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145 articles for “Human neural networks”
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BIS Processes in the Human Neural Networks and Asymptotic Periodic Solutions of the Evolution Equations in the Brain Nanosystem using Jacobi Elliptic Function
Abstract: Our perseverance is dependent upon the normal functioning and fluctuation of the brain. That functioning involves complex electrical activities. These in turn generate subtle waves which were first noticed and studied by Hans Berger. These are essentially electrical rhythms in the brain which, when recorded by means of instruments called electroencephalograms or EEG on a roll of paper, appear as complex wave forms. In this paper, based on Jacobi elliptic …
Published in Current Trends in Signal Processing · Vol. 3, Issue 3, 2013 · pp. 11–18 Read article
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Breakdown of Physicothermodynamic System of The Human Neural Network in The Fractional Dimensional Space Due To Z+ Bis Intake: Introduction to Photonic & Phononic Nociceptions
Abstract: Nociceptionics deals with the properties, dynamism of nonciceptons, emitted from thequasi-particles of pain perception due to killing or annihilation of living organism in anypart of the globe. The new subject of Nonciceptonics is analogous to the conventionaldiscipline of Digital & Pulse Electronics and Abstract Algebra. In our present work wewill study the characteristics of fractional dimensional space in the human brain as asevere consequence of the nociceptons emitted from the …
Published in Research & Reviews : Journal of Physics · Vol. 2, Issue 1, 2013 · pp. 1–9 Read article
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CNN based Gesture Recognition for ISL
Abstract: AbstractGesture recognition has always been at a peak when it comes to computer vision and human-computer interaction (HCI). Hand gestures can be used for interaction with systems like managing UAVs, medical devices, videogames, etc. In this paper, the main focus is on handicapped people, who are physically unable to speak or listen. With the help of computer interaction, gestures will be recognized. As, the same gesture by another people differs, …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 11–19 Read article
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Develop Institutional Chatbot Using Deep Neural Networks and NLTK
Abstract: Chatbots are intelligent software that can communicate and perform actions like those of a customer service representative. Chatbots are widely used for customer interaction and marketing on social networking and e-commerce sites. AI-based chatbots have the core ability to learn from any question based on initial training on a predefined dataset. A web-based platform provides a broad intelligent foundation for simulating human problem solving. The technology used here is based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 1–7 Read article
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Controlling Media Player Through Hand Gesture Recognition System Using CNN and RNN Models
Abstract: Artificial intelligence markup language (AIML) project represents a pioneering endeavor in the realm of media player control through hand gesture recognition, merging advanced technologies like convolutional neural networks (CNN) and recurrent neural networks (RNN). By harnessing the image analysis capabilities of CNN, our system ensures accurate, real-time detection, and interpretation of intricate hand gestures, enabling users to interact with their media content naturally and seamlessly. What sets our project apart …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 29–34 Read article
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An Artificial Intelligence for Detection of User's Emotion from the Micro Expression of Facial Images Using Co-activated Recurrent Neural Network
Abstract: Human-computer intelligent interaction is a technically emerging field in computer science, which aims at improving the natural ways of interaction between computer and humans. The emphasis of our work relies on bridging the emotional gap between humans and computer i.e., to enable the computers to determine the emotional status of the users involved with through the facial micro-expressions. This work exploits existing methods of facial feature extraction using ABLATA and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 2, Issue 1, 2015 · pp. 1–6 Read article
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Reverse Engineering’s Neural Network Approach to the Human Brain
Abstract: The organic components of the brain are capable of performing consistently and successfully in noisy situations. Brain components with highly adaptive or flexible interactions that could be low-precision, unpredictable, or excessively simultaneous are used to construct biological circuits. Two of the most remarkable characteristics of brain networks are their propensity to self-organize and their pattern organization. Recent research on neural networks, including artificial neural networks and convolutional neural networks (CNN), …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 2, 2022 · pp. 17–24 Read article
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A Study of Hand Gesture Identification with Convolution Neural Network
Abstract: Human-Computer Interaction is the study of how the people interact with machine. Hand gesture technology is active research in computer vision and machine learning. Hand gesture recognition is used enormously in the recent years for Human Computer Interaction (HCI). In this research work, we study about hand gesture identification with machine learning technique. Basically implementation of hand gesture identification has three phases: Preprocessing, Feature extraction, and Classification. This study includes …
Published in Recent Trends in Programming languages · Vol. 8, Issue 1, 2021 · pp. 30–34 Read article
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House Price Prediction: A Review
Abstract: In today’s scenario, real estate industry is growing rapidly. Everyone wants to purchase land and a home, either for personal use or as an investment. House prices keep changing day by day and it is hard for a person to choose the best from all of them. There are many technologies that help to analyse the various aspects of buying property. These digital platforms are created using various algorithms like …
Published in Journal of Open Source Developments · Vol. 9, Issue 3, 2022 · pp. 25–29 Read article
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Signature Based Human Behaviour Prediction
Abstract: Earlier personality or behavior of a person was predicted by spending lot of time with the person. As we know, spending time with person is very difficult task. Concerning this problem, in the present study a method has been proposed for the behavioral prediction of a person through signature analysis. The prediction is done from four features which are alignment, thickness, shape and pen pressure as found in individual’s signature. …
Published in Recent Trends in Programming languages · Vol. 2, Issue 2, 2015 · pp. 13–21 Read article
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A Review on Neural Networks and its Applications
Abstract: Neural Networks have been a hotspot domain for researchers due to its increasing area of applications in areas where huge amounts of data is used and the main goal is to infer patterns out of it. This passage offers an assessment of Neural Networks and their pragmatic uses in real-world situations. It provides information regarding the basic structure of Neural Networks and its working principles. There are also brief introductions …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 60–71 Read article
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EMOTION RECOGNITION FROM ELECTROENCEPHALOGRAM SIGNAL AND EYE MOVEMENT BASED ON DEEP LEARNING
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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Artificial Intelligence in Cerebellum Activation
Abstract: Neuroscience plays a significant function during the progression of artificial intelligence. It provided inspiration for the development of human-like AI. There are two ways that neuroscience encourages us to develop AI systems. Neural networks that replicate human cognition and those that match the structure of the brain are the two objectives. Neural networks, which draw inspiration from the architecture of the human brain, are the engine behind contemporary artificial intelligence …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 14–26 Read article
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Enhancing Image Classification Performance with Deep Neural Networks
Abstract: Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 13–23 Read article
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A Novel Approach of Gait Recognition Using LDA, PAL and Neural Network Technique
Abstract: Gait recognition is one type of biometric technology that can be used to the monitor person without their any cooperation. Controlled atmospheres for example; military installations, banks and even airports required to be able to rapidly detect threats and give differing stages of access to various customer groups. Gait presents a specific way or moving manner on the foot and gait recognition is the recognizing procedure an individual through the …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 3, 2015 · pp. 27–35 Read article
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Applications of Artificial Neural Network in Construction Engineering and Management: An Academic Literature Review and Direction for Future Research
Abstract: One of the artificial intelligence topics is artificial neural network in whichdata processing system is the idea of the human brain.The cause of processing data is many processorsthat treat in parallel form in order to solve the problem.The applications of artificial neural network with neuron model and different network architecture can be used to estimate, predict and modelling of complex problems in construction management. In order to bridge the gap …
Published in Journal of Construction Engineering, Technology & Management · Vol. 6, Issue 1, 2016 · pp. 24–38 Read article
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Facial Expression Recognition Using Convolutional Neural Network
Abstract: The recognition of facial expression is a key step in nonverbal human communication in the field of computer vision. The Facial Expression Recognition (FER) system reflects emotions as well as mental activities, social interaction with people and expressing positive or negative attitude in general. It has many applications like human machine interaction, understanding human behavior and emotions, mental state identification, drowsiness detection for driving safety and health care. One of …
Published in Journal of Open Source Developments · Vol. 6, Issue 1, 2019 · pp. 18–27 Read article
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AI Robotic System in Medical Field
Abstract: Our idea focuses on implementing a robot equipped with a special Artificial Intelligence Program (AIP) for performing surgery in the medical field and various other medical operations. The special AI program is made of deep neural networks, which is trained for thousands of medical prescription and surgical operations procedures. As the AI program is highly trained program the error rate will be almost negligible as compared to the error rates …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 6, Issue 1, 2017 · pp. 20–26 Read article
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Background Suppression for Visual Surveillance Using SOM
Abstract: AbstractBackground suppression is widely used approach for detection of moving objects in video streams which is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient. An approach based on self-organization …
Published in Journal of Communication Engineering & Systems · Vol. 5, Issue 1, 2015 · pp. 15–20 Read article