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34 articles for “CNN”
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A Study on CNN-Based Image Mosaicing
Abstract: The intricate tapestry of image mosaicing, while a cornerstone of computer vision, has long been constrained by the rigidity of classical, geometry-driven pipelines. Hand-crafted feature detectors and homography estimators, while effective in controlled environments, prove brittle when confronted with the challenges of real-world scenes: significant parallax, dynamic moving objects, repetitive textures, and illumination variance. This work introduces a fundamental paradigm shift, proposing a deep convolutional neural network (CNN) architecture designed …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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Classification of Fetal ECG Arrhythmia by Using Advance Hybrid Deep Learning Technique CNN-LSTM
Abstract: Fetal heart abnormalities, particularly fetal heart arrhythmias, are becoming an increasing concern in maternal healthcare. Early and accurate detection remains challenging due to limitations in conventional diagnostic techniques and inadequate signal processing methods. Existing studies have applied various machine learning and deep learning approaches; however, capturing the complex characteristics of fetal electrocardiogram (ECG) signals remains a significant gap. This study proposes an advanced deep learning-based approach for detecting fetal heart …
Published in International Journal of Cardiovascular Nursing · Vol. 12, Issue 1, 2026 · pp. 27–36 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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CNN-Based Traffic Sign Recognition with Voice Alerts
Abstract: Traffic sign recognition is a crucial component of intelligent transportation systems, significantly enhancing road safety by aiding both autonomous and human drivers. This paper presents a convolutional neural network-based traffic sign recognition system integrated with voice alerts. Our approach utilizes a deep learning model trained on a comprehensive dataset of traffic signs to accurately identify various road signs in realtime. Upon recognition, the system issues corresponding voice alerts to inform …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–9 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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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 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
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Machine Learning-Based Channel Estimation for 5G NR Systems: A Comprehensive Review of TDL/CDL Channel Models and CNN Architectures
Abstract: Accurate channel estimation is a fundamental requirement for reliable communications in fifth-generation New Radio (5G NR) systems, where highly dynamic propagation environments impose severe challenges on conventional pilot-based methods. This study provides a thorough analysis of channel estimate methods for 5G NR, including everything from contemporary deep learning (DL) techniques based on Convolutional Neural Networks (CNNs) to traditional Least Squares (LS) and Minimum Mean Square Error (MMSE) estimators. Our analysis …
Published in International Journal of Telecommunications & Emerging Technologies · 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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Facial Emotion Based Stress Detection Using CNN and Haar Cascade Algorithms
Abstract: Understanding human conduct requires the ability to recognize facial emotions, which has applications in everything from human-computer interaction to psychological wellness monitoring. This research provides a new approach to stress detection using Convolutional Neural Networks (or CNNs) and Haar Cascade classifiers. The suggested method uses CNN to recognize facial expressions and Haar Cascade algorithm for face detection. The methodology begins with preliminary processing the input photos, followed by face detection …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 2, 2024 · pp. 41–50 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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Automated Image Captioning Using Xception–CNN and LSTM for Descriptive Sentence Generation
Abstract: Generating descriptive texts for images is a complex and challenging task that requires advanced deep learning techniques. This paper presents a descriptive sentence generator for images using a combination of convolutional neural networks and recurrent neural networks. The proposed model utilizes a pretrained convolutional neural network, Xception, to extract image features, which are then processed by a long short-term memory network to generate meaningful textual descriptions. The model is trained …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 20–28 Read article
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Facial Emotion-Based Stress Detection Using CNN and Haar Cascade Algorithms
Abstract: Understanding human conduct requires the ability to recognize facial emotions, which has applications in everything from human–computer interaction to psychological wellness monitoring. This research provides a new approach to stress detection using convolutional neural networks and Haar Cascade classifiers. The suggested method uses convolutional neural network to recognize facial expressions and Haar Cascade algorithm for face detection. The methodology begins with preliminary processing of the input photos, followed by face …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 2, 2024 · pp. 1–11 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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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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Enhancing Image Quality with Deep Learning Techniques for Restoration and Denoising
Abstract: Abstract: Clear and high-quality images have become more and more necessary in recent years due to the rapid development of computer vision-based autonomous systems, including autonomous driving, underwater robots, video surveillance, and medical imaging. However, real-world circumstances, such as inclement weather, underwater scenes, and moving cameras, can lead to poorer-quality photographs. These degradations, which include color distortions, noise, and blurring, hurt how well visual systems accomplish tasks like target tracking, …
Published in International Journal of Broadband Cellular Communication · Vol. 10, Issue 2, 2024 · pp. 1–6 Read article
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Intelligence Video Surveillance Using Deep Learning
Abstract: Intelligent video surveillance powered by deep learning represents a transformative paradigm in security and surveillance. This new approach uses the power of complex neural networks to revolutionize the analysis and management of video data. Through the seamless incorporation of deep learning technologies like convolutional neural networks (CNN) and recurrent neural networks (RNN) into observation systems, automated identification, tracking, and classification of objects can be accomplished, alleviating storage constraints on the …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 1, 2024 · pp. 9–20 Read article
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Investigation of FSO Communication System Using Various Neural Networks
Abstract: A prospective method for high-speed data transfer via light propagation in free space, such as between buildings, satellites, or metropolitan areas, is Free Space Optics (FSO) communication. FSO systems have great promises, but their performance can be severely hampered by atmospheric disturbances. Problems like fog, rain, and turbulence cause the optical signal to be absorbed and scattered, increasing BER. To address these challenges, various Neural Network (NN) techniques such as …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 12–20 Read article
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Facial Expressions Detection Using Machine Learning
Abstract: Facial expressions are necessary in human communication and understanding emotions. First and foremost, identifying emotions is a critical factor for many businesses to comprehend how their customers are responding to the things they have introduced. It can also be utilized to find out if the amenities provided to their staff are meeting their needs. Additionally, it has a plethora of other applications, such as utilizing a camera to identify someone's …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 1, 2024 · pp. 11–16 Read article
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Need of Modern Technologies in Agriculture
Abstract: The surge in population growth coupled with the diminishing availability of cultivable land has significantly heightened the strain on arable areas. While the provision of sustenance for the underprivileged remains a pressing issue, the focus has expanded beyond mere food provision to ensuring a nutritionally balanced diet. Consequently, there arises an urgent imperative to delve into contemporary methodologies aimed at not only feeding the burgeoning population but also preserving essential …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article