人工智能 | 国际会议/SCI期刊约稿信息9条

人工智能

HumL 2018

International workshop on Augmenting Intelligence with Humans­-in-­the-­Loop

摘要截稿: 2018-01-19

全文截稿: 2018-01-26

开会时间: 2018-04-24

会议难度: ★★★

CCF分类: 无

会议地点: Lyon, France

网址：https://humlworkshop.github.io/

HumL 2018, is the first international workshop on Augmenting Intelligence with Humans­-in-­the-­Loop, co-located with TheWebConf.

Human­-in-­the-­loop is a model of interaction where a machine process and one or more humans have an iterative interaction. In this paradigm the user has the ability to heavily influence the outcome of the process by providing feedback to the system as well as the opportunity to grab different perspectives about the underlying domain and understand the step by step machine process leading to a certain outcome. Amongst the current major concerns in Artificial Intelligence research are being able to explain and understand the results as well as avoiding bias in the underlying data that might lead to unfair or unethical conclusions. Typically, computers are fast and accurate in processing vast amounts of data. People, however, are creative and bring in their perspectives and interpretation power. Bringing humans and machines together creates a natural symbiosis for accurate interpretation of data at scale. The goal of this workshop is to bring together researchers and practitioners in various areas of AI (i.e., Machine Learning, NLP, Computational Advertising, etc.) to explore new pathways of the human­in­the­loop paradigm.

人工智能

CogArch 2018

WORKSHOP ON COGNITIVE ARCHITECTURES

全文截稿: 2018-02-05

开会时间: 2018-03-24

会议难度: ★★★★

CCF分类: 无

会议地点: Williamsburg, VA, USA

网址：http://cogarch-workshop.org/

Recent advances in Cognitive Computing Systems (as evidenced by innovations like Watson from IBM and AlphaGo from Google DeepMind), coupled with neurally-inspired hardware designs (such as the IBM TrueNorth chip and Tensor Processing Units (TPU) from Google), have spawned new research and development activity in machine learning, neuromorphic and other brain-inspired computing models, and architectures for efficient support of complex tasks in computer vision, speech recognition and artificial intelligence. The proliferation of mobile computing platforms, Internet-of-Things and cloud support features thereof have opened up exciting new opportunities for real-time, mobile (distributed or swarm-driven) cognition. This half-day workshop solicits formative ideas and new product offerings in this general space. Topics of interest include (but are not limited to):
-Algorithms in support of cognitive reasoning: recognition, intelligent search, diagnosis, inference and informed decision-making.
-Swarm intelligence and distributed architectural support; brain-inspired and neural computing architectures.
-Prototype demonstrations of state-of-the-art cognitive computing systems.
-Accelerators and micro-architectural support for cognitive computing.
-Approaches to reduce training time and enable faster model delivery.
-Cloud-backed autonomics and mobile cognition: architectural and OS support thereof.
-Resilient design of distributed (swarm) mobile cognitive architectures.
-Energy efficiency, battery life extension and endurance in mobile, cognitive architectures.
-Case studies and real-life demonstrations/prototypes in specific application domains: e.g. Smart homes, connected cars and UAV-driven commercial services, as well as applications of interest to defense and homeland security.

人工智能

HCOMP 2018

AAAI Conference on Human Computation and Crowdsourcing

摘要截稿: 2018-02-19

全文截稿: 2018-02-23

开会时间: 2018-07-05

会议难度: ★★★

CCF分类: 无

会议地点: Zurich, Switzerland

网址：https://www.humancomputation.com/2018/

The 6th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2018) will be held July 5–8 in Zurich, Switzerland at the University of Zurich. HCOMP 2018 will be co-located with the conference on Collective Intelligence (CI 2018).

HCOMP is the premier venue for disseminating the latest research findings on crowdsourcing and human computation. While artificial intelligence (AI) and human-computer interaction (HCI) represent traditional mainstays of the conference, HCOMP believes strongly in inviting, fostering, and promoting broad, interdisciplinary research. This field is particularly unique in the diversity of disciplines it draws upon, and contributes to, ranging from human-centered qualitative studies and HCI design, to computer science and artificial intelligence, economics and the social sciences, all the way to digital humanities, policy, and ethics. We promote the exchange of advances in human computation and crowdsourcing not only among researchers, but also engineers and practitioners, to encourage dialogue across disciplines and communities of practice.

人工智能

IRCE 2018

IEEE International Conference on Intelligent Robotic and Control Engineering

全文截稿: 2018-03-05

开会时间: 2018-07-28

会议难度: ★★

CCF分类: 无

会议地点: Chengdu, China

网址：http://www.irce.org/

It is our great pleasure to invite you to join the International Conference of Intelligent Robotic and Control Engineering (IRCE), which is sponsored by IEEE, co-organised by University of Electronic Science and Technology of China, Shandong Technology and Business University. This event will provide unique opportunity to have fruitful discussions about Intelligent Robotics, Automations and Control Engineering, and best practices that address Artificial Intelligence. The IRCE conference aims to foster interdisciplinary and international collaboration opportunities, and strengthen domestic and international recognition in pure and applied research for the participants.

Accepted and presented papers will be published by IEEE conference proceedings. Published papers are expected to be included in IEEE Xplore and indexed by EI Compendex, Scopus etc.

Interested topics including, but not limited to:
-Intelligent Robotics
-Robot control, Mobile robotics
-Evolutionary Robotics, Medical/ Surgical Robots
-Humanoid Robotics, Entertainment Robots
-Rehabilitation Robotics, Micro/Nano Robotics
-Underwater Robots
-Robot sensing and data fusion
-Automations & Control Engineering
-Man-machine interactions
-Process automation
-Intelligent automation
-Factory modeling and simulation
-Computational intelligence in automation
-Home, laboratory and service automation
-Artificial Intelligence
-Agents
-Fuzzy systems
-AI Architectures and Applications
-Computer Games
-Computer Vision Data Mining

人工智能

UAI 2018

International Conference on Uncertainty in Artificial Intelligence

全文截稿: 2018-03-09

开会时间: 2018-08-06

会议难度: ★★★★

CCF分类: B类

会议地点: Monterey, CA, USA

网址：http://www.auai.org/uai2018/cfp.php

The Conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier international conferences on research related to knowledge representation, learning, and reasoning in the presence of uncertainty. UAI 2018 will be held in Monterey, California, on August 6-10, 2018. The main conference will take place on August 7-9, with tutorials on August 6 and workshops on August 10.

UAI solicits submission of papers which describe novel theories, methodology and applications related to knowledge representation, learning, and reasoning under uncertainty. A non-exclusive list of subject areas can be found here. We welcome submissions by authors who are new to the UAI conference, or on new and emerging topics. We encourage submissions on applications, especially those that inspire new methodologies.

人工智能

IC3 2018

International Cognitive Cities Conference

全文截稿: 2018-03-15

开会时间: 2018-08-07

会议难度: ★★

CCF分类: 无

会议地点: Okinawa, Japan

网址：http://iscie.org/IC3/

The First International Cognitive Cities Conference (IC3), August 7-9, 2018, Okinawa, Japan.

The cities around the world are vibrant and thriving, often be regarded as the initial experimental field for corresponding most immediate issues. Recently, there are many emergency trends included population aging, global warming, food crisis and environmental pollution to affect cities. The intersection of these trends poses issues and challenges to cities. Meanwhile, rapid systems and infrastructures of intelligence and cognitive are developped to provide city resident smarter services efficiently. However, it is difficult to archive the more cognitive depended on existing techniques, models. How to construct the theoretical framework for advanced improvements of cognitive cities becomes a critical issue. IC3 2018 will provide an open platform to exchange each others' research results and experience in the topics from cognitive cities and other related fields.  

This conference features all recent advances in an integral concept that highlights the trends in advanced theory, systems and applications for cognitive cities.

人工智能

KSEM 2018

International conference on Knowledge Science,Engineering and Management

全文截稿: 2018-04-14

开会时间: 2018-08-17

会议难度: ★★★

CCF分类: C类

会议地点: Changchun, China

网址：http://ksem2018.venue.link

KSEM 2018 will be held in Changchun, China on August 17-19, 2018. KSEM is in the list of CCF (China Computer Federation) recommended Conferences (C series, Artificial Intelligence).

The aim of this interdisciplinary conference is to provide a forum for researchers in the broad areas of knowledge science, knowledge engineering, and knowledge management to exchange ideas and to report state of the art research results. The conference committee invites submissions of applied or theoretical research and application-oriented papers on all topics of KSEM. Topics include, but are not limited to the following:
-Knowledge representation and reasoning
-Logics of knowledge; formal analysis of knowledge; reasoning about knowledge
-Knowledge complexity and knowledge metrics
-Commonsense knowledge; nonmonotonic reasoning
-Uncertainty in knowledge (randomness, fuzziness, roughness, vagueness, etc.)
-Reasoning about knowledge in the presence of inconsistency, incompleteness, context-dependency, etc.
-Belief revision and update
-Cognitive foundations of knowledge
-Knowledge in complex systems (e.g. economical and quantum systems)
-Game-theoretical aspects of knowledge; knowledge in multiagent systems
-Formal ontology
-Knowledge extraction from texts/big data/Web
-Knowledge discovery from very large databases
-Knowledge integration
-Knowledge-based software engineering
-Knowledge-based systems in life sciences
-Conceptual modelling in knowledge-based systems
-Semantic database systems
-Semantic Web
-Content engineering
-Ontological engineering
-Knowledge engineering applications
-Knowledge creation and acquisition
-Knowledge verification and validation
-Knowledge dissemination
-Knowledge management systems
-Organizational ontology
-Organizational memory
-Organizational learning
-Knowledge management strategies and practices
-Knowledge management applications

人工智能

Neurocomputing

Special Issue on Deep Learning for Image Super-Resolution

全文截稿: 2018-08-31

影响因子: 3.317

CCF分类: C类

中科院JCR分区:

  • 大类 : 工程技术 - 2区

  • 小类 : 计算机：人工智能 - 3区

网址: http://www.journals.elsevier.com/neurocomputing/

The goal of image super-resolution (SR) is to restore a visually pleasing high-resolution (HR) image from a low-resolution (LR) input image or video sequence. HR images have higher pixel densities and finer details than LR images. Image SR has been proved to be of great significance in many applications, such as video surveillance, ultra-high definition TV, low-resolution face recognition and remote sensing imaging. Benefiting from its broad application prospects, SR has attracted huge interest, and currently is one of the most active research topics in image processing and computer vision.

Early interpolation-based image SR methods are extremely simple and fast. Unfortunately, severe aliasing and blurring effects make interpolation-based SR suboptimal in restoring fine texture details. Reconstruction-based image SR methods combine elaborately designed image prior models with reconstruction constraints, and can restore fine structures. However, these image priors usually are incapable of modeling complex and varying contexts of natural image.

In the past decade, most researches focus on learning-based image SR. It utilizes machine learning techniques to capture the relationships between LR image patches and their HR counterparts from some samples. Recently due to fast advances in deep learning, deep network-based SR has shown promising performance in certain applications. However, there are still many challenging open topics of deep learning for image SR, e.g. new objective functions, new architectures, large scale images, depth images, various types of corruption, and new applications.

Therefore, this special issue emphasizes the important role of deep learning for image SR. It aims to call for the state-of-the-art researches in the theory, algorithm, modeling, system and application of deep learning-based SR and to demonstrate the latest efforts of relevant researchers.

The list of possible topics includes, but is not limited to:

- Review/survey/vision of deep learning for SR

- New image databases for deep learning for SR

- New objective functions of deep learning for SR

- New deep network architectures for SR

- Combining deep learning with traditional SR approaches

- Combining deep learning with image priors

- Deep learning for large scale SR

- Deep learning for SR with different or unknown types of corruption

- Deep learning for video sequence SR

- Deep learning for SR for special types of images

- Deep learning for depth image SR

- Hybrid RGB and depth image SR with deep learning

- Acceleration of deep learning for SR

- Hardware and systems of deep learning for SR

- Deep learning-based SR applications in video surveillance, ultra-high definition TV, face hallucination, biometrics, medical imaging, remote sensing, LR face recognition, etc.

人工智能

Pattern Recognition Letters

Virtual Special issue on Intelligent Industrial Digital Forensics and Biocybernetics: Practices and Challenges

全文截稿: 2019-03-31

影响因子: 1.995

CCF分类: C类

中科院JCR分区:

  • 大类 : 工程技术 - 3区

  • 小类 : 计算机：人工智能 - 4区

网址: http://www.journals.elsevier.com/pattern-recognition-letters/

Digital forensic methodologies are widely used in industries to ensure authentication of multimedia data. Biocybernetics has emerged as a tool to secure systems from cyber threats via biometric based processes. Jointly, digital forensics and biocybernetics can ensure support system for high level security. The mechanisms of digital forensics and biocybernetic technologies presently need human expert interference, and cannot perform in automated way. Thereby these processes cannot be suited for in large scale industrial need in their present form. Hence a lot of research has been conducted in this domain during last few years, mostly all studies yielding sub-optimal solutions, which still encourages current researchers to conduct further research in this area.

This special issue solicits original research articles, extensive reviews, and case studies in the aforementioned field of research.

Topics include, but are not limited to:
• Digital Forensic techniques applicable to large scale systems
• Biocybernetic architecture management
• Biosignal processing and biosensing systems
• Brain-human-interface
• Knowledge sharing systems for forensic analysis
• Biocybernetic surveillance in industry
• Anti-pattern search for biocybernetic spoofing
• Biometric technologies for large scale industry
• Industrial biometric data management
• Parallel and distributed processing of forensic data
• Cybercrime detection and mitigation
• Uberveillance technologies for smart industry
• Standards and protocols for industrial forensics

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