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276 articles for “Accuracy”
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Classification and Detection of Cabbage Leaf Diseases from Images Using Deep Learning Methods
Abstract: The presented work uses Deep learning methods to detect diseases in cabbage leaves. To avoid a reduction in agricultural product yield, disease diagnosis in plants is crucial. Manual plant disease monitoring is challenging and time-consuming at every stage. Five major types of diseases are considered. Initially, the input images are classified as healthy and diseased. Further, the diseased images are classified into five different varieties. Early and precise biotic stress …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 8, Issue 2, 2022 · pp. 23–32 Read article
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Sound-based Bird Classification Using Perceptual Features and Machine Learning: A Gaussian Mixture Model
Abstract: Classification of birds based on their sound patterns and identification of bird species found in the chirping sounds of birds were experimented with using the feature extraction method. This work is beneficial in ornithology to study birds and their behavior based on their sounds. The proposed methods can automatically classify birds by different sound processing. The audio file of a bird’s sound recording is first cut into smaller samples, and …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 2, 2023 · pp. 46–52 Read article
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Vehicle Number Plate Detection and Recognition System in Nigeria Using Deep Learning
Abstract: With over 200 million citizens, Nigeria is one of Africa’s largest and most populous nations. It is now essential to automate traffic management due to the rising number of vehicles in the nation. With the use of a deep learning technique known as the YOLO method, the study was able to construct an automatic vehicle license plate identification system that will recognize each of the vehicle license plates when many …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 2, 2023 · pp. 32–45 Read article
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For Analyzing Fraud in Credit Cards, Fuzzy Particle Swarm Optimization (FPSO) with Enhanced Support Vector Machine (ESVM) Classifier
Abstract: Credit cards are extremely significant in today’s economy. However, as the number of Credit Card clients grew, so did the number of Credit Card fraud instances. To fight the upward thrust in credit score card fraud, a number of techniques were recommended. In previous study, a unique fraud detection system was presented that uses similar cardholders’ behavioural patterns to construct a recent behavioural profile of a cardholder in order to …
Published in International Journal of Software Computing and Testing · Vol. 7, Issue 2, 2021 · pp. 1–12 Read article
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Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains
Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article
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Comparative Analysis of deep learning based object detection model’s for their application in autonomous vehicles
Abstract: In this work, we compare the detection accuracy and speed of several state of the art models for the task of detecting red and green traffic lights. We compare detection performance and speed of YOLOv4, ScaledYOLOv4 and YOLOR. All of these are single stage object detection models. Two stage models have good detection accuracy but are slower than single stage detectors, single stage detectors are faster and also have good …
Published in International Journal of Analog Integrated Circuits · Vol. 8, Issue 1, 2022 · pp. 1–8 Read article
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COVID-19 Detection Using Decision Tree Support Vector Machine Random Forest.
Abstract: The rapidly spreading novel coronavirus (SARS-CoV-2) presents a substantial global health risk, necessitating swift detection through efficient diagnostic methods. Reports highlight lung-related issues in many COVID-19 patients, and both chest CT scans and X-rays are effective in identification. Chest X-ray (CXR) imaging, due to its convenience, faster imaging, simplicity, and lower cost, stands out. In our study, we applied Decision Tree, Random Forest, and Support Vector Machine to identify COVID-19 …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 2, 2023 · pp. 7–21 Read article
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Autonomous Multi-Agent Sensor Network for Distributed Environmental Instrumentation
Abstract: Environmental monitoring requires intelligent, scalable, and autonomous instrumentation systems capable of continuously sensing, processing, and communicating heterogeneous data under dynamic conditions. This study proposes an Autonomous Multi-Agent Sensor Network for Distributed Environmental Instrumentation, integrating distributed sensor nodes, edge computing, multi-agent collaboration, adaptive data fusion, and intelligent decision-making to achieve reliable real-time monitoring of environmental parameters. Each sensor agent autonomously performs local sensing, anomaly detection, energy-aware communication, and cooperative information exchange …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Classification of power quality disturbances using advanced deep learning algorithms for Accurate and efficient electrical signal analysis
Abstract: Power systems today have to deal with more and more power quality issues (PQDs) like voltage drops, rises, harmonics, and transients because more people are using renewable energy sources and electronic devices. These problems can hurt equipment, stop services, and lower the overall reliability of power. In real-time settings, traditional detection methods often don't work as quickly or accurately as they should. This paper looks at how deep learning models, …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 2, 2026 Read article
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Speech Emotion Recognition using Multi- Kernel CNN for Features extraction and Random Forest Classifier
Abstract: Identifying human emotional states from speech signals is the main goal of Speech Emotion Recognition (SER), which has grown to be a significant area of study in affective computing. However, class imbalance and efficient feature extraction from speech data pose problems for many of the current methods. This study suggests a hybrid framework that combines a Random Forest (RF) classifier with a multi-kernel Convolutional Neural Network (CNN) to address these …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article
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AI-Based Image Detection of Rice Crop Diseases Using Deep Learning and Grad-CAM
Abstract: The Indian economy relies heavily on agriculture, and rice is one of the most significant staple crops grown in the country. Nevertheless, rice cultivation faces numerous challenges due to several leaf diseases, such as bacterial leaf blight, brown spot, and leaf smut. These diseases can lead to substantial yield losses and financial burdens for farmers. Therefore, the early detection and classification of these diseases are essential to minimize crop damage …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 2, 2026 Read article
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Predicting Traffic Congestion in Mumbai Using Artificial Intelligence
Abstract: Abstract — Mumbai's ongoing traffic problems are brought on by the city's fast urbanization, population expansion, and growing reliance on private automobiles. The majority of traffic management technologies in use today are reactive, frequently reacting only after congestion has already arisen. Using information from a variety of sources, such as commuter surveys, weather reports, and traffic incident logs, this study explores the application of artificial intelligence (AI) and machine learning …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 2, 2026 Read article
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The Role of Artificial Intelligence in Mental Health: New Approaches for Diagnosis and Treatment
Abstract: Artificial intelligence (AI) is increasingly reshaping mental health care by supporting early identification of mental health conditions, improving diagnostic accuracy, and enabling personalized intervention strategies for disorders such as depression, anxiety, and post-traumatic stress disorder. Advanced AI technologies, including machine learning algorithms and natural language processing techniques, allow analysis of large-scale behavioral, textual, and speech-based data to identify patterns related to emotional and cognitive health. These tools help clinicians make …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 · pp. 22–26 Read article
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AI-Based Deepfake Voice Detection Model for Hindi Language
Abstract: Most current research on deepfake voice detection focuses heavily on English or Mandarin, creating a significant security gap for Hindi speakers. To address this, we developed a detection framework specifically tailored for the Hindi language using a lightweight approach: Mel-Frequency Cepstral Coefficient (MFCC) feature extraction paired with an XGBoost classifier. We trained the system on a large dataset comprising over 99,000 real voice samples and roughly 3,800 synthetic samples, each …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 2, 2026 Read article
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Advanced Classification of Diabetic Retinopathy Using GAN and Deep Residual CNN Model
Abstract: Diabetic retinopathy (DR) is a leading cause of blindness worldwide, impacting the largest number of individuals who have diabetes. Early identification of diabetic retinopathy may help to prevent severe effects; however, the very limited availability of labeled datasets, and the possibility of overfitting of the model, presents obstacles to obtaining an accurate diagnosis. In this research, a hybrid deep learning strategy is introduced, where Generative Adversarial Networks (GANs) are used …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 8–16 Read article
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Toward Sustainable Intelligence: A Framework for Green AI Adoption
Abstract: The rapid expansion of Artificial Intelligence has shattered the illusion of the cloud as an ethereal entity, revealing a massive physical infrastructure with a staggering environmental price tag. The traditional Red AI paradigm – where success is measured solely by accuracy through brute-force scaling – has created an unsustainable trajectory. Training a single large-scale model like GPT-3 requires 1,287 MWh of electricity, while the necessary cooling systems evaporate millions of …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 17–23 Read article
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Design, Development, and Testing of 2-Phase Separator
Abstract: As the pressure vessel operates under high internal pressure, the choice of material and accuracy indesign play a vital role in ensuring its safety and reliability. Proper design is essential because anyfailure in a pressure vessel can lead to serious hazards, financial losses, and operational shutdowns.In compliance with the ASME Code (Section VIII, Division 1) and the process data sheet, this articledescribes how to design a pressure vessel. To guarantee …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 12, Issue 1, 2026 · pp. 29–37 Read article
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The Role of Artificial Intelligence in Mental Health: New Approaches for Diagnosis and Treatment
Abstract: Artificial intelligence (AI) is increasingly reshaping mental health care by supporting early identification of mental health conditions, improving diagnostic accuracy, and enabling personalized intervention strategies for disorders such as depression, anxiety, and post-traumatic stress disorder. Advanced AI technologies, including machine learning algorithms and natural language processing techniques, allow analysis of large-scale behavioral, textual, and speech-based data to identify patterns related to emotional and cognitive health. These tools help clinicians make …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 · pp. 12–17 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article