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68 articles for “feature fusion”
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Feature Fusion Based Iris and Retina Recognition System Using Kohonon Self-Organizing Mapping Neural Network Algorithm
Abstract: This paper proposes a model of biometric security with feature fusion based iris and retina recognition system. Though, a lot of research works have done for iris recognition system and it is not new for the fusion of multimodal iris recognition in the area of biometric security and authentication system. But, it is a relatively new idea of mixing iris and retina features for human authentication. Here, the features of …
Published in Trends in Electrical Engineering · Vol. 5, Issue 2, 2015 · pp. 22–26 Read article
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A Novel Feature Level Fusion Method for Classification of Remote Sensing Images
Abstract: Feature level fusion approach is utilized in this paper to classify remote sensing images. Texture features are extracted from panchromatic images using mixed Gabor filter (GB), fast gray level co-occurrence matrix (GLCM) and linear binary pattern (LBP). The resultant texture features are classified using nearest neighbor (k-NN) classification method. Spectral features are extracted from the MS image and segmented using over segmented k-means algorithm with novel initialization (OSKNI). Finally the …
Published in Journal of Remote Sensing & GIS · Vol. 10, Issue 1, 2019 · pp. 58–65 Read article
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Pair of Retina Recognition System Using Hopfield Neural Network Algorithm
Abstract: process of pair of retina recognition system using feature fusion method has been proposed in this paper. Left and right retinal images of human have been used for the inputs of this retinal recognition system. Wavelet based retinal image pre-processing technique has been applied to process the retina images. After extracting the features from the left and right retinal images, features are concatenated using feature fusion technique. Principal Component Analysis …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 41–45 Read article
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Cascade CNN Framework for Low Resolution Image Classification
Abstract: Abstract: Low resolution images contain less visual information, so classifications of these images are difficult. For overcoming this problem, cascade CNN framework for low resolution image classification is proposed. In this framework, super resolution CNN (SRCNN) enlarges low resolution image into super resolution image. The convolutional features of these super resolution images are fused with low resolution convolutional features which are extracted by low resolution CNN (LRCNN) feature extractor. A …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 39–43 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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Decision Fusion based Pair of Iris Recognition using Back-Propagation Learning Neural Network Algorithm
Abstract: AbstractThe contribution of this work is to enhance the performance of the iris recognition system through decision fusion of left and right iris pattern. Iris recognition system performs well and identify human correctly in neutral environment. In this paper a pair of iris recognition system has been proposed, which is capable enough to identify human through noisy environments. Principal component analysis based dimensionality reduction technique has been used toreduce and …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 1–6 Read article
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Iris and Retina Recognition based Multimodal Person Identification System
Abstract: Nowadays we are living in such an era of science where authentication has become one of the greatest challenges in the thorny issue of security. There are many ways in which authentication can be provided, but among them biometric authentication is indispensable. Among all the biometrics in use today the highest level of uniqueness, performance, universality and circumvention are provided by eye based biometrics (i.e., iris and retina recognition). This …
Published in Current Trends in Information Technology · Vol. 5, Issue 1, 2015 · pp. 22–28 Read article
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Facial Recognition System Based on Score-level Fusion of LBP and Gabor Feature Extraction Techniques
Abstract: Face recognition is gaining recognition over the last few decades. Nowadays, this technology is highly used in smartphones to unlock the phone by sensing the face of an individual. In our paper, we aim to maximize recognition rates by performing the score-level fusion of two feature extraction techniques: Local Binary Pattern (LBP) and Gabor features. These two techniques on fusion provide better recognition rates as compared to the recognition rates …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 10–14 Read article
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Improved Melanoma Recognition using Score Fusion Framework based on Deep Classifiers
Abstract: Melanoma is a fast-growing and malignant cancer that affects neural crest-derived cells of the skin. Early detection is the key to survival and rapid recovery; however, typical diagnosis is based on visual inspection by expert dermatologists. Many melanoma recognition methods have been proposed in the literature that can classify lesions, based on hand-crafted as well as deep learning-based features. However, an accurate, automated method for melanoma is still required. This …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 2, 2021 · pp. 25–33 Read article
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SYNERGISTIC FUSION OF HYPERSPECTRAL AND HIGH RESOLUTION IMAGE FOR IMPROVING PERFORMANCE AND RELIABILITY OF AUTOMATICALLY EXTRACTED URBAN FEATURES
Abstract: Image fusion is a generic word referring to several techniques of digital image processing which are used to integrate data from different spatial and spectral resolutions in order to obtain higher-quality synthetic images. This paper emphasizes the assessment and systematic analysis of image fusion techniques by measuring the quantity of enhanced information in fused images. EO1- Hyperion and IKONOS (MSS+PAN) have been fused using Principal component analysis, Gram-Schmidt Transformation (GST) …
Published in Journal of Remote Sensing & GIS · Vol. 1, Issue 1, 2010 · pp. 1–11 Read article
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An Approach of Multi-modal Biometric Iris and Speech based Person Recognition System with Decision Fusion Technique
Abstract: This paper presents a unique approach of multi-modal iris and speech feature based person recognition system. Iris images and speech signals are taken from CASIA iris database and NOIZEUS speech database respectively. Iris features are extracted after applying iris images noise removing and image pre-processing techniques. On the other hand, speech signal noise removing, start-end points detection algorithm, silence parts removal, windowing and feature extraction techniques are applied to extract …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 2, Issue 2, 2015 · pp. 5–10 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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DETECTION OF LUNG CANCER USING SOFT COMPUTING TECHNIQUES
Abstract: Cancer is a generic term that can affect any part of the body. Most cancers, 90%-95%, are because by environmental and lifestyle variables which cause genetic mutations. Inherited genetics account for 5% to 10% of the total. Early identification of lung cancer has improved patient survival and has been a vital study topic. It starts within the cells covering the bronchi and lung parts like bronchioles or alveoli. Due to …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 1–12 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 1–9 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Prediction of Likelihood of Contraceptive Method among Women using Machine Learning Techniques
Abstract: This paper presents the various machine learning techniques and early fusion approach for analyzing usage of contraceptive methods among women. The analysis has been done using various nine features that the usage of contraceptive among women is whether low, high or not at all. This paper also evaluates the effect of contraceptive prediction is affected by men, age, and religion. Finally, comparison of classification accuracy has been employed between 22 …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 6, Issue 1, 2019 · pp. 1–6 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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Comparative Review on Image Fusion Techniques
Abstract: The goal of image fusion is to combine relevant information from two or more images of the same scene of the different times. The result of image fusion is a new fused image which is more suitable for human being and machine discernment for further image-processing tasks like segmentation, feature taking out and object recognition. Image fusion is the combination of two or more different images to form a new …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 1, Issue 3, 2014 · pp. 10–13 Read article
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An Approach of Likelihood Ratio Score Fusion for Appearance and Shape based Face Recognition
Abstract: AbstractThis paper deals with an approach of likelihood ratio based score fusion technique where appearance and shape based facial features have been used to enhance the efficiency of existing face recognition system. Active Shape Model (ASM) has been used to extract the appearance and shape based facial features. Two different types of features have been used in this work in such a way that when the appearance based feature contains …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 3, 2013 · pp. 1–8 Read article