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11th Global Summit on Artificial Intelligence and Neural Networks, will be organized around the theme “"The Next Evolution in Digital Transformation"”

NEURAL NETWORKS 2023 is comprised of keynote and speakers sessions on latest cutting edge research designed to offer comprehensive global discussions that address current issues in NEURAL NETWORKS 2023

Submit your abstract to any of the mentioned tracks.

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The science of computing is speedily evolving, with several technologies getting used that will create it easier for humans to finish numerous tasks. We have seen that gift computing systems have variety of limitations, as well as a scarcity of personalization, ability, and self-learning capabilities. With freshly developed options, sensible Agents technology is Associate in Nursing AI tool that may scale back the shortage of capability.

  • Track 1-1Machine learning
  • Track 1-2Algorithms
  • Track 1-3Neural network compression
  • Track 1-4Web technologies

Predictive modeling may be a mathematical operation accustomed predicts future events or outcomes by analyzing patterns in a very given set of computer file. It’s a vital element of prognosticative analytics, a kind information of knowledge of information analytics that uses current and historical data to forecast activity, behaviour and trends.

  • Track 2-1Determine the datasets
  • Track 2-2Develop procedures
  • Track 2-3Software options

A Digital Avatar is Associate in Nursing AI-powered human-like virtual assistant that allows intelligent interactions with customers. 3D avatars may be used for various functions and that they produce a way of trust by creating communication with the purchasers direct and straightforward. Their use on varied platforms is critical, as they convey a way of seriousness. The utilization of a digital human that swimmingly communicates the values of the corporate in a very specific method, can convert these guests into trustworthy customers. A comprehensive avatar's creation involves a lot of steps. This complicated method may be lessened into 5 stages.

  • Track 3-1STT
  • Track 3-2NLP
  • Track 3-3Recommender System
  • Track 3-4TTS
  • Track 3-5Articulation

The ethics of computing is that the part of the ethics of technology specific to robots and alternative unnaturally intelligent beings. It’s generally divided into robo ethics, a priority with the ethical behaviour of humans as they style, construct, use and treat unnaturally intelligent beings, and machine ethics, that thinks about with the ethical behaviour of artificial ethical agents.

Robot Ethics:  

The term "robot ethics" (robo ethics) refers to the morality of however humans style, construct, use and treat robots and different unnaturally intelligent beings. It considers each however unnaturally intelligent beings could also be wont to damage humans and the way they will be wont to profit humans.

Cyber security is one of the main concerns for today’s digital world for functions of security by exploitation AI rising technologies. AI will improve security also a similar technology will offer cyber criminals access to systems with no human intervention. AI applications with Cybersecurity can overcome the issues with cybercriminals by exploitation some tools like security screening, security & crime bar, AI-powered threat detection, and Detection of refined cyber-attacks.

  • Track 5-1Network security
  • Track 5-2Fraud detection
  • Track 5-3Intrusion detection

Artificial intelligence in health care is associate overarching term accustomed describe the utilization of machine-learning algorithms and software package, or AI (AI), to mimic human noesis within the analysis, presentation, and comprehension of advanced medical and health care knowledge. Specifically, AI is that the ability of laptop algorithms to approximate conclusions based mostly entirely on computer file.

The primary aim of health-related AI applications is to research relationships between clinical techniques and patient outcomes. AI programs square measure applied to practices like as below

  • Track 6-1Diagnostics
  • Track 6-2Treatment protocol development
  • Track 6-3Drug development
  • Track 6-4Personalized medicine
  • Track 6-5Patient monitoring

Machine learning is one amongst the foremost exciting technologies that involve computers discovering, however they'll perform tasks while not being expressly programmed and mechanically improves through the expertise of victimization algorithms. It’s a set of computing associated with procedure statistics. It focuses on creating forecasts victimization computers, however not all machine learning is applied mathematics learning. It facilitates the continual advancement of computing through exposure to new situations, testing, and adaptation whereas using pattern and trend detection for improved choices in resulting things.

  • Track 7-1Data mining
  • Track 7-2Reinforcement learning
  • Track 7-3Mathematical optimization
  • Track 7-4Exploratory data analysis

Robotics and Mechatronics square measure primarily involved with the sensible application of current systems and management strategies. Artificial intelligence worries with the configuration, development, operation, design, and use of automatons like a robot management system, sensory feedback, and processing. Robotics, computers, telecommunications, products, and lots of additional fields square measure lined by Mechatronics that uses a mixture of code, physical science, and mechanical style.

  • Track 8-1Nano robotics
  • Track 8-2Machine vision
  • Track 8-3Automation and robotics
  • Track 8-4Engineering cybernetics

AI in bioinformatics includes each basic moreover as clinical analysis with the assistance of biological sequence matching, protein-protein interaction and function-structure analysis. This analysis helps within the style and discovery of medication moreover as complicated systems. Bioinformatics is one amongst the main contributors of the current innovations in computing. The main goals of Bioinformatics are

  • Track 9-1To manage data in such a way that it allows easy access to the existing information and to submit new entries as they are produced
  • Track 9-2To develop technological tools that help analyze biological data

Natural Language process focuses on system development that enables computers to speak with individual’s victimization everyday language. It’s divided into 2 classes are tongue Understanding and tongue Generation. This tongue generation is employed to converts data from the pc info into clear human language and contrariwise.

  • Track 10-1Morphological analysis
  • Track 10-2Higher-level NLP applications
  • Track 10-3Speech recognition
  • Track 10-4Neural networks

As new technologies are developed for security purposes, the biometric security system is one of the most recent upgrades, which comprises the design and implementation of the sensor's enabling hardware and software. Biometric security systems have come a long way in terms of technological breakthroughs and general adoption, but there is still a lot of scepticism about the technology around the world. Face recognition and biometric access for attendance in an organisation are examples of how it is utilised.

  • Track 11-1Multimodal biometric system
  • Track 11-2Human dignity
  • Track 11-3Finger vein
  • Track 11-4Palm print

Artificial intelligence is already being used during a sort of applications. Currently it is time to believe what quantity it'll have an effect on however folks build and consume music. With the event of multiple protocols and AI tools like audio mastering, tuning, and streaming the music. AI has become a solution to a straightforward demand: additional music is required than ever before. It should have a major impact on any musician's artistic method, and artists within the future could also be needed to own in-depth technical information of neurosciences.

Web-based coaching (WBT) could be a type of computer-based learning that depends on a web association to share content and support communication. In its origins, this sort of apply relates to distance learning because it principally doesn't need face-to-face interaction between the learner, or trainee, and also the teacher.

This type of coaching is turning into a lot of widespread thanks to the provision of web access and also the indisputable fact that the two-way info flow out there over the net creates a decent setting for a training system. With the net operating as a learning delivery tool, the chances of interaction between peers and with the educational system area unit large. Most web-based coaching programs specialize in applying those potentialities to assist understanding and learning.

  • Track 13-1Learning management system
  • Track 13-2Web-based instruction
  • Track 13-3E-instruction
  • Track 13-4Distance learning
  • Track 13-5Blended courses

Artificial neural networks square measure supported on the assumption that they will be imitated victimization element and wires as living neurons and dendrites to join forces with the human brain by creating the right connections. A man-made neural network could be a procedure model supported biological principles that contains of process parts and connections between them, moreover as coaching and recall algorithms. Feed Forward ANN, Feed Back ANN, Learning vector quantisation, and lots of different kinds of neural networks exist.

  • Track 14-1Supervised model
  • Track 14-2Physical neural networks
  • Track 14-3Networks with the memory model
  • Track 14-4Recurrent neural network

If you scrutinize today’s AI application within the gaming industry, you'll note that AI is especially upgraded in-game expertise and style. They need totally different parts that are supercharged by computing and connected applications in video diversion options. It additionally helps to extend the player's interest and satisfaction over an extended amount of your time. AI uses some mechanisms that don't seem to be like a shot visible to the user that's associated with data processing and procedural-content generation.

  • Track 15-1Computer simulations of board games
  • Track 15-2Monte Carlo tree search method

Deep learning is additionally referred to as deep structured learning could be a part of machine learning method supported learning information illustration. It uses some variety of gradient descent for coaching via backpropagation. The layers used in deep learning include hidden layers of artificial neural networks and sets of propositional formulas.

Deep Neural Networks is associate degree ANN with multiple hidden layers between the input and output layers. DNN architectures generate integrative models wherever the item is expressed as a superimposed composition of primitive. They’re generally fed forward neural networks during which knowledge flows from the input layer to the output layer while not process back.

  • Track 16-1Automatic speech recognition
  • Track 16-2Image recognition
  • Track 16-3Visual art processing
  • Track 16-4Natural language processing

Convolutional neural networks (CNN) area unit regular versions of multilayer perceptron, that area unit absolutely connected networks to every vegetative cell in one layer that area unit fastened to any or all neurons within the following layer, and area unit most generally utilized in deep learning to analyse visual pictures. Image and video recognition, recommender systems, image classification, medical image analysis, linguistic communication process and monetary statistic area unit simply some of CNN's uses.

  • Track 17-1Receptive fields in the visual cortex
  • Track 17-2Neural abstraction pyramid
  • Track 17-3Depth based CNN’s
  • Track 17-4Electromyography (EMG) recognition

Cloud computing is a subfield of information technology that provides open access to shared reservoirs of virtualized computer resources. A cloud may host a variety of workloads, allowing them to be expanded or deployed out quickly using physical or virtual machines, self-recovering, supporting redundant, highly scalable programming models, and allowing them to pass through hardware/software rebalancing and failure allocations.

In especially for cloud computing applications, artificial intelligence technology is crucial in developing the resources made available, the transparency of the distribution, and the quantifiability of openness. By working together in a mutually beneficial way, AI and cloud computing can significantly influence the future of data technology.

  • Track 18-1Private clouds
  • Track 18-2Public clouds
  • Track 18-3Hybrid clouds
  • Track 18-4Multiclouds

The study of patterns and regularities in knowledge is a key component of machine learning, and pattern recognition is one such application. This is done by utilising supervised learning algorithms to create classifiers that are backed by training data from a variety of object categories. With the use of supervised pattern recognition, optical character recognition (OCR) can detect faces, identify faces, identify objects, and classify objects. Unsupervised learning consequently operates by identifying hidden structures using clustering techniques.

The process of choosing a subset of pertinent features to be used in model creation is known as feature selection or variable selection. Additionally, they are utilised to reduce overfitting, shorten training times, and simplify the models to make them easier to understand (reduction of variables). Numerous characteristics in the data are unnecessary or redundant, and they can be deleted with little to no information loss.

  • Track 19-1Learning phase
  • Track 19-2Prediction phase

Ambient intelligence (AMI) refers to the use of computing devices in surroundings that behave intelligently and cautiously around people. These settings should consider people's preferences, particular needs, and prognosticating behaviours. There are many other things that it could be, including houses, conference rooms, offices, schools, management centres, cars, etc. The goal of AI research is to add more intelligence to AMI surroundings so that people can interact with them with greater ease and have access to the information they need to make better decisions.

  • Track 20-1Embedded
  • Track 20-2Context aware
  • Track 20-3Personalized
  • Track 20-4Anticipatory