustainable Global Development (INDIACom)

作者： Tanvi Modi Jinal Patel Manish Paliwal Kaushal Shah Aditya Shastri School of Technology Pandit Deendayal Energy University Gandhinagar Gujarat India

The medical domain has seen an increased use of image steganography and encryption for securing medical pictures and data. image steganography is the procedure of hiding a text (message) within a picture, while encryption of a message would be the state of transforming a readable message into an unreadable format. These two methods can be used together to provide a higher level of security for medical images and data. In this paper, The proper system for securing medical images and data using image steganography and encryption has been proposed. The proposed approach uses the Advanced Encryption Standard (AES) for encryption and decryption. Subsequently, the encrypted data is then embedded into a cover image using a steganographic technique, Linked Pixel pixel steganography. The methodology is tested on large data-sets that include various medical images and are evaluated on various performance parameters. The observations demonstrate that the suggested approach allows secure information transmission even though it is prone to threats.

关键词： Steganography statistical analysis Information security Medical services Information processing Encryption Reliability

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Research on seawater laser communication channel based on visible light 2

Research on seawater laser communication channel based on vi...

引用

2nd IEEE Asia-Pacific conference on image processing, Electronics and Computers, IPEC 2021

作者： Wang, Fei Xi'An Traffic Engineering Institute Xi'an Shaanxi China

ISBN: (纸本)9781728190181

In this paper, the optical characteristics of seawater laser communication channel in offshore waters are analyzed, and the transmission process of the seawater channel by Monte Carlo method, we get the statistical chart of the received power under different transmission distances. The results show that the fitting error of circular arc algorithm is less than that of Gaussian function. Based on the circular fitting algorithm, the underwater wireless optical communication channel model is established. According to the transmission model, the relationship among laser transmission distance, arbitrary receiving position and receiving power can be quickly obtained under certain sea water quality parameters, which provides valuable reference for the design of underwater wireless optical communication system. © 2021 IEEE.

关键词： Monte Carlo methods

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A Pairwise Approach for fMRI Group Studies using the BrainSync Transform

A Pairwise Approach for fMRI Group Studies using the BrainSy...

引用

conference on Medical Imaging - image processing

作者： Joshi, Anand A. Choi, Soyoung Li, Jian Akrami, Haleh Leahy, Richard M. Univ Southern Calif Los Angeles CA 90007 USA

ISBN: (纸本)9781510640221

Due to the spontaneous nature of resting fMRI (rs-fMRI) signals, cross-subject comparison and group studies of rs-fMRI are challenging. Existing group comparison methods typically reduce the fMRI time series either to lower-dimensional connectivity features or use ICA to reduce dimensionality. We previously developed BrainSync, an orthogonal transformation that allows direct comparison of fMRI time-series across subjects.(1) This orthogonal transform performs a temporal alignment of time-series at homologous locations across subjects allowing a direct comparison of scans. In contrast with existing fMRI analysis methods, this transform does not involve dimensionality reduction and preserves the rich functional connectivity information in fMRI data. BrainSync Alignment (BSA) is an extension of this approach that jointly synchronizes fMRI data across time-series data for multiple subjects.(2) Point-wise distance measures, or Pearson correlations, can be computed between the reference and synchronized time-series as measures of inter-subject differences in functional connectivity at each location in the brain. In group studies, especially in the case of spectrum disorders, distances to a single atlas do not fully reflect the differences between subjects that may lie on a multi-dimensional spectrum. Here we describe an approach that measures the distances between pairs of subjects instead of to a single reference point(3). We present novel pairwise statistical methods for fMRI that can be used for regression and also for identifying group differences. We demonstrate the effectiveness of our method in two studies: (i) pairwise comparisons of fMRI data in subjects for performing regression to an ADHD index, and (ii) an F-test using pairwise statistical analysis to compare traumatic brain injury (TBI) subjects that develop post-traumatic epilepsy (PTE) to those that do not.

关键词： fMRI statistical methods

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Transfer Learning Based Effective Approach for Classification of Flowers 1

Transfer Learning Based Effective Approach for Classificatio...

引用

1st International conference on Computational Science and Technology, ICCST 2022

作者： Nithin, Mattapally Sai Shaik, Avesha Balasundaram, A. Surya Deveswar Reddy, Kovvuri Uday Ram Kakarla, Lakshmi Sai Selvakumar, A. School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9781665476553

Deep learning algorithms are being used to do complex tasks like extracting meaningful features, segmenting, and semantic classification of images. In recent years, these methodologies have had a substantial impact on the classification of flower types. Deep neural networks are a type of image recognition system that has been widely used in computer vision applications because of the similarities between classes and intraclass variance. Due to a greater number of flower species that are similar in shape, color, and visualization, classifying flowers is a tough task. Classification of flowers is used for different purposes, like Recognition of medicinal plants. In this paper, we implemented VGG19 and EfficientNetV2L architecture for the classification of flowers. We have fine-tuned our model compared to other methods to obtain higher accuracy. By normalizing and scaling our flower images, we underwent pre-processing. Then we input the pre-trained model of the images. we divided our flower dataset into train, test, and validation. We achieved an accuracy of 88.21 for VGG19 for 20 epochs and 96.28 for 20 epochs which provides the best accuracy than other proposed architectures in the Kaggle dataset. © 2022 IEEE.

关键词： statistical tests

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Digital image processing for Study of Color Design of Residential Apartment Building 4

Digital Image Processing for Study of Color Design of Reside...

引用

4th International conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2022

作者： Alekseeva, Irina E. Ivanova, Olga Yu. Perm National Research Polytechnic University Perm Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

Regularities of color design of residential apartment building are investigated using intelligent technologies for analyzing digital images. Based on the analysis of the collected images, spectral colors and their combinations were found characteristic of every major Russian city. The research was carried out using the universal cognitive-analytical system 'EIDOS-X ++', using three statistical and seven information models based on the methods of information theory. After machine learning the EIDOS-X ++ system using digital images of buildings, which were marked with the names of cities, an intellectual analysis of digital data was carried out. The analysis revealed colors typical of the largest Russian cities. As the results, the spectral colors and their shades characteristic of Yekaterinburg, Chelyabinsk, Nizhny Novgorod, Samara and Kazan are given, as well as which combinations of them are most relevant for the studied cities. Having decided on the options for color combinations, it becomes possible to select the necessary amount of a particular color for the facade and develop design options for the main facades of houses under construction located in the cities under study. It is worth noting that in the creative process of searching for the color design of buildings, a person cannot be replaced. Therefore, the Eidos application created by the authors should be perceived exclusively as a recommendation system. The developed application can simplify and reduce the amount of work of architects, designers and related specialties. © 2022 IEEE.

关键词： Color

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A Review of Modeling Modification methods for Mixed FE-SEA

A Review of Modeling Modification Methods for Mixed FE-SEA

引用

2021 Asia-Pacific conference on image processing, Electronics and Computers, IPEC 2021

作者： Su, Jintao Lou, Jianping Jiang, Xiaolu Saic Commercial Vehicle Technology Center Shanghai China Saic-iveco Hongyan Commercial Vehicle Co. Ltd Chongqing China

Since the traditional deterministic method and classical statistical energy method have little room for improvement, more and more researches gradually turn to the combination of the two methods to solve the low and medium frequency "acoustic vibration"problem. However, in the application of mixed FE-SEA model, researchers found that when the coupling interface between FEA substructure and SEA statistical substructure is in the form of continuous interface, a very large finite element grid needs to be established at the boundary of the mixed model, which leads to huge time-consuming problem in the calculation of medium and low frequency of the mixed model. To solve this problem, the hybrid FE-SEA model needs to be improved and modified. In this paper, some common hybrid model correction methods, including deterministic subsystem edge gradient correction, are reviewed to provide theoretical support for the comprehensive study of hybrid model correction. © Published under licence by IOP Publishing Ltd.

关键词： Finite element method

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