Search
398 articles for “Neural Network Techniques”
-
Identification of Handwritten Digits using Machine Learning
Abstract: Handwritten Digit Recognition is one of the practical issues in sample recognition applications. The task for handwritten recognition has been difficult due to various variations in written styles. The capacity to create an effective algorithm that can detect handwritten numbers given by users via a scanner, tablet, and other digital devices is at the core of the issue. Artificial intelligence is used in machine learning, which automatically corrects errors based …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 19–26 Read article
-
Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
-
Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
-
Convolutional Neural Network and its Architectures
Abstract: Convolutional neural network (CNN) is a type of artificial neural network (ANN) with multiple layers. From the past decades, it has been considered as a powerful classification technique as it can handle a huge amount of imagery data. It can be applied in the field of image recognition. The name CNN has been derived from the mathematical linear operation known as convolution which is performed between two matrices. CNN has …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 6–14 Read article
-
Automated Detection of Polycystic Ovarian Syndrome using Neural Network Algorithm
Abstract: The ovarian ultrasound imaging could be a good tool in infertility treatment. Monitoring the follicles is extremely important in human reproduction. Periodic measurements of the scale and shape of follicles over several days are the primary means of evaluation by doctors. Today monitoring the follicles is finished by non-automatic means with human interaction. This work could also be very demanding and inaccurate and, in most of the cases, means only …
Published in Recent Trends in Parallel Computing · Vol. 7, Issue 2, 2020 · pp. 9–13 Read article
-
Predicting Eye Blindness by Detecting Exudates in the Retina of Human Eye
Abstract: Diabetic retinopathy is a condition where a person suffering from diabetes starts to loosen his vision slowly as the severity of the disease increases gradually. We can diagnose this condition by the fundus image of the retina of the human eye; although it is very complicated for doctors to predict the conditions just by seeing the fundus images. By detecting diabetic retinopathy at the earliest, we can protect patients from …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 17–23 Read article
-
DeMe-Net Model to Diagnose Skin Cancer Disease from Skin Lesion
Abstract: Skin cancer is a quite common disease in the world and Melanoma is one of the serious types of skin cancer. It begins in melanocyte cells. Skin irritation or tanning due to UV radiation triggers changes in melanocytes, leading to uncontrolled growth of cells. It can potentially develop and spread if it is not treated early. The biopsy is a traditionally used method to diagnose skin cancer in which a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 3, 2021 · pp. 10–20 Read article
-
A Novel Approach to Fingerprint Authentication Using Histogram Oriented Gradients for Feature Extraction and Machine Learning Convolution Neural Network for Classification
Abstract: With applied biometrics, it is possible to identify a person by examining a feature vector of attributes derived from their physical and behaviour characteristics. In biometrics, fingerprints have become one of the most famous and well known techniques of identification and authentication. In light of technological advancements and safety, fingerprint recognition has been successfully used in a variety of Civil, Defence, and Commercial applications for more than a decade. The …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 1–12 Read article
-
Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
-
Automatic Image Description Generation Using Deep Learning Techniques
Abstract: Automatic Image Description Generation methods are extremely useful for image retrieval, search and organization. Previous approaches either use the existing labelled dataset to compose sentences or compose a new description for the test image by exploiting available descriptions of the training images. In practice these methods have limited accuracy, hence if the most important objects in an image cannot be identified, then they cannot generate valid description. Another difficulty lies …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 6, Issue 1, 2019 · pp. 28–37 Read article
-
Review on Evaluation Techniques Such as DOE and ANN Used for Evaluate Heat Flow Parameters for Resistance Spot Welding
Abstract: Resistance spot welding is a widely used process of metal joining in industries. In resistance spot welding process, the time of welding is very little so, during welding process maintenance of high accuracy and precision is very difficult. Resistance spot welding has a wide application in automobile industry, household and domestic appliances manufacturing industry and fabrication industry like air craft manufacturing industry. For better output quality of product, save time …
Published in Trends in Mechanical Engineering & Technology · Vol. 5, Issue 3, 2015 · pp. 26–32 Read article
-
Deep-globe Challenge for Road Extraction Using Convolution Neural Network
Abstract: High-resolution lackey pictures contain a riches of information. They're too intense to decipher. For various operations, it's vital to snappily and straightforwardly distinguish streets from fawning pictures. The thought is to create a bracket demonstration to prize street systems from today’s pictures. The technique of the proposed strategy is grounded on the pre-processing of the disciple information to enhance the picture quality, which in turn comes about in superior comes …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
-
A Comprehensive Review on Brain Tumour Classification through Deep Learning Utilizing Convolutional Neural Networks
Abstract: Abstract- Convolutional neural networks (CNNs) constitute a widely used deep learning approach that has frequently been applied to the problem of brain tumor diagnosis. Such techniques still face some critical challenges in moving towards clinic application. Brain tumours are classified using a biopsy, which is not normally done before conclusive brain surgery. The enhancement of this technology by machine learning could aid radiologists in tumour detection without the use of …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 12, Issue 3, 2023 · pp. 24–29 Read article
-
Content-based Image Retrieval: Recent Trends and Techniques
Abstract: Due to the affordability of digital devices and the accessibility of internet technologies, a vast number of multimedia databases have been established for various applications. These image databases increase the need for efficient picture retrieval search strategies that meet user requirements. When compared to other systems, the content-based image retrieval (CBIR) system is one of the most widely used systems for retrieving images from enormous databases. Much work has been …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 01–32 Read article
-
To Study the VLF Signal for SeismoElectromagnetic Phenomena by Using Wavelet Analysis
Abstract: The research focuses on exploring the potential of Very Low Frequency (VLF) signals as indicators of seismic and geomagnetic activities, particularly in the context of earthquake prediction. It delves into the analysis of VLF data using wavelet-based methodologies and neural networks to detect anomalies preceding seismic events.Observations and analysis of VLF data revealed fluctuations and discrepancies, notably "silent days," occurring several days before seismic events. These irregularities studied through wavelet …
Published in Research & Reviews : Journal of Physics · Vol. 12, Issue 2, 2023 Read article
-
A Comparative Study of ANN and Traditional Control Techniques based Active Shunt Power Filter for 400 Hz Aircraft Electric Power System
Abstract: Sinusoidal current control strategy for extracting reference current for shunt active power filters have been modified using artificial neural network (ANN) and its performances have been compared too. The acute analysis of comparison of the compensation capability is based upon THD, speedwell and recommendations will be given for the choice of technique to be used. The simulated results using MATLAB model are shown in this paper, and they will undoubtedly …
Published in Trends in Electrical Engineering · Vol. 6, Issue 1, 2016 · pp. 42–49 Read article
-
Comprehensive Study of Least Squares Estimation in Fast Fading MIMO-OFDM Systems
Abstract: MIMO-OFDM technology is now the foundation for modern wireless communication systems, allowing dramatic improvements in spectral efficiency, power efficiency, and transmission rate. On the other hand, the least accurate channel estimation is still a critical task, especially when they are in fast-fading environments. This study gives a comprehensive survey of LSE-based approaches and their applications on different fast-fading channel models for MIMO-OFDM systems. Techniques like Pilot Assisted Channel Estimation (PACE), …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 13–21 Read article
-
Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article
-
AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
-
Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article