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334 articles for “feature based techniques”
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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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Software and Hardware Implementation of Quasi z Source Inverter in DC-DC Converter with DC Motor as Load
Abstract: DC/DC power converters are employed in applications like telecom, industrial, automotive, military, aerospace and motor drives. The dc/dc converter market is forecast to grow at a strong rate to $ 4.3 billion by 2016. The primary factor limiting the widespread application of low voltage producing renewable energy sources to motor load is interfacing of converter system. The traditional voltage source inverter (VSI) cannot be dealt without overrating of inverter because …
Published in Journal of Power Electronics and Power Systems · Vol. 5, Issue 3, 2015 · pp. 97–107 Read article
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Dimensionality Reduction using Eigenfaces and Fisherfaces for Face Recognition Applications using Kernel LMS Algorithm
Abstract: AbstractFace recognition is an intricate numerical technology in computer systems that can support recognition of human faces using methods such as principal component analysis (PCA), linear discriminant analysis (LDA), etc. by comparing the given facial uniqueness with the already available face database. PCA and LDA are classical feature extraction and data representation techniques used in face recognition algorithm involving unsupervised statistical methods. The 2-D facial image can be transformed into …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 29–55 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Voting Classification Method for Network Traffic Prediction
Abstract: Prediction analysis (PA) is a data mining-based technique. The futuristic outcomes based on present data can be predicted using this technique. As the dataset is large and complex, network traffic classification is a big concern in prediction analysis. Three phases are included in network traffic strategies. The data collection is obtained in the first step of pre-processing, and it is analysed to delete incomplete and obsolete values. The relationship between …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 1, 2021 · pp. 23–30 Read article
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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
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Application of Grey Wolf Optimizer (GWO) strategy for Malware Analysis
Abstract: The ever-evolving landscape of cybersecurity necessitates continuous advancements in malware analysis techniques. This study explores the deployment of the Grey Wolf Optimizer (GWO) algorithm as a novel bio-inspired optimization mechanism to address the challenges posed by modern malware threats. The primary objective is to enhance various facets of malware analysis, including feature selection, parameter optimization, and the overall efficacy of malware detection models. The study begins by introducing the GWO …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 43–53 Read article
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Polymer Composite Phase Change Materials: Materials Design, Processing, Characterization, and Structure–Property Relationships—A Comprehensive Review
Abstract: Polymer composite phase change materials (PCPCMs) have been recognized as an innovative category of multifunctional polymeric materials, which could be tuned by appropriate materials design, composite formation, and interface modification. With the incorporation of phase change materials in polymer matrix systems and functional fillers, PCPCMs show improved mechanical properties, physicochemical stability, and functionality in contrast to traditional phase change materials. With recent advances in polymer science, nanocomposites, and processing techniques, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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An Intelligent Neural Networks Approach for Monitoring of Soilless Urban Farms
Abstract: Urban agriculture is increasingly recognized as a sustainable approach to addressing food security challenges in rapidly growing and densely populated cities. Conventional soil-based farming often faces limitations such as space scarcity, excessive water consumption, and environmental degradation. To overcome these challenges, soilless farming techniques such as hydroponics and aeroponics have gained significant attention due to their efficient utilization of space, reduced water requirements, and potential for year-round crop production. However, …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 31–37 Read article
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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 Read article
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AI Driven IoT based Satellite remote sensing system: KSK Approach in Satellite Remote Sensing
Abstract: The convergence of the Internet of Things (IoT) and satellite remote sensing has traditionally been bottlenecked by massive data latency and limited downlink bandwidth. This paper proposes a decentralized framework for an "AI-Driven IoT-based Satellite Remote Sensing System," which shifts the paradigm from raw data transmission to onboard edge-intelligence. By integrating lightweight convolutional neural networks (CNNs) directly into satellite payloads, the system performs real-time feature extraction and anomaly detection before …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 50–57 Read article
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Scalability Analysis of Semantic Relational Key Terms based Document Clustering Using Parsing Text Calcification
Abstract: Abstract: Document agglomeration, one among the standard info mining ways, is an unsupervised learning worldview wherever agglomeration techniques endeavor to tell apart-inborn groupings of the text documents, with the goal that a meeting of clusters is made during which clusters show high intra-cluster closeness and low bury cluster likeness. The importance of document agglomeration rises out of the big volumes of matter documents created. Albeit varied document agglomeration techniques are …
Published in Recent Trends in Programming languages · Vol. 6, Issue 3, 2019 · pp. 33–40 Read article
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Analysis of Various Diabetes Prediction Techniques Based on Machine Learning
Abstract: AbstractData mining is a method of mine from the underdone data for maintains useful information. In organize to obtain fundamental knowledge it is important to remove bulky quantity of data. This method is consist of many important components like data cleaning, data selection, data integrity, pattern evaluation with data mining engine and database with graphical user interface. Diabetes is a chronic disease that is also known as Non‐Insulin Dependent Diabetes …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 1, 2021 · pp. 17–22 Read article
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Performance Comparison between Back-Propagation Learning and Kohonen Self-Organizing Neural Networks Algorithm in Terms of Pattern Recognition
Abstract: Pattern recognition using back-propagation learning and Kohonen self-organizing neural network algorithms has been developed and measured various performance based on different criteria and environment of the pattern. These pattern recognition systems have taken the object image as input. In image pre-processing stage, scaling and clipping process has been applied from the background image to avoid unnecessary portion of the object image. Feature extraction has been performed after applying filtering and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 1–8 Read article
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Fabrication of Adaptive Headlamp System
Abstract: According to National Highway Transportation Safety Administration (NHTSA), the percentage of deaths of the pedestrian is high between the hours of 6 pm. to 9 pm. Due to insufficient light conditions. Looking at the current condition it is of great importance to use available techniques to contribute to road safety by increasing the visual image provided by currently used vehicle headlights. The feature of these headlamps is that they turn …
Published in Journal of Production Research & Management · Vol. 11, Issue 2, 2021 · pp. 34–42 Read article
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Solar Energy Harvesting for Wireless Sensor Network Nodes
Abstract: A Wireless Sensor Network (WSN) consists of numerous sensor nodes that senses, processes and transmits sensor data from periphery of the network to BaseStation (BS) located at central location. A number of router nodes are deployed to transmit the sensed data to the BS. Generally, WSN nodes are battery powered. The lifetime of nodes is decided by the lifetime of the battery. To increase the lifetime of the batteries Energy …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 13, Issue 3, 2022 · pp. 36–46 Read article