Artificial Intelligence Congress 2018 invites honorable speakers, researchers, PhD. students and exhibitors from all over the world to attend and register for the “International Artificial Intelligence Congress” which is going to be organized from October  25th-26th, 2018 at Amsterdam, Netherlands. We invite you to accompany us at the Artificial Intelligence Congress 2018, where you are assured to have a substantially worthwhile experience with global scholars.

Session-1: Artificial Neural Network

An Artificial Neural Network (ANN) is an information taking care of perspective that is animated by the way natural tangible frameworks, for instance, the cerebrum, process information. The key part of this perspective is the novel structure of the information planning system. It is made out of a broad number of interconnected taking care of segments (neurons) filling in as one to handle specific issues.

ANNs are made out of different center points, which emulate natural neurons of human personality. The neurons are related by associations and they coordinate with each other. The centers can take enter data and perform essential undertakings on the data. The outcome of these exercises is passed to various neurons. The yield at each center point is called its institution or center point regard.

Artificial Intelligence Meetings | Artificial Neural Network Symposia | Artificial Neural Network Workshops | Artificial Neural Network Congress

Session-2: K Nearest Neighbor

KNN is a kind of case based learning, or emotionless perceiving, where the most remote point is simply approximated locally and all count is surrendered until delineation.

K-Nearest Neighbors is a champion among the most central and essential portrayal figurings in Machine Learning. It has a place with the controlled learning space and discovers striking application in plot confirmation, data mining and impedance locale.

It is broadly pointless, in fact, conditions since it is non-parametric (it doesn't make any secured assumptions about the course of data). KNN has for the most part high exactness. It is flexible in nature i.e. it is useful for classification or regression.

Artificial Intelligence Meetings | Artificial Neural Network Symposia | Artificial Neural Network Workshops |Artificial Neural Network Congress

Session-3: Machine Learning

Machine learning teaches computers to do what comes naturally to humans and animals which they learn from experience. Machine learning algorithms use computational methods to gain information directly from data without relying on a predetermined equation as a model. As the number of samples available for learning increases, the performance of the machine increases.

Machine learning algorithms find natural patterns in data that generate insight and help you make better decisions and predictions. They are every day used to make difficult decisions in medical diagnosis, stock trading, energy load forecasting, and more.

Machine Learning Meetings | Machine Learning Symposia | Machine Learning Workshops | Machine Learning Congress

Session-4: Support Vector Machine

Support Vector Machine (SVM) is a classifier technique that performs arrangement of tasks by building hyper planes that isolates instances of various class names. SVM supports regression as well as classification tasks which can handle different types of variables. Support Vector Machines are based on the concept of decision planes that define decision boundaries.

Support Vector Meetings | Support Vector Symposia | Support Vector Workshops | Support Vector Congress

Session-5: Image Processing

Image Processing is a method to perform any operation on an image, either to get an enhanced image or to find out any characteristic about the image. It is kind of signal processing. Here the input is an image and the output can be an image or any feature of an image. Image Processing is basically used for visualization, image retrieval, image enhancement, etc.

Image Processing Meetings | Image Processing Symposia | Image Processing Workshops | Image Processing Congress

Session-6: Data Mining

Data Mining is a process mostly used for converting raw data into some useful information. Data mining is also known as Knowledge Discovery in Data. Data Mining focuses on large data sets & database. Data Mining is widely used in business, science research, security, etc.

Data Mining Meetings | Data Mining Symposia | Data Mining Workshops | Data Mining Congress

Session-7: Robotics

A robot is a multitasking controller intended to move materials, devices or specific gadgets through programming to perform variety of tasks. A robot is a system that contains sensors, control frameworks, controllers, control supplies and programming all cooperating together to perform a task. Robots have supplanted humans in performing dreary assignments and perilous errands which people lean toward not to do or can't do.

Robotics Meetings | Robotics Symposia | Robotics Workshops | Robotics Congress | Smart Robotics Conference

Session-8: Virtual Intelligence

Virtual Intelligence is a term given to computerized reasoning that exists inside a virtual world. Virtual Intelligence is the crossing point of Virtual Environment and Artificial Intelligence. Virtual Intelligence is a program intended to make PC frameworks less demanding to utilize. Virtual Intelligence is a thoroughly program based machine i.e. they are not mindful.

Virtual Intelligence Meetings | Virtual Intelligence Symposia | Virtual Intelligence Workshops | Virtual Intelligence Congress

Session-9: Watson

Watson created by IBM in 2010 as a question answering computing system. As a system, it is described as a heterogeneous ensemble of experts. The supercomputer IBM Watson consumes all the data & gives doctors the relevant information to a particular case, giving them access to better diagnostic information.

Artificial Intelligence Meetings | Artificial Neural Network Symposia | Artificial Neural Network Workshops |  Artificial Neural Network Congress

Session-10: Drones

Drones also known as unmanned aerial vehicles (UAVs) which has no human pilot onboard, and is either controlled by a person on the ground or autonomously via a computer program. These stealth craft are becoming increasingly popular for war, military purposes, wildlife, atmospheric research to disaster relief and sports photography, archaeological sites, signs of illegal hunting and crop damage.

Artificial Intelligence Meetings | Artificial Neural Network Symposia | Artificial Neural Network Workshops

Session-11: Deep Learning

Deep learning also known as deep structured learning or hierarchical learning is part of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised. ‘Deep Learning’ means using a neural network with several layers of nodes between input and output. The series of layers between input & output do feature identification and processing in a series of stages, just as our brains seem to.

Deep Learning Meetings | Deep Learning Symposia | Deep Learning Workshops | Artificial Neural Network Congress

Session-12: Speech & Pattern Recognition

In speech analysis, the voiced-unvoiced decision is performed in conjunction with the pitch analysis. The linking of voiced unvoiced (V-UV) decision to pitch analysis  results in unnecessary complexity, as well as makes it difficult for classification of short speech segments which are less than a few pitch periods in duration.

Pattern recognition is a part of machine learning that emphasis on the recognition of patterns. Pattern recognition systems are in many cases trained from supervised learning, but when no data are available other algorithms can be used to discover previously unknown patterns i.e. unsupervised learning.

Artificial Intelligence Meetings | Artificial Neural Network Symposia | Artificial Neural Network Workshops

The global artificial intelligence market size was valued at USD 641.9 million in 2016 on the basis of its direct revenue sources and at USD 5,970.0 million in 2016 on the basis on enabled revenue and AI based gross value addition (GVA) prognoses. The market is expected to reach USD 35,870.0 million by 2025 by its direct revenue sources, growing at a CAGR of 57.2% from 2017 to 2025, whereas it is expected to reach around USD 58,975.4 million by 2025 from its enabled revenue arenas.

The AI market includes end-use verticals such as healthcare, BSFI, law, retail, advertising & media, automotive and transportation, agriculture, manufacturing, and others. The advertising & media segment dominated the overall market and accounted for over 20% of the total market share in 2016. The AI Market by healthcare application further segregated in to use-cases including, robot assisted surgery, virtual nursing assistants, hospital workflow management, dosage error reduction, clinical trial participant identifier, preliminary diagnosis, and automated image diagnosis. Additionally BFSI applications market further includes, risk assessment, financial analysis/research, investment/portfolio management solicitations.

Societies On Artificial Intelligence:

•  Society for the study of artificial intelligence and simulation of behavior, United Kingdom
•  Association for the advancement of artificial intelligence, United Sates
• Artificial intelligence society
• Canadian Artificial Intelligence Association, Canada
• Chilean society of computer science, Chile
• Association for Computing Machinery(ACM), United States
• IEEE Computer Society, United States
• Association of Developers and Users of Intelligent Systems, Ukraine

Universities in Amsterdam related to Artificial Intelligence:

• Utrecht University
• University of Groningen
• University of Amsterdam
• Maastricht University
• Radboud University
• Vrije Universiteit (VU University)

Universities related to Artificial Intelligence :

• Carnegie Mellon University, Pittsburgh, USA
• Stanford University, Stanford, California
• Massachusetts Institute of Technology , Cambridge, United States
• University of California, Oakland, United States
• Harvard University, Cambridge, USA
• Yale University, New Haven, USA
• Cornell University, Ithaca, USA
• University of Maryland, College Park, USA
• Columbia University, New York City, USA
•  University of Texas, Austin, USA
• University of California, Los Angeles,
• University of Michigan, Ann Arbor, USA
• Georgia Institute of Technology, Atlanta, USA
• University of Sheffield, Sheffield, United Kingdom
• University of Wollongong, Wollongong, Australia
• Coventry University, Coventry, United Kingdom
• University of Manitoba, Winnipeg, Canada
• Universiti Utara Malaysia, Kedah,  Malaysia

Companies related to the field of Artificial Intelligence:

• DeepMind
• Google
• Facebook
• IBM
• Open AI
• Baidu
• Microsoft Research
• Apple
• Active.ai
• Alndra Systems
• Amazon
• Cloud Minds
• Intel
• Twitter