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238 articles for “Machine learning”
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A Study of Application of No Regret Learning Algorithm for Development of a Career Counselling Software
Abstract: This paper explores the application of “no regret learning algorithms” in the development of a career counselling software, aimed at providing individuals with personalized and data-driven career guidance. By harnessing the power of machine learning methods, this groundbreaking approach provides a flexible and responsive system designed to aid users in making well-informed choices regarding their career trajectories. The software incorporates user profiling, reward modelling, continuous feedback mechanisms, and ethical considerations …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 2, 2023 · pp. 37–43 Read article
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Enhancing Facial Expression Analysis Using CNNs: Insights from ML and Deep Learning Comparisons
Abstract: Emotion recognition from facial manifestations increases the interaction between humans and computers by enabling the interaction between humans and computers to effectively explain human feelings. This study presents a comparative analysis of three approaches to the emotional recognition of faces: a custom Convolutional Neural Network (CNN) model, Traditional Machine Learning (ML) methods, and other deep learning architectures such as VGG, ResNet, and Hybrid CNN–RNN models. The proposed CNN-based system, developed …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 23–31 Read article
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A Realtime Coronavirus Notifier
Abstract: Fresh corona virus deadly disease has not clinically confirmed vaccine or medicines. Its tolerant are improving through the help of antibiotic drug, anti-viral treatments, over and above vitamin C supplementation. It is currently apparent that the world necessities an expedient and speedier answer for contain and tackle the further spread of COVID-19 across the world with the guide of non-clinical advance for instance data mining schemes, improved aptitude furthermore extra …
Published in International Journal of Distributed Computing and Technology · Vol. 7, Issue 1, 2021 · pp. 22–25 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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Leveraging Artificial Intelligence for Traffic Flow Optimization: A Case Study Approach
Abstract: AbstractTraffic congestion poses a significant challenge in urban environments, contributing to economiclosses, increased fuel consumption, environmental pollution, and diminished quality of life. Traditionaltraffic management approaches, such as pre-timed traffic signals and manual interventions, often failto adapt dynamically to fluctuating traffic conditions. This study explores the integration of artificialintelligence (AI) in traffic management to optimize traffic flow and reduce congestion. By leveragingAI-driven predictive models, deep reinforcement learning, and real-time traffic data, …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 11, Issue 1, 2025 · pp. 37–42 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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Analyzing Applications and Risks of IoT in Education: A Comprehensive Approach
Abstract: By promoting student involvement, increasing administrative effectiveness, and developing intelligent learning environments, the Internet of Things (IoT) is revolutionizing the education industry. Smart classrooms, interactive whiteboards, and real-time attendance systems are just a few examples of IoT-powered gadgets that are enhancing accessibility and customization in education. The potential impact that IOT can have on various industries is huge, including the education industry. IoT (internet of things) can be said as …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 20–28 Read article
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Gourmet Sage Using Deep Learning With Calories Chart
Abstract: Gourmet Sage via Deep Learning with Calories Chart is an innovative system that merges advanced deep learning technology with nutrition science to help users make healthier dietary choices. By leveraging YOLOv8, a cutting-edge object detection model, the system allows real-time identification of food items, estimating their calorie content and ingredient composition with remarkable accuracy. It goes beyond detection by providing a comprehensive nutritional breakdown, including macronutrients (proteins, fats, carbs) and …
Published in International Journal of Image Processing and Pattern Recognition Read article
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Advances in Gender Classification from Facial Images Using CNNs: A Comprehensive Review
Abstract: Predicting age and gender from facial images is important for various uses, like social interactions, security, and customizing user experiences. Despite progress in facial recognition technology, getting accurate and reliable predictions is still a challenge. This paper reviews recent advancements in Convolutional Neural Networks (CNNs) for age and gender classification, comparing their effectiveness to traditional methods. CNNs excel in extracting features from images and have shown notable improvements in accuracy …
Published in International Journal of Digital Communication and Analog Signals · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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Deep Learning Techniques for Optimizing Resource Allocation and Sustainability in the Next Generation of 6G Wireless Networks
Abstract: The upcoming sixth generation (6G) of wireless communication networks aims to meet challenging requirements such as ultra-reliable low-latency services, massive connectivity for billions of smart devices, and intelligent automation across highly diverse environments. Along with these goals, the issues of energy efficiency and environmental sustainability are becoming equally important, as the rising number of users and traffic volumes will directly increase power demand and carbon emissions. To lower total energy …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 Read article
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Sign Language Alphabet Detection System
Abstract: Currently, gesture recognition for hands and sign language detection for human-computer interaction isthe main emphasis of computer vision and machine learning. The creation of systems that can identifygestures and use them to transmit data or control devices is one of the main goals. Specifically, handgestures entail dynamic hand movements that require explanations in both the spatial and temporaldomains, whereas hand postures reflect the static structure of the hand. The goal …
Published in International Journal of Analog Integrated Circuits · Vol. 9, Issue 2, 2023 · pp. 29–35 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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Convolutional Neural Network Algorithm for Stress Field Approximation for a Uniaxially Loaded Plate with Holes
Abstract: ABSTRACTKnowing the high stress concentration and its location around a hole is of practical importance in designing engineering structures, effective parameters can be selected in order to achieve minimum stress concentration around the hole(s). The visualisation of the stress distribution is done experimentally or numerically using finite element analysis (FEA). This study involved the approximation of the von Mises stress field distribution around regular holes in finite metallic plates, based …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 1–12 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Automated Vehicle classification and counting for Smart City Traffic management using AI/ML and DL
Abstract: Traffic jams and safety on the road have become a serious problem in modern cities. They need smart and versatile solutions. This project is a proposal to use automated vehicles to count and classify real- time vehicles. The system will enhance the traffic monitoring and management in smart cities. It can identify and differentiate the various kinds of vehicles: cars, trucks, buses, and motorcycles by utilizing machine learning on real-time …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 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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Remote Sensing Technologies for Weather Forecasting: Techniques, Uses, andAssessment
Abstract: Remote sensing has become an important tool for modern weather forecasting since it lets us see the Earth's atmosphere and surface all the time and on a huge scale. Remote sensing uses satellites and sensors to collect data in real time on important weather variables like temperature, humidity, cloud cover, precipitation patterns, and atmospheric motion. These numbers are used in numerical weather prediction models to make forecasts more accurate and …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 1, 2026 · pp. 25–34 Read article
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Recent Advances in the Development and Performance Optimization of Advanced Metallic Alloys
Abstract: The continuous demand for high-performance materials in aerospace, automotive, energy, and biomedical industries has accelerated research and development in advanced metallic alloys. Metallurgy and alloy design play a crucial role in achieving superior mechanical, thermal, and chemical properties while maintaining cost efficiency and sustainability. This study presents a comprehensive overview of recent advances in metallic alloy development, focusing on novel alloying strategies, microstructural control, and performance optimization techniques. Emphasis is …
Published in International Journal of Metallurgy and Alloys · Vol. 12, Issue 1, 2026 · pp. 1–6 Read article
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Phase-Change Material Integrated Semiconductor Circuits for In-Memory Analog Computing Applications
Abstract: The continuous demand for high-speed, energy-efficient computing has intensified the exploration of in- memory analog computing (IMAC) architectures, which aim to minimize the latency and power overhead associated with conventional von Neumann architectures. This research investigates the integration of phase- change materials (PCMs) with semiconductor circuits to realize programmable, non-volatile in-memory analog computing platforms. PCMs exhibit reversible resistance switching between amorphous and crystalline states, enabling precise analog weight storage directly …
Published in International Journal of Analog Integrated Circuits · Vol. 12, Issue 1, 2026 · pp. 32–42 Read article