Search
628 articles for “neural”
-
Traffic Sign Detection and Recognition Using Deep learning based- Convolutional Neural Network Algorithm
Abstract: The concept of Deep Convolutional Neural Organizations (CNNs) is a quickly arising new zone for Automatic traffic sign detection and recognition among the few master frameworks, such as independent driving and driver assistance. Here, in this paper, for traffic sign detection, we have utilized another methodology that uses a newly developed identification calculation and an RGB-based tone thresholding procedure. Results of the proposed identification and acknowledgement approaches are assessed on …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 1, 2021 · pp. 24–29 Read article
-
Prediction of Excitation Current of Synchronous Machines Based on Neural Network Model
Abstract: There are several difficulties found to estimate the excitation current & and optimum input parameters of synchronous motors. Heuristic methods are frequently used to weightt the problem's parameters or optimum coefficients. As a result, a neural network model is modified in this study to explore the best parameters and estimate the excitation current of a synchronous motor with minimal prediction errors for both the testing dataset and cross validation. Excitation …
Published in Recent Trends in Electronics Communication Systems · Vol. 10, Issue 1, 2023 · pp. 28–33 Read article
-
Predictive Modeling System for Automated Skin Lesion Classification Using Deep Neural Networks and Voting Ensembles
Abstract: Skin cancer is one of the most prevalent cancers globally. Early and accurate diagnosis is critical for timely treatment and improved prognosis. This study presents a predictive modeling system for automated classification of skin lesions from dermoscopic images using deep neural networks and voting ensemble techniques. A customized 16-layer convolutional neural network architecture is developed for feature learning from lesion images. The concept of horizontal voting ensemble is implemented by …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 29–35 Read article
-
Real-world Pothole Detection Using Image Processing and Deep Learning Convolutional Neural Network Model
Abstract: Potholes are a major problem of concern in many parts of the cities across the country. Road accidents are one of the causes that significantly affect humanity and result in damage to vehicles and road surface. Potholes are dangerous for pedestrians who walk along the road and vehicular traffic on busy roads. Road accidents are caused due to improper maintenance of roads, and it is imperative to attend to such …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 95–103 Read article
-
Trigeminal Neuralgia: Revisiting Clinical Characteristics in the Indian Scenario
Abstract: The diagnosis of trigeminal neuralgia has been a source of confusion for the clinicians since long and still remains a difficult condition to manage with no treatment modality providing a satisfactory management of the patient. The aim of this study was to assess the sex, age, branch and side distribution in patients with trigeminal neuralgia. For each of the subjects, a detailed, structured case history was recorded and the findings …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 1, Issue 2, 2012 · pp. 9–17 Read article
-
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
-
Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
-
Neuromorphic Spiking Neural Networks and Event-Driven Hardware: Architectures, Learning Paradigms, and Experimental Realizations
Abstract: With the current computational boom the research community is seeking for more sustainable energy efficient i.e. biologically inspired models of conventional Artificial Neural Networks (ANNs). Spiking Neural Networks (SNNs) known as the third generation of neural network models, provide a revolutionary approach by mimicking the asynchronized event-driven and temporally accurate signaling of the mammalian brain. Whereas conventional deep learning models operate with real-valued activations and dense matrix multiplications, SNNs use …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 39–46 Read article
-
Simulation of Neural Network based PID Controller for Pressure Process
Abstract: This paper provides a Neural Network PID controller based on Back Propagation (BP) algorithm applied to pressure control in a tank. The controller has many advantages like that more convenient in parameter regulating, better robust. Neural network is to adjust the parameters of PID controller based on the operational status of the system, to achieve a better performance, making the output of the output neurons corresponding to the three adjustable …
Published in Journal of Control & Instrumentation · Vol. 4, Issue 1, 2013 · pp. 23–27 Read article
-
Artificial Neural Network Based Defect Prediction in Casting
Abstract: The main problems which are facing by most of the casting industries is loss of productivity which is due to casting defects occurred during the production time. The main casting defects are cracks, misruns, blowholes scabs and airlocks. Most of the investigations made in this area is only discussing the defects occurred after a cast is made and no method has yet been developed to prevent the defects before casting. …
Published in Journal of Mechatronics and Automation · Vol. 2, Issue 2, 2015 · pp. 33–38 Read article
-
Convolution Neural Network Model for Intrusion Detection in Network
Abstract: The evolution of the internet has made protecting information a necessity. Network intrusion and prevention plays an integral role in network-based security. The Intrusion technologies primarily used in today’s world deploy various machine learning algorithms and train models based on them resulting in effectively low detection rates. A technical advancement from machine learning, Deep Learning employs complex mechanisms to extract features from samples. As observed that conventional intrusion detection systems …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 1, 2021 · pp. 7–13 Read article
-
Power Estimation for VLSI Circuits Using Neural Networks
Abstract: Neural network based VLSI power estimation is done which estimates power in VLSI circuits from its input/output and gate information, without simulation and analysis of its detail structure and the interconnections.Artificial neural network is created which helps in estimation of power. Power estimation results from the [2] [3]are used as the training vector for the network .The network is trained using Back-propagation algorithm. Asimple recurrent network is also introduced called …
Published in Journal of VLSI Design Tools and Technology · Vol. 1, Issue 1-2-3, 2011 · pp. 45–56 Read article
-
The Formulation of Neural Network Model
Abstract: Mathematically, a neural network model is presented in this paper. This formulation is efficient and secure to apply to design any network model for information, data analysis, decision, prediction etc. The compact formula is defined over the set of polynomials. The finiteness & discreteness allows this formation efficient and feasibility &isomorphism provides the security. These advantages are carried this formulation. Probability is also applied to transform the result for analyzing …
Published in Recent Trends in Electronics Communication Systems · Vol. 6, Issue 2, 2019 · pp. 26–32 Read article
-
Study and Prediction of Radiation Effects in Solar Power Plants using Neuro Fuzzy and Neural Network
Abstract: Neural and neuro-fuzzy frameworks are utilized, to figure temperature and sun powered radiation. The principle benefit of these frameworks is that they don't need any earlier information on the qualities of the information time-series to foresee their future qualities. These frameworks with various models have been prepared utilizing as information estimations of the above meteorological boundaries acquired from the National Observatory of Athens. In the wake of having reproduced a …
Published in Trends in Electrical Engineering · Vol. 12, Issue 1, 2022 · pp. 8–19 Read article
-
Handwritten English Alphabet Recognition Using Convolutional Neural Network
Abstract: This research paper presents an approach for English alphabet recognition using machine learning. The proposed system utilizes a convolutional neural network (CNN) to identify individual characters within an input image. The dataset used in this research consists of a large collection of handwritten alphabet images, sourced from Kaggle's A-Z Handwritten Alphabets dataset in CSV (comma-separated values) format, which were preprocessed and augmented to improve the model's accuracy. We trained and …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 17–25 Read article
-
Convolutional Neural Network and Transfer Learning-based Approach for Brain Tumor Detection in Magnetic Resonance Imaging
Abstract: Brain tumors are among the most invasive illnesses that can affect both children and adults. Brain tumors develop very quickly, and if not treated at the proper time, they decrease the patient's chances of survival. It is crucial to find brain tumors at an early stage. To increase patients’ life expectancy, proper treatment planning and precise diagnostics are most important. The best way to detect brain tumors is via Magnetic …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 13, Issue 2, 2023 · pp. 23–30 Read article
-
Exploring Practical Applications of Artificial Neural Networks: A Review
Abstract: Computational models called artificial neural networks (ANNs) are modeled after the structure of the human brain. These models are designed to process information and learn from data. Artificial neural networks, or ANNs, are composed of interconnected artificial neurons layered to resemble the brain's neural network.. Through training, ANNs adjust the connections between neurons based on labeled data, enabling them to recognize patterns and perform specific tasks. Despite their efficacy in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
-
Enhancing Power Conversion Efficiency in Tandem Solar Cells with Temporal Dynamic Graph Neural Network
Abstract: In modern homes, people want good comfort and also less electricity bill, so managing heating load and cooling load become very important. Heating Load (HL) and Cooling Load (CL) depend on many things like wall material, window size, sunlight, ventilation, and weather. Because of this many factors, calculation and optimization of HL and CL is little difficult and many time normal formulas give wrong or not perfect results. So in …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 · pp. 12–19 Read article
-
Thermal Performance of Flat Tube Louver Fin Heat Exchanger using Artificial Neural Network
Abstract: In this paper, an application of artificial neural networks (ANNs) is presented to predict the outlet temperatures on both fluid side of flat tube louver fin type heat exchanger used in flat tube louver fin heat exchanger. A validated numerical code is developed using MATLAB to generate huge data sets which gives outlet temperature of both the fluids. Three-layer feed-forward back propagation neural network is developed to model the thermal …
Published in Journal of Thermal Engineering and Applications · Vol. 4, Issue 3, 2017 · pp. 6–12 Read article
-
Design and Analysis of FIR Filter using Neural Network
Abstract: This paper is intended to provide an alternative approach for comparison of FIR digital filter by using neural network. This proposed approach establishes relation between (I) order and main width lobe of filter and (II) order and cutoff frequency of filter. In this paper is used FDA tool to design digital FIR filters of different orders and neural network tool box to compare different filters. As the simulation results show, …
Published in Current Trends in Signal Processing · Vol. 3, Issue 2, 2013 · pp. 9–14 Read article