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36 results for “Feature Fusion”
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Research ArticleOpen accessPhrase in the titleFeature Fusion in Improving Object Class RecognitionNoridayu Manshor, Amir Rizaan Abdul Rahiman, Mandava Rajeswari, Dhanesh RamachandramProblem statement: Extraction of features in object class recognition researches previously gives attention to local features as discriminative features. This is because local features have invariant properties that are robust to viewpoints, translation and rotation. However this feature still has a limitation to represent high-level representation of objects. The problem will occur if the object is too small and do … …Journal of Computer Science, Vol. 8, Issue 8 · 24 Jul 2012 · 6,907 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFeature Fusion Technique for Colour Texture Classification System Based on Gray Level Co-occurrence MatrixA. Suresh, K. L. ShunmuganathanIn this study, an efficient feature fusion based technique for the classification of colour texture images in VisTex album is presented. Gray Level Co-occurrence Matrix (GLCM) and its associated texture features contrast, correlation, energy and homogeneity are used in the proposed approach. The proposed GLCM texture features are obtained from the original colour texture as well as the first non … …Journal of Computer Science, Vol. 8, Issue 12 · 5 Jan 2013 · 6,615 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleMultimodal Biometrics using Feature FusionK. Krishneswari, S. ArumugamProblem statement: Biometric is a unique, measurable physiological or behavioral characteristic of a person and finds extensive applications in authentication and authorization. Fingerprint, palm print, iris, voice, are some of the most widely used biometric for personal identification. To reduce the error rates and enhance the usability of biometric system, multimodal biometric systems are used where more than one biometric … …Journal of Computer Science, Vol. 8, Issue 3 · 24 Jan 2012 · 7,370 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePalmprint Recognition using Feature Level FusionR. Gayathri, P. RamamoorthyProblem statement: Palmprint based biometric method has gained high impact over the other biometric methods due to its ease of acquisition, reliability and high client acceptance. Multiple feature extraction from image gives higher accuracy of the authentication system. Approach: This study presents the palmprint based identification methodology which uses the Gabor wavelet entropy to extract multiple features existing on the … …Journal of Computer Science, Vol. 8, Issue 7 · 19 May 2012 · 6,982 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Multi-Scale Feature Extraction and Fusion Deep Learning Method for Classification of Wheat DiseasesSajjad Saleem, Adil Hussain, Nabila Majeed et al.Wheat is an important source of dietary fiber and protein that is negatively impacted by a number of risks to its growth. The difficulty of identifying and classifying wheat diseases is discussed with an emphasis on wheat loose smut, leaf rust, and crown and root rot. Addressing conditions like crown and root rot, this study introduces an innovative approach that … …Journal of Computer Science, Vol. 21, Issue 1 · 2 Jan 2025 · 6,344 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDual-Branch Shape Texture Learning With Pyramid Residual and Sobel Edge Layers for Rice Variety ClassificationM Pradeep, M SiddappaAutomated rice variety classification categorizes rice types based on features, such as grain texture, shape, color, and size. Traditional handcrafted feature-based models fail at rice classification due to lighting variations, background noise, and environmental conditions, leading to overlapping visual characteristics and frequent misclassification. To address these challenges, this research proposes a novel Dual-Branch Convolutional Neural Network with Pyramid Residual Units … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 627 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,113 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Innovative Approach for Person Identification by Detection and Extraction of Optic Disc from Retina and Concha from EarC. Malathy, A. K. Sadiq, K. AnnapuraniPerson identification based on unimodal biometric system suffers from noise, intra class similarity, non universality, distinctiveness and spoof attacks. To alleviate the problem faced in unimodal biometric system biometric traits are combined in multimodal biometric system. In this study a new approach, to improve the recognition rate, reduces computational complexity and storage space is presented. Distinct method of person identification … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Sep 2014 · 6,557 accessesView PDFCite
Research ArticleOpen accessIn the keywordsImaging Spectroscopy and Light Detection and Ranging Data Fusion for Urban Features ExtractionMohammed Idrees, Helmi Zulhaidi Mohd Shafri, Vahideh SaeidiThis study presents our findings on the fusion of Imaging Spectroscopy (IS) and LiDAR data for urban feature extraction. We carried out necessary preprocessing of the hyperspectral image. Minimum Noise Fraction (MNF) transforms was used for ordering hyperspectral bands according to their noise. Thereafter, we employed Optimum Index Factor (OIF) to statistically select the three most appropriate bands combination from … …American Journal of Applied Sciences, Vol. 10, Issue 12 · 28 Oct 2013 · 7,152 accessesView PDFCite
Research ArticleOpen accessIn the keywordsChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 651 accessesView PDFCite