Call for Abstract
Scientific Program
International Congress on AI and Machine Learning, will be organized around the theme “Deploying the knowledge on AI and Robotics on the edge”
Artificial Intelligence 2021 is comprised of 21 tracks and 41 sessions designed to offer comprehensive sessions that address current issues in Artificial Intelligence 2021.
Submit your abstract to any of the mentioned tracks. All related abstracts are accepted.
Register now for the conference by choosing an appropriate package suitable to you.
Cloud computing services have morphed from platforms such as Google App Engine and Azure to Infrastructure which involves the provision of machines for computing and storage. The points in the direction of the growth of Artificial Intelligence and Cloud Computing. About 90% of early cloud adopters claim that cloud technology will play an important role in their Artificial Intelligence initiatives in the coming years. And more than 55% of users chose cloud-based services and are leveraging SaaS and PaaS to execute and deploy AI-infused cloud results. Cloud Machine Learning Platforms: technologies like AWS ML, Azure ML and the upcoming Google Cloud ML use a technology that is held responsible for powering the creation of Machine Learning models. But excepting Google Cloud ML that leverages Tensor Flow can be difficult because a large number of cloud ML technologies won’t allow implementation of AI programs coded in conventional AI.
Artificial intelligence technology is evolving daily and Business Insider Intelligence keeping its finger on the pulse of how artificial intelligence will shape the future of a variety of industries, such as Internet of Things, transportation and logistics, digital health, and multiple branches like
- AI in Science and Research
- AI in Cyber Security
- AI in Data Analysis
- AI in Transport
- AI in Home
- AI in Healthcare
- Track 2-1AI in Science and Research
- Track 2-2AI in Cyber Security
- Track 2-3AI in Data Analysis
- Track 2-4AI in Transport
- Track 2-5AI in Healthcare
Artificial intelligence can help in reduce human error, to create more precise analytics, and turn data collecting devices into powerful diagnostic tools. One example of this is wearable devices such as smart watches and fitness trackers, which put data in the hands of consumers to empower them to play a more active role managing their health. Learn more about how tech start-ups are using AI to transform industries like digital health and transportation.
Artificial intelligence techniques are used to detect abnormal activity and identify new types of malware. There are lots of applications used for cyber security purpose like
- Security screening
- AI-powered threat detection
- Detection of sophisticated cyber-attacks
- Security & crime prevention
- Track 4-1Security screening
- Track 4-2AI-powered threat detection
- Track 4-3Detection of sophisticated cyber-attacks
- Track 4-4Security & crime prevention
The AI technologies are rapidly increasing in the field of automotive manufacturing industry. The Robots are taking a great participation in automotive manufacturing.
- Robots are used in Mechanical Cutting, Grinding, Debarring and Polishing.
- Robots Assemble the smaller components pumps and performing tasks like windshield installation.
- Robots do Painting for highly toxic paints that the Professional painters are difficult to do.
- Robots do welding cars it is very necessary for the automotive sector.
AI technologies have high importance to healthcare. To increase the effective pathway in health care and medical science the artificial intelligence is adopted. AI is used as
- Physical robots for surgery assistance
- Drug discovery with aid AI/ML techniques
- Identifying rare or difficult to diagnose diseases
- Radiotherapy
E-Commerce businesses around the world are using artificial intelligence to advance the trends and also to providing the features for interactive buying experiences. Most of the E-Commerce websites are using AI features like image search, Virtual Fitting Rooms, advertising automation for Sellers, Chatbots. Artificial Intelligence will continue to assist the e-commerce businesses in the areas of the
- Customer experience
- Website and app optimization
- Fraud detection
Countries across the globe have been running on the race to explore space for a century now so the space exploration process is also adopting Artificial Intelligence (AI) and robotics to fast-track their mission
- GPS To navigate space travel efficiently and it will be easy to explore planets
- CIMON – Crew Interactive Mobile Companion is a head shaped robot used in international space station .This AI based device assists the astronauts in the space. CIMON helps in inventory management, documenting experiments, videography, and photography. Cimon acts like a hands free database, computer.
- SKICAT – Sky Image Cataloguing and Analysis Tool identified what was beyond human capabilities. It classified thousands of objects in low resolution during the second Palomar Sky Survey.
Artificial intelligence and its applications are endless and are applied in all disciplinary.
- AI In Banking
- AI In Finance
- AI In Agriculture
- AI In HealthCare
- AI In Gaming
- AI In Space Exploration
- AI In Autonomous Vehicles
- AI In Artificial Creativity
Developing the AI and ML application is long and it requires lot of through behind the implement of an application so we have the Tools and frameworks that are available for the developers and data scientists. They are:
- TestCraft
- Applitools
- Functionize
- Testim
- Mabl
- Sealights
- ReTest
- Tensorflow
- Caffe
- Auto ML
- Open NN
- MXNet
- Google ML Kit
- H20: Open Source AI Platform
- CNTK
- Track 10-1TestCraft
- Track 10-2Applitools
- Track 10-3Functionize
- Track 10-4Testim
- Track 10-5Mabl
- Track 10-6Sealights
- Track 10-7ReTest
- Track 10-8Tensorflow
- Track 10-9Caffe
- Track 10-10Auto ML
- Track 10-11Open NN
- Track 10-12MXNet
- Track 10-13Google ML Kit
- Track 10-14H20: Open Source AI Platform
- Track 10-15CNTK
Artificial intelligence and machine learning algorithms are designed to make decisions, often using real-time data these are the algorithms used in AI and ML.
- K Nearest Neighbours
- Linear Regression
- Logistic Regression
- Support Vector Machine
- K Means
- Decision Tree
- Principal Component Analysis
- Apriori
- Track 11-1K Nearest Neighbours
- Track 11-2Linear Regression
- Track 11-3Logistic Regression
- Track 11-4Support Vector Machine
- Track 11-5K Means
- Track 11-6Decision Tree
- Track 11-7Principal Component Analysis
- Track 11-8Apriori
AI branch of computer science by which we can create intelligent machines which can behave like a human, think like humans, and able to make decisions. So AI also called as "a man-made thinking power." Artificial intelligence is one of the booming technologies of computer science which is ready to create a new revolution in the world by making intelligent machines.AI makes it possible for machines to learn from experience, to perform human-like tasks. These machines make decisions which normally require a human level of expertise.
Computer vision is a part of artificial intelligence that enables a machine to understand the visual world. With the help of computer vision, a computer system can precisely locate and identify images and videos to fetch meaningful information from the real world Artificial intelligence helps computer vision to serve the following purposes
- Self-driving cars
- Facial recognition
- AR and mixed reality
Learning is the fundamental building blocks of artificial intelligence it helps in improving the knowledge of Artificial intelligence programming.AI learning processes focused mainly on processing of a collection of input-output pairs for a specific function and predicts the outputs for new inputs. The learning models used in AI and ML are:
- Reinforcement Learning
- Supervised Learning
- Semi-supervised Learning
- Unsupervised Learning
- Track 14-1Reinforcement Learning
- Track 14-2Supervised Learning
- Track 14-3Semi-supervised Learning
- Track 14-4Unsupervised Learning
Human-Robot Interaction (HRI) is a involving in several disciplines field of study and it mainly focusing on computer technology. HRI is one of the challenging research fields in the intersection of psychology, cognitive science, the social sciences, artificial intelligence, computer science, robotics, and engineering. Generally people's exposure to robots in their daily lives like robotic toys, household appliances like robotic vacuum cleaners or lawn movers.
When most people hear the term artificial intelligence, the first thing they usually think of robots. A robot is a mechanical device that is capable of performing a variety of tasks on command or according to instructions programmed in advance so a robot perform a task easily and with greater accuracy Some everyday examples of robots are
- Automatic teller machines (ATMs)
- Remote control cars and trucks
- Vending machines
- Track 16-1Automatic teller machines (ATMs)
- Track 16-2Remote control cars and trucks
- Track 16-3Vending machines
An artificial neural network (ANN) are computing systems and information processing models these are inspired by biological neurons that are designed to simulate the way the human brain analyses and processes information. ANN is the foundation of artificial intelligence (AI) and it solves problems that would prove impossible or difficult by human or statistical standards. Artificial neural networks have self-learning capabilities that enable them to produce better results as more data becomes available.
Big data is a term that describes the large volume of data. The AI technologies used in big data are:
- Anomaly Detection: If anomaly detection is not detected in any data base then big data analytics can be used. fault detection, sensor networks can be detected with big data technology.
- Pattern Recognition: It is a technique of ML used in identifying the patterns in a certain amount of data, with help of training data set the patterns can be identified
- Track 18-1Anomaly Detection
- Track 18-2Pattern Recognition
NLP is a branch of artificial intelligence which deals with the interaction between computers and humans using the natural language. NLP makes it possible for the computers to read text, hear speech, interpret the data , measure sentiment and determine which parts are important mostly NLP techniques rely on machine learning to derive meaning from human languages. Tasks that are used in higher-level NLP are Content categorization, Speech-to-text and text-to-speech conversion, Document summarization, Machine translation.
Deep learning is an AI function that mimics the workings of the human brain in processing data for use in detecting objects, recognizing speech, translating languages, and making decisions. Deep learning is used in all industries for a number of different tasks. Commercial apps that use image recognition, open-source platforms, Virtual assistants, Chatbots and service bots. Deep learning algorithms can automatically translate between languages and these algorithms are also used in medical research tools that explore the possibility of reusing drugs for new ailments. Deep learning allows machines to solve difficult problems even when using a data set that is very diverse, unstructured and inter-connected.
Machine learning is an area of artificial intelligence with the concept of computer program can learn and adapt to new data without human intervention more specifically machine learning. It allows the computer program to automatically improve through experience using computer algorithms. We use machine learning in our daily life like Siri, Google Maps, Virtual assistants Translations.