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Journal
摘要: Glaucoma is an eye disease that damages optic nerves in eye leading to loss of vision. It is recognized to be the one of the major cause of blindness across the world. The detection of glaucoma in its early stage followed by treatment is the only way forward because damage done by the disease is irreversible. Hence there is a requirement of a large scale glaucoma screening. Manual screening of glaucoma at large scale is quite a challenging task due to lack of skilled manpower in ophthalmology. T关键词: Glaucoma;Structural Features;CDR;RDR;Texture Features;GLCM;HOG
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Journal
摘要: Above-ground biomass (AGB) is a significant phenotypic index for evaluating photosynthesis capacity, healthy growth, and estimating crop yield. Accurately monitoring the AGB helps improve agricultural fertilization management and optimize planting patterns. Numerous studies have confirmed that canopy spectrum saturation causes optical vegetation indices (VIs) to underestimate the AGB of crops at multiple growth periods. To solve this problem, the present research used a remote sensing method to 关键词: UAV;Digital images;Potato;Texture features;Crop height;Above ground biomass
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摘要: Structural cracks in concrete have a significant influence on structural safety, so it is necessary to detect and monitor concrete cracks. Deep learning is a powerful tool for detecting cracks in concrete structures. However, it requires a large quantity of training samples and is costly in terms of computational time. In order to solve these difficulties, a deep learning target detection framework combining texture features with concrete crack data is proposed. Texture features and pre-processe关键词: concrete;crack identification;deep learning;texture features
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Book Chapter
摘要: Image categorization is the process of assigning land cover classes to pixels. It may categorize images into forest, urban, agricultural, and other categories. The approaches in this study are tested using a large image dataset comprising 21 land use categories. There are comparisons to be done in addition to traditional approaches. DWT at two degrees of decomposition is used to extract texture features from remote sensing images. The results are explained using the UC Merced dataset. At the app关键词: Remote sensing images;Preprocessing;Texture feature extraction;Classification;Support vector machine (SVM)
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Book Chapter
摘要: Due to availability of human resources in India, nearly all the horticulture work is done manually by workers which involves the possibility of human error, and we get to have some rotten or not so fresh fruits. To avoid this possibility of human error and mistakes it is required to have an automated system in the field of horticulture in India. Numerous research papers have been proposed to address these external issues, however they all have drawbacks and limitations, such as low accuracy due 关键词: Fresh fruit;Rotten fruit;Classification;Texture features;Convolution neural network
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Journal
摘要: The identification of script in a document page image is the first step for an OCR system processing multi-script documents. In this multilingual/multiscript world, document processing systems relying on the OCR that need human involvement to select the appropriate OCR package is definitely undesirable and inefficient. The development of robust and efficient methods for automatic script identification of a document is a subject of major importance for automatic document processing in a multiling关键词: Script identification;page level;texture features;machine learning;Gabor;wavelet
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Book Chapter
摘要: Brain is recognized as one of the complex organs of the human body. Abnormal formation of cells may affect the normal functioning of the brain. These abnormal cells may belong to category of benign cells resulting in low-grade glioma or malignant cells resulting in high-grade glioma. The treatment plans vary according to grade of glioma detected. This results in need of precise glioma grading. As per World Health Organization, biopsy is considered to be gold standard in glioma grading. Biopsy is关键词: High-grade glioma;Low-grade glioma;AdaBoost;Texture features;Feature selection
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Book Chapter
摘要: Aging is a natural process that affects the human body. The primary focus of this research work is to study the appearance of face wrinkles, which is considered as one of the most noticeable changes that happen as people become older. In any medical cosmetology, skin analysis becomes an important procedure for the wrinkle detection or any other medical problems. Maximum of the conventional wrinkles examination schemes is semi-automatic. Also, these methods require a lot of human interference. Si关键词: Deep learning;Image segmentation;Edge detection;Hough transformer;Region of interest;Neural networks;Texture features
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Journal
摘要: Breast density has been recognised as an important biomarker that indicates the risk of developing breast cancer. Accurate classification of breast density plays a crucial role in developing a computer-aided detection (CADe) system for mammogram interpretation. This paper proposes a novel texture descriptor, namely, rotation invariant uniform local quinary patterns (RIU4-LQP), to describe texture patterns in mammograms and to improve the robustness of image features. In conventional processing s关键词: breast density classification;mammography;local quinary patterns;spatial distribution analysis;texture features
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Book Chapter
摘要: The technique of assigning land cover classifications to pixels is known as image classification. It may divide pictures into categories such as forest, urban, agricultural, and others. A huge picture dataset of 21 land use types is used to test techniques in this research. In addition to conventional methods, there are comparisons to be made. The texture characteristics are extracted from remote sensing pictures using DWT at two degrees of decomposition. The UC-Mercedes dataset is used to expla关键词: Texture feature extraction;Optimal features;Classification;Remote sensing images
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Journal
Hong Yong;Li Deren;Wang Mi;Jiang Haonan;Luo Lengkun;Wu Yanping;Liu Chen;Xie Tianjin;Zhang Qing;Jahangir Zahid;
Remote SensingVolume 14, Issue 6, 2022, PP 1392-1392
摘要: Cotton is an important economic crop, but large-scale field extraction and estimation can be difficult, particularly in areas where cotton fields are small and discretely distributed. Moreover, cotton and soybean are cultivated together in some areas, further increasing the difficulty of cotton extraction. In this paper, an innovative method for cotton area estimation using Sentinel-2 images, land use status data (LUSD), and field survey data is proposed. Three areas in Hubei province (i.e., Jin关键词: cotton extraction;spatial constraint;vegetation indices;spectral features;texture features;CSSDI;LUSD
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Journal
摘要: Presently, while automated depression diagnosis has made great progress, most of the recent works have focused on combining multiple modalities rather than strengthening a single one. In this research work, we present a unimodal framework for depression detection based on facial expressions and facial motion analysis. We investigate a wide set of visual features extracted from different facial regions. Due to high dimensionality of the obtained feature sets, identification of informative and dis关键词: Depression classification;Video processing;Visual Cues;Texture Features;Feature selection;Wrapper method;Incremental Linear Discriminant Analysis
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Journal
摘要: Natural rubber is one of the four major industrial raw materials in China, and the demand for it is increasing rapidly in China. However, due to geographic and climatic limitations, the rate of natural rubber production in China is significantly less than required to satisfy this demand. Therefore, to ensure the healthy development of China’s rubber industry, it is urgent to develop a method to rapidly and accurately monitor the planting and distribution of rubber forests in China. Existing stud关键词: Keywords;rubber;vigorous period;texture features;object-oriented method;random forest algorithm
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Book Chapter
摘要: There is a rising requirement that medicinal plants are properly classified and identified since they are extremely vital to our lives. However, it is quite difficult to identify such biological things because they are not governed by mathematical function. In this paper, the classification of six different species of medicinal plants is discussed using different feature extraction techniques, namely morphological, color, and texture. The image dataset is comprised of a total of 90 sample leaves关键词: Color model;Image;Morphological feature;Neural network;Segmentation;Texture feature
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Journal
摘要: Neovascular glaucoma (NVG) is a human eye disease due to diabetes that leads to permanent vision loss. Early detection and treatment of it prevent further vision loss. Hence the development of an automated system is more essential to help the ophthalmologist in detecting NVG at an earlier stage. In this paper, a novel approach is used for detection of Neovascular glaucoma using fractal geometry concepts. Fractal geometry is a branch of mathematics. It is useful in computing fractal features of i关键词: Glaucoma;Fractal Dimension (FD);Box Counting;Segmentation;Texture Features;Retina.
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Journal
Niwa Shiori;Mawaki Ayana;Hisano Fumiya;Nakanishi Keisuke;Watanabe Sachiyo;Fukuyama Atsushi;Kikumori Toyone;Shimamoto Kazuhiro;Fujimoto Etsuko;Oshima Chika;
Lymphatic research and biologyVolume 20, Issue 1, 2022, PP 11-16
摘要: Background: Breast cancer-related lymphedema (BCRL) is a chronic swelling of the arm due to breast cancer treatment. Lymphedema is diagnosed and staged on the basis of limb circumference measurements and the patient's subjective symptoms, which have poor reproducibility and objectivity: these cannot detect any fluid accumulation in the tissue. Ultrasonography is a feasible noninvasive technique that can be used to evaluate tissue structure in real time. This study aimed to assess the ability of 关键词: breast cancer-related lymphedema;fluid accumulation;texture features;ultrasound
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Journal
Cao Weiguo;Pomeroy Marc J.;Zhang Shu;Tan Jiaxing;Liang Zhengrong;Gao Yongfeng;Abbasi Almas F.;Pickhardt Perry J.;
SensorsVolume 22, Issue 3, 2022, PP 907-907
摘要: Objective: As an effective lesion heterogeneity depiction, texture information extracted from computed tomography has become increasingly important in polyp classification. However, variation and redundancy among multiple texture descriptors render a challenging task of integrating them into a general characterization. Considering these two problems, this work proposes an adaptive learning model to integrate multi-scale texture features. Methods: To mitigate feature variation, the whole feature 关键词: colorectal cancer;computed tomographic colonography;polyp classification;texture features;random forest;convolutional neural network
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Book Chapter
摘要: Forests are necessary as well as important for combatting climate change. Forest fires destroy the forest’s wealth and affect the environment. They pose a threat, to fauna and flora, seriously. Forest fires are difficult to detect and thus have a long response time which leads to mass destruction. Hence, it has been a prominent research area with the aim of conserving ecology. In this paper, we have created a knowledge base for forest fire risk prediction and detection purposes by extracting dif关键词: Knowledge base;Multispectral image analysis;Landsat 8;Feature extraction;Texture feature;Normalized difference vegetation indices;Land surface temperature
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Book Chapter
摘要: The technique of assigning land cover pattern classifications to pixels is known as image categorization. It may divide pictures into groups such as forest, urban, agricultural, and others. A large picture dataset with 21 land-use types is used to evaluate the methods in this study. In addition to standard techniques, there are comparisons to be made. Texture characteristics are extracted from remote sensing pictures using DWT at two degrees of decomposition. The UC-Mercedes dataset is used to e关键词: Remote sensing images;Preprocessing;Texture feature extraction;Classification;Back propagation (BPN)
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Journal
摘要: Cervical cancer is the common cancer among women, where early-stage diagnoses of cervical cancer lead to recovery from the deadly cervical cancer. Correct cervical cancer staging is predominant to decide the treatment. Hence, cervical cancer staging is an important problem in designing automatic detection and diagnosing applications of the medical field. Convolutional Neural Networks (CNNs) often plays a greater role in object identification and classification. The performance of CNN in medical 关键词: CapsNet;Deep learning;Medical image classification;Texture features
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Journal
摘要: Image manipulation has become widely accessible to the masses over the past years due to the sophisticated image editing tools which are readily-available and easy to use. As a result, image forgery has increased such that it has become infeasible to discriminate authentic from tampered images with the naked eye. Image forgery plays a prominent role in the spread of misinformation, which might be criminalized under certain jurisdictions. Image splicing is a common type of image manipulation and 关键词: Image splicing;fractional differential;texture features;support vector machine
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Journal
摘要: The detection of fires in surveillance videos are usually done by utilizing deep learning. In Spite of the advances in processing power, deep learning methods usually need extensive computations and require high memory resources. This leads to restriction in real time fire detection. In this research, we present a time-efficient fire detection convolutional neural network coupled with transfer learning for surveillance systems. The model utilizes CNN architecture with reasonable computational ti关键词: Fire detection; classification; neural network; texture features; transfer learning
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Journal
摘要: COVID-19 pandemic outbreak became one of the serious threats to humans. As there is no cure yet for this virus, we have to control the spread of Coronavirus through precautions. One of the effective precautions as announced by the World Health Organization is mask wearing. Surveillance systems in crowded places can lead to detection of people wearing masks. Therefore, it is highly urgent for computerized mask detection methods that can operate in real-time. As for now, most countries demand mask关键词: Mask detection; classification; neural network; texture features; transfer learning
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Journal
摘要: Facial temperature distribution in healthy people shows contralateral symmetry, which is generally disrupted by facial paralysis. This study aims to develop a quantitative thermal asymmetry analysis method for early diagnosis of facial paralysis in infrared thermal images. First, to improve the reliability of thermal image analysis, the facial regions of interest (ROIs) were segmented using corner and edge detection. A new temperature feature was then defined using the maximum and minimum temper关键词: facial paralysis;infrared thermal images;thermal asymmetry;temperature features;texture features
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Journal
Research Article
摘要: In recent years, 3D point cloud technology has played an increasingly important role in the field of casting parts detection. Due to the huge amount of high-precision point cloud data, simplification is often necessary before 3D reconstruction to improve computational efficiency. However, most of the existing point cloud simplification algorithms often blur edge details and produce holes in the final 3D reconstruction. To avoid these problems, a novel point cloud simplification method is propose关键词: 3D point cloud simplification;3D reconstruction;geometric features;texture features
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Journal
摘要: Severity assessment of the novel Coronavirus (COVID‐19) using chest computed tomography (CT) scan is crucial for the effective administration of the right therapeutic drugs and also for monitoring the progression of the disease. However, determining the severity of COVID‐19 needs a highly expert radiologist by visual assessment, which is time‐consuming, boring, and subjective. This article introduces an advanced machine learning tool to determine the severity of COVID‐19 to mild, moderate, and s关键词: computed tomography;random forest;severity of COVID‐19;texture features
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Journal
摘要: Breast cancer is one of the common reasons for deaths of women over the globe. It has been found that a Computer-Aided Diagnosis (CAD) system can be designed using X-ray mammograms for early-stage detection of breast cancer, which can decrease the death rate to a large extent. This paper work proposes a novel 2-way threshold-based intelligent water drops IWD “algorithm for feature selection to design an effective and efficient CAD system that can detect breast cancer in early stage. This approac关键词: CAD system;Mammography;Texture features;SVM;Meta-heuristic optimization;Intelligent water drops algorithm
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Journal
摘要: The dirty degree of banknotes determines to some extent whether banknotes can continue to circulate. This paper proposes a whale optimization algorithm based multi-layer support vector machine (WOA-MLSVMs) dirty degree recognition method based on the texture characteristics of banknote images. Based on the contact image sensor to collect the double-sided reflection images of the banknotes under red, green, blue, infrared and ultraviolet light, as well as the transmission images under the green l关键词: banknote dirty degree; texture features; whale optimization algorithm; data dimension reduction; support vector machine
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Journal
摘要: With the development of remote sensing technology and machine learning, the research on hyperspectral remote sensing image classification has also progressed rapidly. In this paper, based on the random forest model, a new classification model of hyperspectral remote sensing images is proposed, which can effectively classify the spectral information and texture information of hyperspectral images. First, the texture features are extracted from the hyperspectral remote sensing image data and super关键词: hyperspectral remote sensing;texture features;spectral-space domain;random forest model;optimal combination of parameters
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Journal
Research Article
Pociask Elżbieta;Nurzynska Karolina;Obuchowicz Rafał;Bałon Paulina;Uryga Daniel;Strzelecki Michał;Izworski Andrzej;Piórkowski Adam;
SensorsVolume 21, Issue 22, 2021, PP 7481-7481
摘要: The aim of this study was to evaluate whether textural analysis could differentiate between the two common types of lytic lesions imaged with use of radiography. Sixty-two patients were enrolled in the study with intraoral radiograph images and a histological reference study. Full textural analysis was performed using MaZda software. For over 10,000 features, logistic regression models were applied. Fragments containing lesion edges were characterized by significant correlation of structural inf关键词: texture features;classification;periapical lesions;intraoral radiography;tSNE;granulomas;cysts
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