Welcome Message

Welcome to the highly anticipated 13^th Global Summit on Artificial Intelligence and Neural Networks, taking place as a webinar on March 13-14, 2025. We are excited to announce this year’s theme: “Next-Gen Intelligence: Exploring Frontiers in Artificial Intelligence and Neural Networks.” The summit promises to deliver fresh insights, innovative strategies, and transformative approaches to advance your professional journey.

This premier event brings together leading experts in the field under the banner of Artificial Intelligence Meet 2025. It offers a vibrant platform for researchers, university professors, industry specialists, and students to engage, collaborate, and exchange knowledge. The program features keynote lectures, oral and poster presentations, interactive discussions, and networking opportunities, fostering an enriching experience for all participants.

Attendees will have the chance to showcase their research, gain recognition, and receive certificates of participation from our esteemed organizing committee. Join us for an enlightening journey into the future of Artificial Intelligence.

About Conference

Conference Series warmly invites participants from around the globe to attend the “13th Global Summit on Artificial Intelligence and Neural Networks”, scheduled as a webinar on March 13-14, 2025. This year’s conference will focus on the theme: "Next-Gen Intelligence: Exploring Frontiers in Artificial Intelligence and Neural Networks."

Join us at ARTIFICIAL INTELLIGENCE MEET 2025, where we offer comprehensive packages for an enriching two-day experience. The event includes oral presentations, poster sessions, workshops, symposiums, and special keynote addresses delivered by distinguished speakers who are leaders in the fields of AI and Neural Networks.

Explore the registration options on our website and secure your place at this dynamic and insightful gathering.

Target Audience:

• Researchers and Scientists
• Professors, Engineers and Students
• Smart Innovators
• Architectures
• Software Developers
• Data labelling professionals
• Robotic Technologist
• Computer vision engineers
• Defence Research Professionals
• Artificial Intelligence hardware specialists
• Data protection specialists
• Automation Industry Leaders
• Gaming Professionals
• Managers & Business Intelligence Experts
• Advertising and Promotion Agency Executives

Why to attend the conference?

Artificial Intelligence (AI) promises to transform our lives—enhancing healthcare diagnostics, driving autonomous vehicles, and ushering us into a future where intelligent machines achieve feats beyond our imagination. AI encompasses diverse fields, including Neural Networks, Machine Learning, Robotics, Evolutionary Computation, Computer Vision, Speech Processing, Expert Systems, Planning, and Natural Language Processing.

The aim of this conference is to bring together researchers, academicians, and scientists from the AI and Neural Networks community to foster a global exchange of knowledge. It will serve as a platform to explore technological advancements, innovative scientific developments, and the impact of various regulatory frameworks shaping the future of AI.

Sessions & Trcaks

Track 1: The Next Generation of Artificial Intelligence

The field of computing is rapidly advancing, with numerous emerging technologies designed to simplify and enhance human tasks. However, current computing systems still face several limitations, including a lack of personalization, adaptability, and self-learning capabilities. Newly developed solutions, such as Smart Agents technology, are AI-driven tools that aim to address these gaps, enhancing system capabilities and improving overall performance.

• Machine learning
• Algorithms
• Neural network compression
• Web technologies

Track 2: Development in predictive analytics

Predictive modeling is a mathematical technique used to forecast future events or outcomes by analyzing patterns in a given dataset. It plays a crucial role in predictive analytics, a branch of data analytics that leverages current and historical data to anticipate behaviors, activities, and trends. By identifying patterns and relationships within the data, predictive modeling helps organizations make informed decisions and plan for future scenarios, enhancing overall strategic and operational effectiveness.

• Determine the datasets
• Develop procedures
• software options

Track 3: Digital Avatars

A Digital Avatar is an AI-powered, human-like virtual assistant that facilitates intelligent interactions with customers. 3D avatars serve various purposes, fostering trust by making communication more direct and accessible. Their presence on different platforms is crucial, as they convey professionalism. A digital human that effectively communicates a company's values in a personalized manner can transform visitors into loyal customers. Creating a comprehensive avatar involves several steps, which can be broken down into five key stages.

• STT
• NLP
• TTS
• Articulation

Track 4: AI Ethics

The ethics of computing refers to the branch of technology ethics focused on robots and other artificially intelligent beings. It is typically divided into two main areas: robo-ethics and machine ethics. Robo-ethics concerns the ethical behavior of humans in designing, building, using, and interacting with artificially intelligent beings. It explores issues related to responsibility, fairness, and the impact of AI on society. Machine ethics, on the other hand, focuses on the ethical behavior of artificial agents themselves, addressing questions of moral decision-making, autonomy, and the responsibility of AI systems in carrying out tasks.

• Robot Ethics
• Machine ethics

Track 5: AI for Cyber Security

Cyber security is a major concern in today’s digital world, particularly with the rise of AI technologies. While AI can enhance security measures, it also presents risks, as cybercriminals may exploit similar technologies to access systems without human intervention. However, AI applications in cyber security can help combat these threats by utilizing tools such as security screening, crime prevention systems, AI-powered threat detection, and the identification of sophisticated cyber-attacks. These advanced solutions help safeguard systems, detect vulnerabilities, and mitigate risks, ultimately improving the effectiveness of cybersecurity efforts in combating the growing threat of cybercrime.

• Network security
• Fraud detection
• Intrusion detection

Track 6: AI in Healthcare

Artificial intelligence in healthcare is a broad term used to describe the application of machine learning algorithms and software to simulate human knowledge in the analysis, interpretation, and understanding of complex medical and healthcare data. Specifically, AI refers to the ability of computer algorithms to make predictions or decisions based on data.

The primary goal of AI in healthcare is to analyze the relationships between clinical practices and patient outcomes. AI is applied in various areas, including:

• Treatment protocol development
• Drug development
• Personalized medicine
• Patient monitoring

Track 7: Machine Learning

Machine learning is one of the most exciting technologies, enabling computers to learn how to perform tasks without being explicitly programmed and to improve automatically through experience using algorithms. It is a branch of computing related to statistical methods, focusing on making predictions using computers. However, not all machine learning is based on mathematical learning. Machine learning facilitates the continuous evolution of computing by exposing systems to new situations, testing, and adapting. It leverages pattern and trend detection to enhance decision-making for future outcomes. Key applications of machine learning include:

• Data mining
• Reinforcement learning
• Mathematical optimization
• Exploratory data analysis

Track 8: Robotics and Mechatronics

Robotics and Mechatronics focus on the practical application of existing systems and control strategies. Artificial intelligence is concerned with the design, development, operation, and use of robots, including robot control systems, sensory feedback, and processing. Mechatronics spans various fields, including robotics, computing, telecommunications, and product development, combining elements of software, physics, and mechanical design. Key areas of Mechatronics include:

• Nano robotics
• Machine vision
• Automation and robotics
• Engineering cybernetics

Track 9: Bioinformatics

AI in bioinformatics encompasses both basic and clinical research, utilizing techniques such as biological sequence matching, protein-protein interaction, and function-structure analysis. This research plays a crucial role in drug design and the exploration of complex systems. Bioinformatics is one of the key contributors to the recent advancements in computing. The primary goals of bioinformatics are:

• To manage data in a way that facilitates easy access to existing information and allows for the addition of new entries as they are generated.
• To develop technological tools that aid in the analysis of biological data.

Track 10: Natural Language Processing

Natural Language Processing (NLP) focuses on developing systems that enable computers to communicate with individuals using everyday language. It is broadly divided into two categories: Natural Language Understanding (NLU) and Natural Language Generation (NLG). NLG involves converting information from computer data into clear human language, while NLU interprets and understands human language inputs.

Key components and applications of NLP include:

• Morphological Analysis
• Higher-Level NLP Applications
• Speech Recognition
• Neural Networks

Track 11: Biometrics

With advancements in security technologies, biometric security systems have emerged as a significant upgrade, involving the design and implementation of sensors along with their supporting hardware and software. These systems have achieved remarkable technological advancements and widespread adoption. However, skepticism and concerns about privacy and reliability persist globally.

Biometric security systems are commonly applied in areas such as face recognition and biometric attendance tracking in organizations. Key features and examples include:

• Multimodal Biometric Systems
• Human Dignity Considerations
• Finger Vein Recognition
• Palm Print Authentication

Track 12: Artificial Intelligence in Music

Artificial intelligence (AI) is already being utilized in various applications, and its influence on how people create and consume music is growing rapidly. With the development of AI tools and protocols for audio mastering, tuning, and streaming, AI has emerged as a solution to the increasing demand for music production. As a result, it is likely to have a profound impact on the creative processes of musicians. In the future, artists may need to possess advanced technical knowledge, including insights into neuroscience, to fully integrate AI into their craft.

Track 13: Web-based Training Environment

Web-based training (WBT) is a form of computer-based learning that relies on an internet connection to deliver content and facilitate communication. Rooted in the principles of distance learning, WBT typically eliminates the need for face-to-face interaction between learners (or trainees) and instructors. This method of training has gained significant popularity due to the widespread availability of internet access and the interactive potential it offers. The two-way flow of information enabled by the internet creates an effective environment for training and education. By utilizing the web as a delivery platform, WBT maximizes opportunities for peer interaction and engagement with the learning system.

Most web-based training programs are designed to leverage these possibilities to enhance understanding and learning outcomes. Key elements and concepts associated with WBT include:

• Learning Management Systems
• Web-Based Instruction
• E-Instruction
• Distance Learning

Track 14: Artificial Neural Networks

Artificial neural networks (ANNs) are based on the idea that they can mimic the structure and function of biological neurons by using hardware components, such as circuits and wires, to replicate neurons and dendrites. These networks aim to collaborate with the human brain by forming appropriate connections. An artificial neural network is a computational model inspired by biological principles, consisting of processing units (nodes), connections, and algorithms for training and recall. Various types of neural networks exist, including Feedforward ANN, Feedback ANN, Learning Vector Quantization, and others.

Key concepts and models related to neural networks include:

• Supervised Models
• Physical Neural Networks
• Networks with Memory Models
• Recurrent Neural Networks (RNNs)

Track 15: Artificial Intelligence in Gaming

In today’s gaming industry, artificial intelligence (AI) has significantly enhanced both gameplay experience and design. AI-powered features and applications in video games have transformed various aspects of gaming, making them more engaging and immersive. These advancements help sustain players' interest and satisfaction over extended periods. AI often operates through mechanisms that are not directly visible to the user, such as data mining and procedural content generation, which work behind the scenes to optimize the gaming experience.

Key AI applications in gaming include:

• Computer Simulations of Board Games
• Monte Carlo Tree Search Method

Track 16: Deep Learning

Deep learning, also known as deep structured learning, is a subset of machine learning focused on learning data representations. It typically utilizes gradient descent for training through back propagation. The architecture of deep learning involves multiple layers, including hidden layers in artificial neural networks and sets of propositional formulas. A Deep Neural Network (DNN) is an artificial neural network with multiple hidden layers between the input and output layers. DNN architectures create hierarchical models where an object is represented as a layered composition of simpler elements. These networks are often feed forward neural networks, where data flows from the input layer to the output layer without feedback loops.

Applications of deep learning include:

• Automatic Speech Recognition
• Image Recognition
• Visual Art Processing
• Natural Language Processing (NLP)

Track 17: Convolutional Neural Network Model

Convolutional Neural Networks (CNNs) are specialized types of multilayer perceptrons, which are fully connected networks where each neuron in one layer is connected to all neurons in the next layer. CNNs are most commonly used in deep learning for visual image analysis.

They are widely applied in tasks such as image and video recognition, recommender systems, image classification, medical image analysis, language processing, and financial analytics.

Key concepts and applications of CNNs include:

• Receptive Fields in the Visual Cortex
• Neural Abstraction Pyramid
• Depth-Based CNNs
• Electromyography (EMG) Recognition

Track 18: Cloud Computing

Cloud computing is a branch of information technology that provides on-demand access to shared pools of virtualized computing resources. These clouds can support various workloads, enabling rapid scaling and deployment using physical or virtual machines. They are self-healing, support redundancy, and employ highly scalable programming models, while also allowing for hardware/software rebalancing and failure mitigation.

In the context of cloud computing, artificial intelligence plays a crucial role in enhancing resource management, ensuring transparent distribution, and enabling measurable openness. By working in synergy, AI and cloud computing are poised to significantly shape the future of data technology.

Key types of cloud computing include:

• Private Clouds
• Public Clouds
• Hybrid Clouds
• Multiclouds

Track 19: Self-Organizing Neural Networks

The study of patterns and regularities in data is a fundamental aspect of machine learning, with pattern recognition being a prominent application. This involves using supervised learning algorithms to develop classifiers trained on data from various object categories. Supervised pattern recognition enables applications such as optical character recognition (OCR), face detection, face recognition, object detection, and object classification. In contrast, unsupervised learning identifies hidden structures within data using clustering techniques.

Feature selection, also known as variable selection, is the process of identifying a subset of relevant features for model development. It helps reduce overfitting, shorten training times, and simplify models for better interpretability by eliminating unnecessary or redundant features with minimal or no loss of information.

Key phases in pattern recognition include:

• Learning Phase
• Prediction Phase

Track 20: Ambient Intelligence

Ambient Intelligence (AmI) refers to the integration of computing devices into environments that adapt intelligently and sensitively to the presence and needs of individuals. These environments are designed to consider people's preferences, specific requirements, and predictive behaviors. AmI can be applied in various settings, such as homes, offices, conference rooms, schools, management centers, and vehicles. The primary objective of AmI research is to enhance the intelligence of these environments, enabling seamless interaction and providing users with the necessary information to make informed decisions.

Key features of Ambient Intelligence include:

• Embedded (integrated into the environment)
• Context-Aware (responsive to situational changes)
• Personalized (tailored to individual preferences and needs)

Market analysis

Artificial Intelligence Market: Size and Trends

The global artificial intelligence (AI) market was valued at USD 196.63 billion in 2023 and is expected to grow at a CAGR of 36.6% from 2024 to 2030. Continuous innovation by tech giants drives AI adoption across industries like automotive, healthcare, retail, finance, and manufacturing. For example, Google LLC launched the ‘Gemini’ AI model in December 2023, notable for its multimodal capabilities and availability in three versions: Nano, Pro, and Ultra. Major companies, including Amazon, Apple, Microsoft, and IBM, are heavily investing in AI R&D to enhance enterprise applications and improve customer experiences.

Advancements in data storage, accessibility to historical datasets, and next-generation computing have accelerated innovation. Industries leverage AI technologies, such as Artificial Neural Networks (ANN), to recognize patterns and offer tailored solutions. Emerging methods like Generative Adversarial Networks (GAN) and Single Shot MultiBox Detector (SSD) are revolutionizing digital imaging, aiding fields like healthcare and surveillance.

The COVID-19 pandemic further boosted AI adoption, with remote work increasing demand for tech solutions. Companies like LogMeIn and Clarifai expanded their offerings to meet rising global needs.

The advertising and media sector led the AI market in 2023, accounting for the largest revenue share, driven by growing applications in AI-driven marketing. For instance, Cadbury's 2022 initiative allowed small businesses to create ads featuring a celebrity’s face and voice using AI tools.

By 2030, healthcare is expected to dominate the market with use cases such as robot-assisted surgeries, virtual nursing assistants, automated image diagnosis, and hospital workflow management. Meanwhile, the BFSI sector utilizes AI for financial analysis, risk management, compliance, and supervisory technologies (SupTech). Financial institutions are also adopting AI for proactive fraud prevention through behavioral insights.

Other key sectors include retail, automotive, and agriculture. Retail AI is projected to grow significantly due to the demand for enhanced shopping experiences and data analytics. Additionally, conversational AI platforms are increasingly adopted across industries, while governments emphasize AI-driven safety solutions in automotive technology.

Benefits of Participation

Types of participation

ARTIFICIAL INTELLIGENCE MEET 2025, provides the participants with different modes or ways to participate under either Academic / Student / Business Category

1. Keynote speaker: 45-50 minutes
2. Speaker (oral presentation): 25-30 minutes (only one person can present)
3. Speaker (workshop): 45-50 minutes (more than 1 can present)
4. Speaker (special session): 45-50 minutes (more than 1 can present)
5. Speaker (symposium): more than 45 minutes (more than 1 can present)
6. Delegate (only registration): will have access to all the sessions with all the benefits of registration
7. Poster presenter: can present a poster and enjoy the benefits of delegate
8. Remote attendance: can participate via virtual mode or video presentation or e-poster presentation
9. Exhibitor: can exhibit his/her/their company’s products by booking exhibitor booths of different sizes
10. Media Partner
11. Sponsor
12. Collaborator

Advantages of Participating in our Conference

• Attendees will be certified with an International Speaker participation certificate
• The Speaker and Abstract pages that Google creates on your profile under your name would give you global visibility.
• Our Library of Abstracts receives more than 30,000 visits per month and 50 thousand views, which brings scholars and speakers to our Conference.
• Interactive meetings will be provided, if you are coming with your research squad
• Meet and exchange ideas with many of thought leaders in the Artificial Intelligence, Neural Networks and Machine learning.
• Young scientist award & Best Poster certificates
• Each conference attendee would have a different motivation for engaging in one-on-one discussions with distinguished speakers and recognized keynote speakers.
• At our Keynote presentations, you'll have the exceptional chance to hear what the world's foremost authorities on Artificial Intelligence and Neural Networks are discovering.

Benefits of Participation for Speaker

• All accepted abstracts will be published in the respective Journals
• Attendees will be certified with an International Speaker participation certificate
• Admiration for researchers' profiles on a global scale.
• Obtain points for your professional development.
• Discover the most recent cutting-edge analysis.
• Become lifelong friends through social and networking activities.
• An opportunity to promote one page through the distribution of abstract books and flyers, which eventually receive 1 million views and greatly enhance your research profile.
• Learn about new topics and studies that are unrelated to your primary subject of Artificial Intelligence and Neural Networks field by making a transition outside of your field of interest.
• We've combined exceptional networking, education, and fun into one bundle.

Benefits of Participation for Delegate

• Increased knowledge and understanding for professional development.
• Attending conferences and webinars helps participants feel refreshed and energized.
• Your participation in our conference will support the development of a new approach and philosophy that can be used to improve business or industry results.
• Opportunities for Artificial Intelligence and Neural Networks field scholars and practitioners to connect and share new perspectives at our conference.

Benefits of Participation for Sponsor

• The likelihood of new businesses would rise with exposure to the global marketplace.
• A chance to showcase your business's most cutting-edge innovations, products, or services to a large international audience.
• Lead generation will help our conference participants do more business.
• To draw energy from others who have a similar purpose and objective, it's always helpful to have a network of co-workers and associates. Building a successful firm takes a lot of time, effort, and drive.
• Conferences and Webinars on Artificial Intelligence and Neural Networks offer chances for greater thought and reflection, which might help you, advance your business.
• Comparing the major organization's plans and advancing them.
• Get answers to your company's queries and difficulties at our conference from reliable people.

Benefits of Participation for Collaborators

• No other website has this many visits, making “Artificial Intelligence Meet 2025” the finest platform for bringing attention to society.
• Establishing enduring peer ties.
• Your organization's logo, branding and marketing materials, promotional content, and the conference banner will all work together to add 40% more subscribers and members to your list.
• Your association will be greatly impacted by the visibility of our event to your company's placement in the Global Business forum.
• Your representatives can interact with important delegates to update their knowledge and comprehension of your organization and services.
• Information will be incorporated into Artificial Intelligence Meet 2025 advertising materials such as posters, brochures, pamphlets, and services that will be distributed to hospitals, universities, the general public, and researchers.

Having trouble in registration?

Please contact Ms. Alice Mary via machinelearning@memeetings.com. The team of Artificial Intelligence Meet 2025 will provide you the INVOICE for the requested price with which he/she can make the Bank-to-Bank transfer.