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  1. Article ; Online: Understanding and Analysis of Enhanced COVID-19 Chest X-Ray Images

    Hanumantharaju, M. C. / Manjunath Aradhya, V. N. / Hemantha Kumar, G.

    Intelligent Systems and Methods to Combat Covid-19 ; SpringerBriefs in Applied Sciences and Technology

    2020  , Page(s) 47–55

    Keywords covid19
    Publisher Springer Singapore
    Publishing country us
    Document type Article ; Online
    ISSN 2191-530X
    DOI 10.1007/978-981-15-6572-4_6
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article: One-shot Cluster-Based Approach for the Detection of COVID-19 from Chest X-ray Images.

    Aradhya, V N Manjunath / Mahmud, Mufti / Guru, D S / Agarwal, Basant / Kaiser, M Shamim

    Cognitive computation

    2021  Volume 13, Issue 4, Page(s) 873–881

    Abstract: Coronavirus disease (COVID-19) has infected over more than 28.3 million people around the globe and killed 913K people worldwide as on 11 September 2020. With this pandemic, to combat the spreading of COVID-19, effective testing methodologies and ... ...

    Abstract Coronavirus disease (COVID-19) has infected over more than 28.3 million people around the globe and killed 913K people worldwide as on 11 September 2020. With this pandemic, to combat the spreading of COVID-19, effective testing methodologies and immediate medical treatments are much required. Chest X-rays are the widely available modalities for immediate diagnosis of COVID-19. Hence, automation of detection of COVID-19 from chest X-ray images using machine learning approaches is of greater demand. A model for detecting COVID-19 from chest X-ray images is proposed in this paper. A novel concept of cluster-based one-shot learning is introduced in this work. The introduced concept has an advantage of learning from a few samples against learning from many samples in case of deep leaning architectures. The proposed model is a multi-class classification model as it classifies images of four classes, viz., pneumonia bacterial, pneumonia virus, normal, and COVID-19. The proposed model is based on ensemble of Generalized Regression Neural Network (GRNN) and Probabilistic Neural Network (PNN) classifiers at decision level. The effectiveness of the proposed model has been demonstrated through extensive experimentation on a publicly available dataset consisting of 306 images. The proposed cluster-based one-shot learning has been found to be more effective on GRNN and PNN ensembled model to distinguish COVID-19 images from that of the other three classes. It has also been experimentally observed that the model has a superior performance over contemporary deep learning architectures. The concept of one-shot cluster-based learning is being first of its kind in literature, expected to open up several new dimensions in the field of machine learning which require further researching for various applications.
    Language English
    Publishing date 2021-03-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2486574-6
    ISSN 1866-9964 ; 1866-9956
    ISSN (online) 1866-9964
    ISSN 1866-9956
    DOI 10.1007/s12559-020-09774-w
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Retrieval of flower videos based on a query with multiple species of flowers

    V.K. Jyothi / V.N. Manjunath Aradhya / Y.H. Sharath Kumar / D.S. Guru

    Artificial Intelligence in Agriculture, Vol 5, Iss , Pp 262-

    2021  Volume 277

    Abstract: Searching, recognizing and retrieving a video of interest from a large collection of a video data is an instantaneous requirement. This requirement has been recognized as an active area of research in computer vision, machine learning and pattern ... ...

    Abstract Searching, recognizing and retrieving a video of interest from a large collection of a video data is an instantaneous requirement. This requirement has been recognized as an active area of research in computer vision, machine learning and pattern recognition. Flower video recognition and retrieval is vital in the field of floriculture and horticulture. In this paper we propose a model for the retrieval of videos of flowers. Initially, videos are represented with keyframes and flowers in keyframes are segmented from their background. Then, the model is analysed by features extracted from flower regions of the keyframe. A Linear Discriminant Analysis (LDA) is adapted for the extraction of discriminating features. Multiclass Support Vector Machine (MSVM) classifier is applied to identify the class of the query video. Experiments have been conducted on relatively large dataset of our own, consisting of 7788 videos of 30 different species of flowers captured from three different devices. Generally, retrieval of flower videos is addressed by the use of a query video consisting of a flower of a single species. In this work we made an attempt to develop a system consisting of retrieval of similar videos for a query video consisting of flowers of different species.
    Keywords Flower region of interest (FRoI) ; Linear discriminant analysis (LDA) ; Retrieval of flower videos ; Multiclass support vector machine ; Agriculture ; S
    Subject code 004 ; 006
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher KeAi Communications Co., Ltd.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: Understanding and Analysis of Enhanced COVID-19 Chest X-Ray Images

    Hanumantharaju, M. C. / Manjunath Aradhya, V. N. / Hemantha Kumar, G.

    SpringerBriefs in Applied Sciences and Technology

    Abstract: The 2019 coronavirus disease (COVID-19) with its origin in China has spread rapidly to other nations and infected millions of people In this context, this paper proposes the development of algorithm that enhances the details of images and assists the ... ...

    Abstract The 2019 coronavirus disease (COVID-19) with its origin in China has spread rapidly to other nations and infected millions of people In this context, this paper proposes the development of algorithm that enhances the details of images and assists the doctors in knowing the exact location of affected area The proposed technique improvises the most popular image enhancement algorithm, namely, multiscale retinex and adjusts the parameters to intensify the details of chest X-ray/CT images of COVID-19 patients Multiscale retinex (MSR) is human perception-related enhancement algorithm which improves intensity, contrast, and sharpness in medical image through dynamic range compression The proposed scheme improves the details of images and validates the resulting images using novel metric called wavelet energy The proposed study is evaluated on images of COVID-19 patients have been obtained from the open-source GitHub repository Considering the experimental result presented and performance metric, the proposed algorithm has provided important details to doctors in making right decision © 2020, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #825969
    Database COVID19

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  5. Article: Retrieval of flower videos based on a query with multiple species of flowers

    Jyothi, V.K. / Aradhya, V.N. Manjunath / Sharath Kumar, Y.H. / Guru, D.S.

    Artificial intelligence in agriculture. 2021, v. 5

    2021  

    Abstract: Searching, recognizing and retrieving a video of interest from a large collection of a video data is an instantaneous requirement. This requirement has been recognized as an active area of research in computer vision, machine learning and pattern ... ...

    Abstract Searching, recognizing and retrieving a video of interest from a large collection of a video data is an instantaneous requirement. This requirement has been recognized as an active area of research in computer vision, machine learning and pattern recognition. Flower video recognition and retrieval is vital in the field of floriculture and horticulture. In this paper we propose a model for the retrieval of videos of flowers. Initially, videos are represented with keyframes and flowers in keyframes are segmented from their background. Then, the model is analysed by features extracted from flower regions of the keyframe. A Linear Discriminant Analysis (LDA) is adapted for the extraction of discriminating features. Multiclass Support Vector Machine (MSVM) classifier is applied to identify the class of the query video. Experiments have been conducted on relatively large dataset of our own, consisting of 7788 videos of 30 different species of flowers captured from three different devices. Generally, retrieval of flower videos is addressed by the use of a query video consisting of a flower of a single species. In this work we made an attempt to develop a system consisting of retrieval of similar videos for a query video consisting of flowers of different species.
    Keywords agriculture ; computer vision ; data collection ; discriminant analysis ; floriculture ; flowers ; models ; support vector machines
    Language English
    Size p. 262-277.
    Publishing place Elsevier B.V.
    Document type Article
    ISSN 2589-7217
    DOI 10.1016/j.aiia.2021.11.001
    Database NAL-Catalogue (AGRICOLA)

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  6. Article ; Online: A Linked List Approach for Handwritten Textline Segmentation

    Naveena C. / Manjunath Aradhya V. N.

    Journal of Intelligent Systems, Vol 21, Iss 3, Pp 225-

    2012  Volume 235

    Abstract: Textline segmentation in handwritten documents is of real challenge and interesting in the field of document image processing. In this paper, we propose a handwritten textline segmentation scheme based on the concept of linked list. The proposed method ... ...

    Abstract Textline segmentation in handwritten documents is of real challenge and interesting in the field of document image processing. In this paper, we propose a handwritten textline segmentation scheme based on the concept of linked list. The proposed method consists of three stages, namely, preprocessing, linked list and mathematical morphology. The concept of the linked list approach is used to build a textline sequence and mathematical morphology is used to obtain the line separator. We experimentally evaluated our proposed method on a document containing handwritten Kannada script. The results are compared with recent methods and show encouraging results.
    Keywords textline segmentation ; connected component analysis ; linked list ; mathematical morphology ; Science ; Q ; Electronic computers. Computer science ; QA75.5-76.95
    Language English
    Publishing date 2012-10-01T00:00:00Z
    Publisher De Gruyter
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet Domain

    Hanumantharaju M.C. / Ravishankar M. / Rameshbabu D.R. / Aradhya V.N. Manjunath

    Journal of Intelligent Systems, Vol 22, Iss 2, Pp 155-

    2013  Volume 177

    Abstract: This article presents a novel full-reference (FR) image quality assessment (QA) algorithm by depicting the sub-band characteristics in the wavelet domain. The proposed image quality assessment method is based on energy estimation in the wavelet- ... ...

    Abstract This article presents a novel full-reference (FR) image quality assessment (QA) algorithm by depicting the sub-band characteristics in the wavelet domain. The proposed image quality assessment method is based on energy estimation in the wavelet-transformed image. Image QA is achieved by applying a multilevel wavelet decomposition on both the original and the enhanced image. Next, the wavelet energy (WE) and vector are computed to obtain the percentage of the energy that corresponds to the approximation and the details, respectively. Further, the approximate and detailed energy levels of both the original and the enhanced images are compared to formulate an image quality assessment. Numerous experiments are conducted on a dozen of image enhancement algorithms. The results presented show that the image with poor contrast in the foreground than the background has continuous regular coefficient values. The probability density function for such an image has a relatively lower WE and skewness compared with the background. The proposed scheme not only evaluates the global information of an image but also estimates the fine, detailed changes in an enhanced image. Thus, the proposed metric serves as an objective and effective FR criterion for color image QA. The experimental results presented confirm that the proposed WE metric is an efficient and useful metric for evaluating the quality of the color image enhancement.
    Keywords image enhancement ; quality assessment ; wavelet domain ; wavelet energy ; Science ; Q ; Electronic computers. Computer science ; QA75.5-76.95
    Subject code 006
    Language English
    Publishing date 2013-06-01T00:00:00Z
    Publisher De Gruyter
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Skew Estimation Technique for Binary Document Images based on Thinning and Moments

    Manjunath Aradhya V N / Hemantha Kumar G / Shivakumara P

    Engineering Letters, Vol 14, Iss 1, Pp 127-

    2007  Volume 134

    Keywords Computer engineering. Computer hardware ; TK7885-7895 ; Electronics ; TK7800-8360 ; Electrical engineering. Electronics. Nuclear engineering ; TK1-9971 ; Technology ; T ; DOAJ:Computer Science ; DOAJ:Technology and Engineering
    Language English
    Publishing date 2007-02-01T00:00:00Z
    Publisher International Association of Engineers
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: An Improved and Efficient Rotation Invariant Thinning Algorithm for Binary Document Images

    Aradhya, V.N. Manjunath / Kumar, G. Hemantha / Shivakumara, P.

    Journal of Intelligent Systems, Vol 17, Iss 1-3, Pp 157-

    2008  Volume 172

    Keywords Science ; Q ; Electronic computers. Computer science ; QA75.5-76.95
    Language English
    Publishing date 2008-08-01T00:00:00Z
    Publisher De Gruyter
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: SiMOR

    Gopala Krishna M. T. / Ravishankar M. / Ramesh Babu D. R. / Manjunath Aradhya V. N.

    Journal of Intelligent Systems, Vol 20, Iss 1, Pp 33-

    Single Moving Object Recognition

    2011  Volume 45

    Abstract: Automatic moving object detection and tracking is very important task in video surveillance applications. In the present work the well known background subtraction model and use of Gaussian Mixture Models (GMM) have been used to implement a robust ... ...

    Abstract Automatic moving object detection and tracking is very important task in video surveillance applications. In the present work the well known background subtraction model and use of Gaussian Mixture Models (GMM) have been used to implement a robust automated single object tracking system. In this implementation, background subtraction on subtracting consecutive frame-by-frame basis for moving object detection is done. Once the object has been detected it is tracked by employing an efficient GMM technique. After successful completion of tracking, moving object recognition of those objects using well known Principal Component Analysis (PCA), which is used for extracting features and Manhattan based distance metric is used for subsequent classification purpose. The system is capable of handling entry and exit of an object. Such a tracking system is cost effective and can be used as an automated video conferencing system and also has applications like human tracking, vehicles monitoring, and event recognition for video surveillance. The proposed algorithm was tested on standard database on complex environments and the results were satisfactory.
    Keywords object detection ; tracking and recognition ; gaussian mixture model ; pca ; surveillance ; video conferencing system ; Science ; Q ; Electronic computers. Computer science ; QA75.5-76.95
    Subject code 004 ; 006
    Language English
    Publishing date 2011-04-01T00:00:00Z
    Publisher De Gruyter
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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