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47 articles for “pattern recognition”
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Using Image and Pattern Recognition to Play the Game of Connect Four Using Computer
Abstract: Connect four is an advanced version of the commonly played game tic-tac-toe. Using an image recognition system, the computer can be assigned the current state of the play and using an algorithm the next move can be calculated. The extraction of image information and using it to find the solution of the diff condition is a fundamental in this field which is substantially extrapolated here. This paper is a result …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 1, Issue 2, 2015 · pp. 1–5 Read article
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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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Investigation and Classification of Cardiac MRI Images using Texture Analysis
Abstract: In order to quantify the myocardial viability after infarction, recent researches have developed new cardiac MRI protocol using particle contrast agents which highlight the different areas after infarction: i.e. the healthy area, the necrosed area and the two ischemic areas. Actually the researches are carried out on rodents micro cardiac MRI for which the obtained images are very noisy and present a very low contrast. In this paper, we analyse …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 2, 2021 · pp. 37–41 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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Face Recognition and Identification Using Computer Vision
Abstract: ABSTRACT In practice, identification of criminal in India is done through thumbprint identification. However, this type of identification has many constraints. Our face recognition poses to be able to detect face and recognize face automatically. Nowadays, face recognition systems use biometric for many security applications. This technique uses an image-based approach toward artificial intelligence by removing redundant data from face images through image compression using computer vision that compares a …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 1, 2019 · pp. 6–10 Read article
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Local Binary Patterns and Its Extended Variants
Abstract: ABSTRACTThis paper focuses on the Local Binary Patterns and its various important variants. LBP is a non-parametric descriptor and used to extract, analyze, recognize and classify the different modality images. It summarizes the local patterns of image characteristics efficiently. LBP and its many extended versions have been extensively used in numerous applications of computer vision, image processing, pattern recognition and biomedical field in recent years. Very discriminative and computationally efficient …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 13–25 Read article
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Redundant Keypoint Elimination Using Redundancy Index on Basic SIFT Algorithm
Abstract: ABSTRACT Matching features across different images is a common problem in computer vision. For the images of different scales and rotations, there is the need of scale-invariant feature transform (SIFT). SIFT identifies the distinctive keypoints that are invariant to location, scale, rotation, robust to affine transformations (changes in scale, rotation, shear, and position) and changes in illumination, which are usable for object recognition. SIFT algorithm includes two main stages: feature …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 1, 2019 · pp. 22–31 Read article
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Deep Learning in Medical Image Classification and Object Detection: A Survey
Abstract: Deep learning methods have demonstrated superior performance in the area of computer vision, speech recognition, natural language processing, healthcare, and many more. Convolutional neural networks (CNNs) are a class of deep learning methods that have the ability to learn from raw data available as images, audio, or text. CNNs have become a powerful tool for variety of pattern recognition tasks due to the availability of abundant data and GPU-based training. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 8, Issue 2, 2022 · pp. 1–15 Read article
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Identifying the Age Using Face Image Using DWT, LBP, SVM and k-NN
Abstract: ABSTRACTThe research related to identifying the age using face images has become progressively more important, due to the fact it has a multiplicity of potentially helpful applications. In this paper we survey the complete age synthesis or age estimation from face images techniques. Automatic facial age identifying is one of the main issues in pattern recognition which shows the age of human according to her/his facial expressions. Basically, age detection/estimation …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 26–37 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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Image Denoising Using IBP n Filter
Abstract: Abstract The ultrasound images are blurred by the multiplicative noise that is the Speckle pattern. It decreases the contrast and resolution of ultrasound images those outcomes in weak interpretation of image characteristics. In several image processing mechanisms like segmentation, classification and pattern recognition the speckle is a significant part. The conventional methods calculate the computation of LBP on gradient. The limitation of this technique was that the LBP mechanism divide …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 2, 2018 · pp. 37–45 Read article
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Adaptive Visual Tracking for Human Motion Detection
Abstract: Abstract—Object detection is one of the fundamental steps for automated video analysis in many vision applications. Object detection in video is usually performed by background subtraction techniques. In the existing method they proposed object detection by pixel variation of the image from one frame to another and the background subtracted by the training process in the recorded videos. In the proposed method the object is detected in the live video …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 1, 2019 · pp. 1–5 Read article
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High Efficient Energy Harvesting by Solar Panel Using Polychromat Layer
Abstract: Abstract:- This project is used to harvest high amount of energy by solar panel using polychromat layer. Polychromat layer is the one which splits all kinds of radiation from the sun where the other solar panels without the polychromat layer can not absorb all types of radiation from the sun. This layer absorb all type of radiation from 10^-4 to 10^-8 while the others can’t absorb it. The complete rotation …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 1, 2019 · pp. 11–15 Read article
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Review on Medical Image Enhancement Techniques
Abstract: Abstract—Image enhancement is the process of improving visual quality of the image. In this paper, Image Processing Methods were implemented on CTA medical images for better understanding. LPFED with different kernels, GLTLPF, are the major techniques that were used to enhance images. The output results give more insights about the images and enhance the overall scope of finding more perceptions. Keywords: Medical Image, Image Enhancement, Filter, Gray Level, Edge, Computer …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 1, 2019 · pp. 16–21 Read article