IEEE AIML4COINS2020 | Artificial Intelligence | Machine Learning | Deep Learning | Machine Vision | Big Data Analytics | Video Analytics | Speech Recognition | NLP
IEEE AIML4COINS 2020
- URL: https://coinsconf.com/
- Event Date: 2020-07-27 ~ 2020-07-29
- Submission Date: 2020-03-06
- Location: Barcelona, Spain
Supported and organized by IEEE Robotics and Automation Society, IEEE Council on Electronic Design Automation, IEEE Circuits and Systems Society, IEEE e-Health Technical Committee (ComSoc), and IEEE Big Data Technical Committee (ComSoc).
The Artificial Intelligence, Machine Learning, and Advanced Analytics track at COINS encourages original and high-quality submissions related to one or more of the following topics (but not limited to):
Machine learning architectures and formulations
Machine learning and artificial intelligent systems analysis, modelling, simulation, and application in different domains
Platforms, architecture and infrastructure for efficient data analytics
Novel computational intelligence methods and improvement of existing algorithms
Human-driven Artificial Intelligence for Smarter Hyper-Connected Societies
Learning from IoT Data
Regression, Classification and Clustering for big data analysis
Intelligence inference in Edge/Fog/Cloud computing and IoT
Reinforcement learning
Data acquisition and cleaning techniques
Data modeling, representation, transformation, and integration techniques
Data mining and machine learning algorithms for IoT Big Data
Intelligent algorithms for Fog and cloud-based Internet of Things
Machine learning on chip and at edge
Deep learning models, architectures and algorithms
Big Data, Large Scale Methods
Brain-inspired representations learning of Big Data
Streaming data learning algorithms
Evolutionary computing in Big Data
Swarm Intelligence and Big data for IoT
AI-driven performance optimization for IoT
Distributed Intelligent Information Systems
Transfer, low-shot, semi- and un- supervised learning
Speech Recognition
3D computer vision
Action and behavior recognition
Adversarial learning, adversarial attack and defense methods
Biometrics, face, gesture, body pose
Computational photography, image and video synthesis
Datasets and evaluation
Image retrieval
Motion and tracking
Neural generative models, auto encoders, GANs
Optimization and learning methods
Recognition (object detection, categorization)
Representation learning, deep learning
Scene analysis and understanding
Segmentation, grouping and shape
Video analysis and understanding
Visual reasoning and logical representation
Natural Language Processing
Crowd Sensing and Human Intelligence
Open issues for data management and analytics in IoT
Case studies in different domains
The Artificial Intelligence, Machine Learning, and Advanced Analytics track at COINS encourages original and high-quality submissions related to one or more of the following topics (but not limited to):
Machine learning architectures and formulations
Machine learning and artificial intelligent systems analysis, modelling, simulation, and application in different domains
Platforms, architecture and infrastructure for efficient data analytics
Novel computational intelligence methods and improvement of existing algorithms
Human-driven Artificial Intelligence for Smarter Hyper-Connected Societies
Learning from IoT Data
Regression, Classification and Clustering for big data analysis
Intelligence inference in Edge/Fog/Cloud computing and IoT
Reinforcement learning
Data acquisition and cleaning techniques
Data modeling, representation, transformation, and integration techniques
Data mining and machine learning algorithms for IoT Big Data
Intelligent algorithms for Fog and cloud-based Internet of Things
Machine learning on chip and at edge
Deep learning models, architectures and algorithms
Big Data, Large Scale Methods
Brain-inspired representations learning of Big Data
Streaming data learning algorithms
Evolutionary computing in Big Data
Swarm Intelligence and Big data for IoT
AI-driven performance optimization for IoT
Distributed Intelligent Information Systems
Transfer, low-shot, semi- and un- supervised learning
Speech Recognition
3D computer vision
Action and behavior recognition
Adversarial learning, adversarial attack and defense methods
Biometrics, face, gesture, body pose
Computational photography, image and video synthesis
Datasets and evaluation
Image retrieval
Motion and tracking
Neural generative models, auto encoders, GANs
Optimization and learning methods
Recognition (object detection, categorization)
Representation learning, deep learning
Scene analysis and understanding
Segmentation, grouping and shape
Video analysis and understanding
Visual reasoning and logical representation
Natural Language Processing
Crowd Sensing and Human Intelligence
Open issues for data management and analytics in IoT
Case studies in different domains
Journal Promotion
|
| Acta Koreana (Acta Koreana) |
|
| Acta Via Serica (AVS) |
|
| Computers and Concrete (CAC) |
|
| Journal of Information Processing Systems (JIPS) |
|
| Journal of Internet Computing and Services (KSII - JICS) |
|
| Journal of Smart Tourism (Smart Tourism) |
|
| Membrane and Water Treatment (MWT) |
|
| Wind and Structures, An International Journal (Wind and Structures) |
MANUSCRIPTLINK © 2015 -
