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52 articles for “Convolutional Neural Networks”
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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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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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Deep Learning for Smarter Farming: Innovations in Plant Disease Identification
Abstract: Agriculture is the backbone of global food security, yet plant diseases significantly impact crop yields and farmers' livelihoods. Traditional disease detection methods are often time-consuming and require expert intervention, making them less feasible for large-scale farming. Recent advancements in deep learning have revolutionized plant disease identification by offering automated, accurate, and efficient solutions. This article explores innovative deep learning techniques, including convolutional neural networks (CNNs) and transformer-based models, that enhance …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 27–32 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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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
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General Health Check-up, Health Care Model using CNN and Internet-of-Medical Things
Abstract: Many people may believe that undergoing a comprehensive medical check-up is unnecessary when they feel perfectly healthy. However, this perception is mistaken. Regular health check-ups are essential to maintain overall well-being and to detect potential health issues early, enabling proactive steps to prevent them from worsening. Such check-ups are valuable for both individuals in good health and those with existing medical conditions, as they provide insight into the progress of …
Published in International Journal of Distributed Computing and Technology · Vol. 9, Issue 2, 2023 · pp. 20–25 Read article
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Facial Expression Recognition by Using Multifeatured Fusion And Deep Learning Techniques
Abstract: In our daily lives, sentiment analysis is a vital part of communication. A vital component is information regarding how the user feels when someone communicates. You will need a solution that can handle everything from recognizing a user's emotional state to personalizing the user experience. This study's objective is to look into emotions. Today, deep learning techniques are quickly advancing in a variety of fields, including computer vision. Without a …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 8, Issue 2, 2022 · pp. 16–22 Read article
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Criminal Face Identification Using Deep Learning and Machine Learning
Abstract: Criminal face identification is a crucial task for law enforcement agencies to prevent and solve crimes. The traditional methods for identifying criminals using human expertise and eyewitness testimonies have several limitations, such as subjectivity, inaccuracy, and unreliability. Machine learning and deep learning techniques have yielded promising gains in facial recognition and identification applications in recent years. In this study, we propose a criminal face identification system that combines machine learning …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 1, 2023 · pp. 28–34 Read article
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Knowing Captchas Using Deep Learning
Abstract: Websites can use CAPTCHA (Completely Automated Public Turing Test to Differentiate Computers from Humans) to distinguish between humans and machines and prevent automated attacks by programmers and malicious programmers. Studies on CAPTCHA recognition have the potential to uncover security flaws, advance CAPTCHA technology, and even advance handwriting and license plate recognition. However, the whole objective of the CAPTCHAs can be bypassed by utilizing the principles of deep learning and computer …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 8, Issue 2, 2022 · pp. 30–40 Read article
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Analyzing Crowds with Deep Learning: A Review of Methods and Challenges
Abstract: With the growing population, the need for an effective crowd management tool emerged. It is important to monitor and analyze unusual crowd movements and behavior for many applications such as peaceful events, protests, gatherings, or traffic management. Current systems, such as video surveillance, are a useful technique for crowd monitoring, but they require human visual capabilities to monitor the crowd. This work is a paper on Crowd Analysis using convolution …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 2, 2023 · pp. 30–42 Read article
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Using LapSRN (Image Resolution Deep Learning Model) with Transfer Learning
Abstract: In order to create high-resolution photographs, Super Resolution (SR) tries to transform low-resolution photos. SR methods can be categorized into two categories: Single Image Super Resolution (SISR) and Video Super Resolution (VSR). SISR initially needs to upscale low-resolution photos to high-definition images. VSR, which stands for "image super resolution," is used to transform low-quality videos into ones with higher resolution. Deep learning techniques use Convolutional Neural Networks (CNN), a special …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 8, Issue 1, 2022 · pp. 18–24 Read article
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A Comparative Study Of RCNN, YOLO V3-Tiny and YOLO V5 Object Classification Architectures for Accurate Object Classification in Military Domain
Abstract: Late advances in object distinguishing proof computations consolidate speedy and faster RCNN whichmade the ID times also low with high accuracy. In this paper, we demonstrate the reliability of asuggested computation that employs RPN (Region Suggestion Associations) and Fast RCNN (RegionbasedConvolutional Neural Networks) for the distinguishing proof. The RPN gives region suggestionsfrom that we give the ROI (Regions of Interest) as commitment to the RCNN association, it will ingeneral be …
Published in International Journal of Broadband Cellular Communication · Vol. 7, Issue 1, 2021 · pp. 19–37 Read article