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Theme : Modernization and advancements in AI

ABOUT CONFERENCE

Scietech International welcomes you to “Annual Summit on Artificial Intelligence and Smart Technology” Scheduled during October 12-14, 2020 in Paris, France. We are privileged to host high-profile keynote speakers around the world. 
 The Annual Summit on Artificial Intelligence and Smart Technology covers every concept of Machine Learning, Regression, Supervised Learning, Unsupervised Learning, Reinforced Learning, Natural Language Processing, Cognitive Computing, and Deep Learning covering each function of Artificial Intelligence. The main objective of the Annual Summit on Artificial Intelligence and Smart Technology is to bring together experts in photogrammetry and remote sensing, surveying, robotics, computer vision, artificial intelligence, aerospace engineering, Geosciences, and various UAS user communities. Annual Summit on Artificial Intelligence and Smart Technology is a great opportunity to learn about the most recent developments and to exchange views on the future directions in Geomatics research, applications, and services. 

Why to Attend? 

 Annual Summit on Artificial Intelligence and Smart Technology will be composed of a three-day international conference designed with a cluster of scientific and technological sessions and several collocated Plenary Sessions, Keynote Speeches, Oral Presentations, Poster Presentations, International Workshops, Best Poster awards, Best Oral presentation awards, Young Researcher Forums ,e-Poster presentations, Video presentations by the experts. AI & Smart Technology is a unique platform to bring together worldwide Experts to improve the education of a Scientist through the International Annual Smart Technology. 

The benefits provided to the attendees are: 
  •  Certificates will be provided to all speakers, delegates, and students 
  •  Opportunity to meet the world’s renowned People at this event 
  •  Keynote forums by Prominent Physicians & Professors 
  •  Best platform for Global business and networking opportunities 
  •  Oral/Poster presentations by Young Researchers 
  •  Best poster award for students. 

Target Audience: 
 • Researchers 
 • Scientists 
 • City planners 
 • Future Policy Makers 
 • Smart Innovators 
 • Space Science Engineers 
 • Mechanical Engineers 
 • Electrical Engineers 
 • Computer Science Engineers 
 • Robotic Technologist 
 • Design Engineers 
 • Law Professionals 
 • Gaming professionals 
 • Automation Industry Leaders 
 • Health Care Service Providers 
 • Defense Research Professionals 
 • Automation Industry Leaders 
 • Managers & Business Intelligence Experts 
 • Advertising and Promotion Agency Executives 
 • Professionals in media sector 
 • Professors 
 • Students 

Scientific Sessions:  

Track 1: Data fusion
 The Artificial Intelligence 2020 Conference is planned to present within a single forum all of the improvements in the field of multi-sensor, multi-source, multi-process data fusion, and the Data fusion is the process of integrating multiple data sources to produce truer, scientific, and useful information than that provided by any individual data source. 
 Relevant Societies: 
The European Coordinating Committee on AI (ECCAI)
Finnish Artificial Intelligence Society FAIS 
Association Française pour l'Intelligence Artificielle 

Track 2: Machine learning and computing 
 Artificial Intelligence 2020 Intent to advertise the integration of machine learning and computing. The main target of the Artificial Intelligence conference would be on newfangled machine learning and computing. 
Relevant Societies: 
Fachbereich Künstliche Intelligenz der Gesellschaft für Informatik 
Hellenic Artificial Intelligence Society 
Neumann János Számítógéptudományi Társaság 

Track 3: Machines and Minds
 The Artificial Intelligence 2020 conference would suggest abstracts related to the Machines and Minds. Machines and Minds can activate states of recreation, concentration, and in some cases altered states of sensibility, which have been compared to those access from meditation and shamanic exploration. Discussions would be on the Knowledge and Its Representation, of Computer Programming, Artificial Intelligence and Computer Methodology.
Relevant Societies
Artificial Intelligence Association of Ireland 
Israeli Association for Artificial Intelligence 
Associazione Italiana per l'Intelligenza Artificiale 

Track 4: Virtual Intelligence
 Virtual intelligence is the term given to AI 2020 that exists within a virtual world. Many virtual worlds have choices for persistent avatars that give an information, training, role-taking part in, and social interactions. The immersion of virtual worlds provides a unique platform for Virtual intelligence beyond the normal paradigm of past user interfaces. What Alan Turing established as the benchmark for telling the distinction between human and computerized intelligence was done void of visual influences.
Relevant Societies:
Japanese Society for Artificial Intelligence 
Latvijas Automatikas Nacionala Organizacija 
Lietuvos Kompiuterininku Sajunga 

Track 5: Decision Management
 Decision management is outlined as an associate degree "emerging vital discipline, because of a rising have to be compelled to automatize high-volume selections across the enterprise and to impart exactitude, consistency, and legerity within the decision-making process”. Call management is enforced "via the usage of rule-based systems and analytic models for sanctioning high-volume, machine-driven call making”. Organizations request to reinforce the price created through each call by deploying package solutions that higher manage the trade-offs between exactitude or accuracy, consistency, agility, speed or call latency, and price of decision-making among organizations. 
Relevant Societies: 
Sociedad Mexicana de Inteligencia Artificial 
Belgium-Netherlands-Luxembourg Association for Artificial Intelligence 
Norwegian Artificial Intelligence Society
 
Track 6: Big Data Algorithms
 A simple, freely learning algorithm that is often used with big data sets, often as a way of classifying into larger categories that other algorithms can further refine. It has some other constitutional problems that make it well suited to large-scale, high-level clustering. Big knowledge challenges express capturing knowledge, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big knowledge was basically related to 3 key concepts: volume, variety, and speed. 
Relevant Societies:
Associação Portuguesa para a Inteligência Artificial 
Romanian Association for Artificial Intelligence 
Russian Association for Artificial Intelligence 

Track 7: Big Data Analysis 
 The construct of substantial knowledge has been around for years; most organizations at present perceive that if they taking all the information that streams into their businesses, they will apply analytics and get significant value from it. But even within the1950s, decades before anyone verbalized the term “big knowledge”, businesses were using basic analytics to uncover insights and trends. The new advantages that substantial knowledge analytics brings to the table, however, are speed and potency. Whereas some years past a business would have gathered data, run analytics and unearthed data that would be used for future decisions, these days that business will determine insights for immediate decisions. The ability to work quicker – and keep agile – offers organizations a competitive edge they didn’t have before. 
Relevant Societies: 
Slovenská spolocnost pre kybernetiku a informatiku pri Slovenskej akadémii vied 
Slovensko drustvo za umetno inteligenco 
Associació Catalana d'Intelligència Artificial 

Track 8: Data Mining 
 Data mining is that the strategy of inventing patterns in large data sets involving ways that at the intersection of machine learning, statistics, and information systems. Data mining is an associate degree knowledge domain subfield of computing associate degreed statistics with an overall goal to extract info from a knowledge set and rework the data into a plain Structure for further use. The distinction between information analysis and data processing is that information analysis is employed to check models and hypotheses on the dataset, e.g., analyzing the effectiveness of a promoting Campaign, notwithstanding the quantity of data; in distinction, data processing uses machine-learning and applied math models to uncover secret or hidden patterns during a massive volume of information. 
Relevant Societies: 
 Asociación Española para la Inteligencia Artificial 
Swedish Artificial Intelligence Society 
Swiss Group for Artificial Intelligence and Cognitive Science 

Track 9: Cloud Computing 
 Cloud computing is that the on-demand convenience of ADPS resources considerably information storage and computing power, whereas not direct active management by the user. The term is mostly used to describe ‘information centers’ available to several users over the web. Large clouds, predominant nowadays, typically have functions distributed over multiple locations from central servers. If the connection to the user is comparatively close, it should be designated an edge server. Clouds is also limited to one organization (enterprise clouds), be available to several organizations (public cloud), or a mix of each (hybrid cloud). Cloud computing depends on sharing of resources to attain coherence and economies of scale. 
Relevant Societies: 
Taiwanese Association for AI 
Association of Developers and Users of Intelligent Systems 
The Society for the Study of Artificial Intelligence and Simulation of Behaviour 

Track 10: Brain Computing Interface
 A brain-computer interface (BCI), typically noted as a neural-control interface (NCI), mind-machine interface (MMI), direct neural interface (DNI), or brain-machine interface (BMI), might be an immediate communication pathway between associate degree Increased or wired brain and an external device. BCI differs from neuromodulation therein it permits for biface info flow. BCIs square measure typically directed at researching, mapping, assisting, augmenting, or repairing human psychological feature or sensory-motor functions. 
Relevant Societies: 
British Computer Society, Specialist Group on Artificial Intelligence 
Association for the Advancement of Artificial Intelligence 
Association for Computing Machinery (ACM) 

Track 11: Quantum Machine Learning
 Quantum machine learning is associate degree rising knowledge domain analysis space at the intersection of natural philosophy and machine learning. The foremost common use of the term refers to machine learning algorithms for the analysis of classical information dead on a quantum laptop, i.e. quantum-enhanced machine learning. Whereas machine learning algorithms area unit won’t to figure Brobdingnag Ian quantities of knowledge, quantum machine learning will increase such capabilities showing intelligence, by making opportunities to conduct analysis on quantum states and systems. This includes hybrid strategies that involve each classical and quantum process, wherever computationally troublesome subroutines area unit outsourced to a quantum device. These routines will be a lot of complicated in nature and dead quicker with the help of quantum devices. 
Relevant Societies: 
AssociationforComputingMachinery 
Special Interest Group in Artificial Intelligence (ACM SIGART) 
Computing Research Association 

Track 12: Social Network Analytics
 Social network analysis is that the method of work social structures through the utilization of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things inside the network) and also the ties, edges, or links (relationships or interactions) that connect them. samples of social structures normally pictured through social network analysis embrace social media networks, memes unfold, info circulation, friendly relationship and acquaintance networks, business networks, information networks tough operating relationships, social networks, collaboration graphs, kinship, and unwellness transmission, These networks square measure typically pictured through sociograms during which nodes square measure delineate as points and ties square measure delineate as lines. These visualizations offer a method of qualitatively assessing networks by variable the visual illustration of their nodes and edges to mirror attributes of interest. 
Relevant Societies: 
Florida Artificial Intelligence Research Society 
IEEE Computer Society 
The IEEE Computational Intelligence Society
 
Track 13: Knowledge Representation and reasoning
 Knowledge illustration and reasoning is that the field of computer science (AI) dedicated to representing info regarding the globe in a very kind that a ADP system will utilize to unravel advanced tasks like diagnosis a medical condition or having a dialog in very linguistic communication. Information illustration incorporates findings from science regarding however humans solve issues and represent information so as to style formalisms which will create advanced systems easier to style and build. Information illustration and reasoning conjointly incorporates finding from logic to alter numerous types of reasoning, like the applying of rules or the relations of sets and subsets. 
Relevant Societies: 
The International Neural Network Society 
Singularity Institute of Artificial Intelligence 
Argentine Society for Informatics and Operations Research (SADIO) Grupo de Interés en Inteligencia Artificial 

Track 14: Expert Systems 
 In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of artificial intelligence (AI) software. An expert system is divided into two subsystems: the inference engine and the knowledge base. The knowledge base represents facts and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging abilities. 
Relevant Societies: 
Sociedade Brasileira de Computação 
Bulgarian Artificial Intelligence Association 
Canadian Artificial Intelligence Association / Association pour l'intelligence artificielle au Canada

Track 15: Deep Learning 
 Deep Learning may be a machine learning technique that constructs artificial neural networks to mimic the structure and performance of the human brain. In apply, deep learning, additionally called deep structured learning or gradable learning, uses an outsized range hidden layers -typically over half-dozen however usually a lot of higher - of nonlinear process to extract options from knowledge and remodel the info into completely different levels of abstraction. 
Relevant Societies: 
The European Coordinating Commitee on AI (ECCAI) 
Finnish Artificial Intelligence Society FAIS 
Association Française pour l'Intelligence Artificielle 

Track 16: Internet of Things
 The Internet of Things is simply "A network of Internet connected objects able to collect and exchange data." It is commonly abbreviated as lot. The word "Internet of Things" has 2 main parts; web being the backbone of property, and Things which means objects / devices. Consumer connected devices include good TVs, good speakers, toys, wearable’s and smart appliances. Smart meters, industrial security systems and good town technologies -- like those wont to monitor traffic and climate -- are samples of industrial and enterprise web of Things devices. 
Relevant Societies: 
Artificial Intelligence Association of Ireland 
Israeli Association for Artificial Intelligence 
Associazione Italiana per l'Intelligenza Artificiale 

Track 17: Neural systems
 The neural systems square measure structures that build, support, and study the inner world through natural computing where they facilitate and organize the growing complexity of bodily process transmission of knowledge. Neural systems are consistent and primarily based in specific parts classified by location, connections, and performance. In several animals, significantly mice and rats, brain elements known as barrels are directly related to specific body components and are visible in brain sections with standard and special strategies. 
Relevant Societies: 
Lietuvos Kompiuterininku Sajunga 
Sociedad Mexicana de Inteligencia Artificial 
Belgium-Netherlands-Luxembourg Association for Artificial Intelligence 

Track 18: Computer vision and perception
 Computer vision is Associate in nursing content scientific field that deals with but computers is formed to attain high-level understanding from digital photos or videos. From the attitude of engineering, it seeks to automatize tasks that the human visual system will do. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information. Perception (from the Latin perception) is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information, or the environment. All perception involves signals that go through the system nervous, that in turn result from physical or chemical stimulation of the sensory system. 
Relevant Societies:
Belgium-Netherlands-Luxembourg Association for Artificial Intelligence 
Norwegian Artificial Intelligence Society 
Associação Portuguesa para a Inteligência Artificial 

Track 19: Evolutionary Computation
 Artificial Intelligence 2020 would be discussing on the assorted topics like nature-inspired algorithms, population-based ways, and improvement wherever choice and variation square measure integral, and hybrid systems wherever these paradigms square measure combined. 
Relevant Societies: 
Swedish Artificial Intelligence Society 
Swiss Group for Artificial Intelligence and Cognitive Science 
Taiwanese Association for AI 

Track 20: Cyber Defense
 Cyber defense might be a network process that has response to actions and significant infrastructure protection and knowledge assurance for organizations, government entities and various potential networks. Cyber defense focuses on preventing, detection and providing timely responses to attacks or threats thus no infrastructure or data is tampered with. With the growth in volume also as complexity of cyber-attacks, cyber defense is essential for many entities in order protect sensitive information as well as to safeguard assets. 
Relevant Societies: 
Pacific Rim International Conferences on Artificial Intelligence 
Österreichische Gesellschaft für AI 
Sociedade Brasileira de Computação
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MARKET RESEARCH


Market Analysis:According to the new market research report "Artificial Intelligence Market by Offering (Hardware, Software, Services), Technology (Machine Learning, Natural Language Processing, Context-Aware Computing, Computer Vision), End-User Industry, and Geography - Global Forecast to 2025", the Artificial Intelligence Market is expected to be valued at USD 21.5 billion in 2019 and is likely to reach USD 190.6 billion by 2025, at a CAGR of 36.6% during the forecast period. Major drivers for the market are growing big data, the increasing adoption of cloud-based applications and services, and an increase in demand for intelligent virtual assistants. The major restraint for the market is the limited number of AI technology experts. Critical challenges facing the AI market include concerns regarding data privacy and the unreliability of AI algorithms. Underlying opportunities in the artificial intelligence market include improving operational efficiency in the manufacturing industry and the adoption of AI to improve customer service. 
European nations are spending more energy and fund on research, given the great public attention currently devoted to Artificial Intelligence and Big Data. Robotics and AI offer huge opportunities for this region and points towards the clear need for an articulate European approach. Europe already has a strong presence and investment in this technology which is helping it to maintain leadership in this sector. It has set up SPARC, the Public-Private Partnership for robotics in Europe, which will help to develop a robotics strategy for Europe. SPARC has €700 million EU funding and, adding private investment, an overall investment of €2.8 billion. At the same time, Europe is in a strong position, both scientifically and commercially to look for the technologies of the future.

WHY TO ATTEND?


Annual Summit on Artificial Intelligence and Smart Technology will be composed of a three-day international conference designed with a cluster of scientific and technological sessions and several collocated Plenary Sessions, Keynote Speeches, Oral Presentations, Poster Presentations, International Workshops, Best Poster awards, Best Oral presentation awards, Young Researcher Forums ,e-Poster presentations, Video presentations by the experts. AI & Smart Technology is a unique platform to bring together worldwide Experts to improve the education of a Scientist through the International Annual Smart Technology.

WHY CHOOSE US

WHY CHOOSE US


  • Scietech International is initiated to meet a need or to pursue collective goals of the scientific community, especially in exchanging the ideas which facilitate growth of research and development.
  • We specialize in organizing conferences, meetings and workshops internationally to overcome the problem of good and direct communication between scientists, researchers working in same fields or in interdisciplinary research.
  • Scietech Group promotes open discussions and free exchange of ideas at the research frontiers mainly focusing on science field.
  • Intense discussions and examination based on professional interests will be an added advantage for the scientists and helps them learn most advanced aspects of their field.
  • It proves that these conferences provide a technique for valuable means of disseminating information and ideas that cannot be achieved by usual channels of communications.
  • To encourage an informal community atmosphere usually we select conference venues which are chosen partly for their scenic and often isolated nature.
  • In sinuations from many scientists and their reviews on our conferences reflected us to continue organizing annual conferences globally.
  • The conference proceedings are regularly publicized in respective journals and details of such proceedings are displayed in the individual conference website.

Target Audience


Researchers 
Scientists 
City planners 
Future Policy Makers 
Smart Innovators 
Space Science Engineers 
Mechanical Engineers 
Electrical Engineers 
Computer Science Engineers 
Robotic Technologist 
Design Engineers 
Law Professionals 
Gaming professionals 
Automation Industry Leaders 
Health Care Service Providers 
Defense Research Professionals 
Automation Industry Leaders 
Managers & Business Intelligence Experts 
Advertising and Promotion Agency Executives 
Professionals in media sector 
Professors 
Students

Don’t Miss This Event

Great Event Schedule

Time Session
9:00-9:15 Registrations
9:15-9:30 Keynote Forum Opening Ceremony
9:30-11:30 Session Keynote Forum
11:30-11:45 Networking and Refreshment Break
11:45-13:00 Sessions
13:00-13:40 Lunch Break
13:40-15:30 Sessions
15:30-15:45 Networking and Refreshment Break
15:45-17:45 Sessions
17:45-18:00 Panel Discussion
Time Session
9:15-10:45 Keynote Forum
10:45-11:15 Networking and Refreshment Break
11:15-13:00 Sessions
13:00-13:45 Lunch Break
13:45-15:30 Sessions
15:30-15:45 Networking and Refreshment Break
15:45-17:00 Poster Presentations and Panel discussion
Time Session
Time Session

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