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16 articles for “pattern recognition”
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Advancing Early Detection of Menkes Disease Through Image Analysis and Biosensor Integration
Abstract: Menkes disease, a rare X-linked recessive disorder of copper metabolism, poses significant challenges in early diagnosis due to its nonspecific initial symptoms. This paper presents a comprehensive approach to enhance the early detection of Menkes disease by leveraging image processing techniques, pattern recognition algorithms, and innovative biosensor technologies. A novel framework is proposed that combines analysis of hair microscopy images, facial feature recognition, and copper-sensitive biosensors to create a multi-modal …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 24–34 Read article
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AI in e-Skin: A Study
Abstract: For years, the concept of electronic skin, or e-skin, has captivated imaginations. Imagine a material that could mimic the sensitivity, flexibility, and even the healing properties of human skin. This isn’t just science fiction anymore. E-skin, a network of flexible sensors and electronic components, is rapidly becoming a reality. And now, thanks to the power of artificial intelligence (AI), this technology is poised to revolutionize various aspects of our lives, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 8–16 Read article
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Deep Learning with CNNs: A Survey of Techniques and Real-World Applications
Abstract: Convolutional Neural Networks (CNNs) have emerged one of the most powerfully used tools in deep learning, particularly in image and pattern recognition tasks. CNNs are being revolutionized through deep learning resulting in a dominant architecture in computer vision as well as other various domains. This paper provides a comprehensive survey of CNN-based deep learning, its methodologies, regularizations, and computational efficiencies. We also address the challenges and future directions of CNN. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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Evaluation of Deep Learning Optimizers for Gujarati Handwritten Numerals
Abstract: Handwritten digit recognition is a fundamental task in the field of pattern recognition and computer vision with numerous applications. The development of deep learning algorithms has greatly increased the efficiency and accuracy of recognition of handwritten digits systems. However, the choice of optimizer plays a crucial role in determining the convergence rate and final performance of deep learning models. In this study, we provide a thorough analysis of many deep …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 34–41 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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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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Predictive Maintenance of 6G Infrastructure Using Artificial Intelligence
Abstract: The transition to Sixth Generation (6G) wireless infrastructure introduces unprecedented complexity, characterized by massive densification, reliance on the Terahertz (THz) spectrum, dynamic cell topologies driven by Reconfigurable Intelligent Surfaces (RIS), and stringent requirements for Ultra-Reliable Low-Latency Communication (URLLC). Traditional reactive or fixed-schedule maintenance protocols are fundamentally inadequate for sustaining the necessary service continuity and energy efficiency in this hyper-connected, heterogeneous environment. This paper explores the critical role of Artificial Intelligence …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 2, 2025 Read article
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Forecasting Trends in the Stock Market by Using Deep Learning Approaches
Abstract: Accurately predicting stock market trends remains a significant challenge in the field of finance. Deep learning, a subset of machine learning, has emerged as a powerful tool for capturing complex relationships within data. What sets deep learning apart is its ability to handle vast amounts of data, recognize intricate features, and adapt to evolving patterns, all while uncovering hidden insights. At its core, deep learning uses artificial neural networks that …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 2, 2024 · pp. 22–30 Read article
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Artificial Intelligence Applications for Sustainable IoT Systems: A Systematic Review and Future Directions in Environmental Sustainability
Abstract: This paper will be a systematic review of the Integration of Artificial Intelligence and the Internet of Things (IoT) in sustainable systems, towards the prospects for them Addressing environmental challenges. The review focuses on AI examples here include recognition AI, explainable AI, among others. The patterns are important for safety, security, and efficiency in Urban landscapes. It describes the functions of with this program, interoperability and openness are achieved. FIWARE …
Published in International Journal of Environmental Chemistry · Vol. 12, Issue 1, 2026 · pp. 27–35 Read article
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Vani-Adapt: A Zero-Shot Accent Trans-Adaptation Framework for Robust Indic Speech Recognition
Abstract: In countries like India with multilingual and accent-rich dialects, speech-based human–computer interaction is important to expand digital services for better accessibility. Even with recent advancements in Automatic Speech Recognition (ASR), existing systems are still very reactive to regional accents and non-standard speech patterns which is not suitable for seamless experience. Traditional perspectives rely on accent-specific fine-tuning, which is unrealistic for real-world deployment and requires a lot of labeled data, which …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 17–22 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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An Overview on Harmonic Intelligence: BridgingMicrowave Sensing and AI-Driven IoT for Autonomous Decision-Making
Abstract: As the Internet of Things (IoT) ecosystem expands into complex industrial and urban environments, the demand for high-fidelity data acquisition and near-instantaneous edge processing has reached a critical juncture. Traditional optical and infrared sensors often falter under adverse conditions, such as dense smoke, occlusions, or low-light environments. This paper explores the transformative potential of microwave signals—leveraging their unique ability to penetrate non-metallic materials and operate independently of ambient lighting—as the …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 1, 2026 · pp. 1–8 Read article
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DESIGNING OF AN EMBEDDED SYSTEM FOR SIGN LANGUAGE TRANSLATION
Abstract: Communication is a fundamental human right, yet over 70 million individuals worldwide who are deaf or speech-impaired face daily barriers in expressing their needs in healthcare, education, workplaces, and emergencies. Sign language serves as the primary mode of communication for this population; however, it is not universally understood by the hearing community, creating a persistent and critical gap in accessibility. Existing assistive solutions such as camera-based AI translators require high …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 31–44 Read article
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Maculopathy Detection and Recommendation using Machine Learning
Abstract: Maculopathies, a diverse group of eye diseases affecting the central portion of the retina, the macula, are a leading cause of vision loss globally. Early detection and accurate diagnosis are critical for timely intervention and preventing irreversible vision loss. However, traditional methods such as manually detecting the disease are time-consuming, tiring, and often lack sensitivity and specificity, hindering optimal patient care. Here we delve into the applications of machine learning …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 10–16 Read article
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A Comprehensive Review of Convolutional Neural Network Architectures and Evolution
Abstract: Convolutional Neural Networks (CNNs) have become a foundational deep learning framework in computer vision because they can automatically extract layered, increasingly complex features directly from raw image data. CNNs use convolutional, pooling, and activation layers to extract spatial patterns from basic edges to intricate object components, drawing inspiration from the human visual cortex. An overview of CNNs’ basic architecture is given in this study, along with an explanation of important …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 32–40 Read article