MIND 2019: International Conference on Machine Learning, Image Processing, Networks and Data Sciences
- Call for paper, ranking, acceptance rate,
submission deadline, notification date, conference location, submission guidelines, and other important details
This article provides the call for paper, ranking, acceptance rate,
submission deadline, notification date, conference location, submission guidelines, and other important details of MIND 2019: International Conference on Machine Learning, Image Processing, Networks and Data Sciences all at one place.
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Conference Location
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Kurukshetra, India
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Conference Date
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2019-03-03
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Notification Date
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2018-12-30
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Submission Deadline
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2018-12-15
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Conference Website and Submission Link
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http://www.mind2019.in
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Conference Ranking
International Conference on Machine Learning, Image Processing, Networks and Data Sciences ranking based on CCF, Core, and Qualis is shown below:
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CCF Ranking
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Core Ranking
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Qualis Ranking
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Click here to check the ranking of any conference.
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About CCF Ranking: The Chinese Computing Federation (CCF) Ranking provides a ranking of peer-reviewed journals and conferences in the field of computer science.
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About Core Ranking: The CORE Conference Ranking is a measure to assess the major conference in the computing field. This ranking is governed by the CORE Executive Committee. To know more about Core ranking, visit Core ranking portal.
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About Qualis Ranking: This conference ranking is published by the Brazilian ministry of education. It uses the h-index as a performance metric to rank conferences. Conferences are classified into performance groups that range from A1 (to the best), A2, B1, B2,..., B5 (to the wost). To know more about qualis ranking, visit here
Conference Acceptance Rate
Below is the acceptance rate of International Conference on Machine Learning, Image Processing, Networks and Data Sciences conference for the last few years:
| Year |
Submitted Papers |
Accepted Papers |
Accepted Percentage/Acceptance Rate |
We are working hard to collect and update the acceptance rate details of the conferences for recent years. However, you can consider the above (if available) acceptance rates to predict the average chances of acceptance of your research paper at this conference.
Conference Call for paper
Original contributions are invited from prospective authors with interests in the indicated conference topics and related areas of application. All contributions should be high quality, original and not published elsewhere or submitted for publication during the review period. Every submission must identify the conference track which best relates to the contents of the paper. Papers will be peer reviewed by the International Program Committee, and may be accepted for long and short presentation.We solicit original research and technical papers not published elsewhere. The papers can be theoretical, practical and application oriented on the following conference tracks (but not limited to).Best Paper AwardsThe Best Paper Awards will be given to the authors which will be selected by the committee among the papers/posters presented in MIND-2019. The Best Paper Awards Committee will be recommended by the advisory committee and the nominees will be evaluated based on scientific contribution, writing/presentation style, reviewers comments etc. The “Best Paper Awards” will be given for each track/discipline.Conference TracksMachine Learning and Computational Intelligence
Theoretical Computer Science
Artificial Intelligence
Pattern recognition
Computer Graphics
Virtual Reality
Distributed & Cloud Computing
Signal Processing
Software Architecture
Soft Computing
Grid and Cluster Computing
Evolutionary Algorithms
Ubiquitous Computing
Parallel and Distributed Networks
Perceptual Computing, and related topics
Learning using Ensemble and boosting strategies
Active Machine Learning
Manifold Learning
Fuzzy Learning
Kernel Based Learning
Genetic Learning
Hybrid models
Bioinformatics and biomedical informatics
Healthcare and clinical decision support
Collaborative filtering
Information retrieval
Natural language processing
Web search
Inference dependencies on multi-layered networks
Recurrent Neural Networks and its applications
Graph wavelets
Spectral graph theory
Self-organizing networks
Multi-scale learning
Unsupervised feature learning
Clustering, Classification and regression methods
Supervised, semi-supervised and unsupervised learning
Reinforcement Learning
Optimization methods
Parallel and distributed learning
Adaptive and dynamic shrinking
Pattern summarization
Graph embeddings
Graph mining methods
Fuzzy approaches to parameter estimation
Genetic optimization
Bayesian estimation approaches
Boosting approaches to Transfer learning
Recurrent Neural NetworksImage Processing and Computer Vision
Filtering, Transforms, Multi-Resolution Processing
Restoration, Enhancement, Super-Resolution
Computer Vision Algorithms and Technologies
Compression, Transmission, Storage, Retrieval
Multi-View, Stereoscopic, and 3D Processing
Multi-Temporal and Spatio-Temporal Processing
Biometrics, Forensics, and Content Protection
Biological and Perceptual-based Processing
Medical Image and Video Analysis
Document and Synthetic Visual Processing
Color and Multispectral Processing
Computational Imaging
Video Processing and Analytics
Visual Quality Assessment
Deep learning for Images and Video
Human activity recognition
Software Tools for Imaging
Image Generation, Acquisition, and Processing
Image-based Modeling and Algorithms
Mathematical Morphology
Image Geometry and Multi-view Geometry
3D Imaging
Novel Noise Reduction Algorithms
Motion and Tracking Algorithms and Applications
Watermarking Methods and Protection + Wavelet Methods
Image Data Structures and Databases
Image Compression, Coding, and Encryption
Multi-resolution Imaging Techniques
Multimedia Systems and Applications
Novel Image Processing Applications
Camera Networks and Vision
Machine Learning Technologies for Vision
Cognitive and Biologically Inspired Vision
Active and Robot Vision
Fuzzy and Neural Techniques in Vision
Novel Document Image Understanding Techniques
Novel Vision Application and Case StudiesNetwork Security
Network Performance Analysis,
Human factors in security and privacy
Security and privacy in ad hoc networks
Machine learning for Biometric security and privacy
Machine learning for Security and privacy of Web service
Security and privacy in e-services
Security and privacy in grid computing
Security and privacy in mobile systems
Security and privacy in wireless sensor networks
Cyber risk and vulnerability assessment
Cyber-crime and warfare
Cyber threat analysis and modelling
Machine learning for Bluetooth, WiFi, WiMax security
Security and privacy in smart grid and distributed generation systems
Security and privacy in social applications and networks
Cyber forensic tools, techniques, and analysis
Visual analytics for cyber security
Security and privacy of mobile cloud computing
Cyber security testbeds, tools, and methodologies
Active and passive cyber defense techniques
Insider threat detection and prevention
Critical infrastructure protection
Security and privacy in industrial systems
Security and privacy in pervasive/ubiquitous computing
Intrusion detection and prevention
Botnet detection and mitigationData Sciences
Big data management,
Platforms and technologies for big data,
Data retrieval,
Big data storage techniques,
Data mining and warehouse,
Data visualization,
Modelling structure and storage of big data,
Scalability and portability issues of big data,
Big data recommender systems,
Digital Forensics,
Parallel processing of big data,
Distributed access of big data,
Applications of big data and related topics,
Web mining,
Social Network Analysis,
Text Mining,
Sentiment Analysis.
Algorithms
Novel Theoretical Models
Novel Computational Models
Data and Information Quality
Data Integration and Fusion
Cloud/Grid/Stream Computing
High Performance/Parallel Computing
Energy-efficient Computing
Software Systems
Search and Mining
Data Acquisition, Integration, Cleaning
Data Visualizations
Semantic-based Data Mining
Data Wrangling, Data Cleaning, Data Curation, Data Munching
Data Analysis, , Statistical Insights
Decision making from insights, Hidden patterns
Data Science technologies, tools, frameworks, platforms and APIs
Link and Graph Mining
Efficiency, scalability, security, privacy and complexity issues in Data Science
Labelling, Collecting, Surveying, Interviewing and other tools for Data Collection
Applications in Mobility, Multimedia, Science, Technology, Engineering, Medicine, Healthcare, Finance, Business, Law, Transportation, Retailing, Telecommunication
Submission Deadline
MIND 2019: International Conference on Machine Learning, Image Processing, Networks and Data Sciences submission deadline is 2018-12-15.
Note: It is generally recommended to submit your conference paper
on or before the submission deadline. Generally, conferences do not
encourage to submit the research paper after the deadline is over.
In rare scenarios, conferences extend their deadline. Decision about the
extension of the deadline is generally updated on the official conference webpage.
Notification date
Notification date of MIND 2019: International Conference on Machine Learning, Image Processing, Networks and Data Sciences is 2018-12-30.
Note: This is the date on which conference announces the result about acceptance or rejection of submitted papers. If your research paper is accepted, the conference will request you to submit the camera ready version of your research paper by the due date. Due date to submit the camera ready version of the paper is generally posted on the official web page of the conferences or notified to you via. email.
Conference Date
MIND 2019: International Conference on Machine Learning, Image Processing, Networks and Data Sciences will start on 2019-03-03.
Note: This is the date on which the conference starts.
Conference Location
MIND 2019: International Conference on Machine Learning, Image Processing, Networks and Data Sciences will be organized at Kurukshetra, India. This is the place where the conference is organized and the research paper is to be presented.
