[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Nayak et al., 2020 - Google Patents

Firefly algorithm in biomedical and health care: advances, issues and challenges

Nayak et al., 2020

View HTML
Document ID
16204265561756061882
Author
Nayak J
Naik B
Dinesh P
Vakula K
Dash P
Publication year
Publication venue
SN Computer Science

External Links

Snippet

Since the past decades, most of the nature inspired optimization algorithms (NIOA) have been developed and become admired due to their effectiveness for resolving a variety of complex problems of dissimilar domain. Firefly algorithm (FA) is well-known, yet efficient …
Continue reading at link.springer.com (HTML) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems

Similar Documents

Publication Publication Date Title
Nayak et al. Firefly algorithm in biomedical and health care: advances, issues and challenges
Suganyadevi et al. A review on deep learning in medical image analysis
Ker et al. Image thresholding improves 3-dimensional convolutional neural network diagnosis of different acute brain hemorrhages on computed tomography scans
Ashraf et al. Deep transfer learning for alzheimer neurological disorder detection
Pires et al. A data-driven approach to referable diabetic retinopathy detection
Helwan et al. Deep networks in identifying CT brain hemorrhage
Balaji et al. Hybridized deep learning approach for detecting Alzheimer’s disease
Ali et al. Machine learning based automated segmentation and hybrid feature analysis for diabetic retinopathy classification using fundus image
Lu et al. A method for optimal detection of lung cancer based on deep learning optimized by marine predators algorithm
Mohammed et al. Novel Crow Swarm Optimization Algorithm and Selection Approach for Optimal Deep Learning COVID‐19 Diagnostic Model
Bhuvaneswari et al. A new fusion model for classification of the lung diseases using genetic algorithm
Jain et al. Lung nodule segmentation using salp shuffled shepherd optimization algorithm-based generative adversarial network
Chudzik et al. Exudate segmentation using fully convolutional neural networks and inception modules
Feng et al. Supervoxel based weakly-supervised multi-level 3D CNNs for lung nodule detection and segmentation
Rashed et al. Critical analysis of the current medical image-based processing techniques for automatic disease evaluation: systematic literature review
Shamrat et al. Analysing most efficient deep learning model to detect COVID-19 from computer tomography images
Mareeswari et al. A narrative review of medical image processing by deep learning models: origin to COVID-19
Goyal et al. Musculoskeletal abnormality detection in medical imaging using GnCNNr (group normalized convolutional neural networks with regularization)
Jatmiko et al. A review of big data analytics in the biomedical field
Rajan et al. IoT based optical coherence tomography retinal images classification using OCT Deep Net2
Ozaltin et al. Artificial intelligence-based brain hemorrhage detection
Mandal et al. Image-based Skin Disease Detection and Classification through Bioinspired Machine Learning Approaches
Ganesh et al. Multi class robust brain tumor with hybrid classification using DTA algorithm
Kumar et al. Prostate cancer classification with MRI using Taylor-Bird squirrel optimization based deep recurrent neural network
Prasad et al. Fractional Pelican African Vulture Optimization-based classification of breast cancer using mammogram images