Recognition of Kannada Character Scripts Using Hybrid Feature Extraction and Ensemble Learning Approaches

Parashivamurthy, Supreetha Patel Tiptur; Rajashekaradhya, Sannangi Viswaradhya

doi:10.1080/01969722.2023.2175145

Cited by 6 publications

(2 citation statements)

References 51 publications

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“…Parashivamurthy et al [125] proposed an automated framework for recognizing handwritten Kannada scripts, addressing structural complexity and diverse styles. The system employs ensemble methods, combining image collection, preprocessing, and segmentation techniques.…”

Section: B Hybridized Versions Of Hgsomentioning

confidence: 99%

Advances in Henry Gas Solubility Optimization: A Physics-Inspired Metaheuristic Algorithm With Its Variants and Applications

El-Shorbagy,

Bouaouda,

Nabwey

et al. 2024

IEEE Access

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The Henry Gas Solubility Optimization (HGSO) is a physics-based metaheuristic inspired by Henry's law, which describes the solubility of the gas in a liquid under specific pressure conditions. Since its introduction by Hashim et al. in 2019, HGSO has gained significant attention for its unique features, including minimal adaptive parameters and a balanced exploration-exploitation trade-off, leading to favorable convergence. This study provides an up-to-date survey of HGSO, covering the walk through the historical development of HGSO, its modifications, and hybridizations with other algorithms, showcasing its adaptability and potential for synergy. Recent variants of HGSO are categorized into modified, hybridized, and multi-objective versions, and the review explores its main applications, demonstrating its effectiveness in solving complex problems. The evaluation includes a discussion of the algorithm's strengths and weaknesses. This comprehensive review, featuring graphical and tabular comparisons, not only indicates potential future directions in the field but also serves as a valuable resource for researchers seeking a deep understanding of HGSO and its advanced versions. As physics-based metaheuristic algorithms gain prominence for solving intricate optimization problems, this study provides insights into the adaptability and applications of HGSO across diverse domains.

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Section: B Hybridized Versions Of Hgsomentioning

confidence: 99%

Advances in Henry Gas Solubility Optimization: A Physics-Inspired Metaheuristic Algorithm With Its Variants and Applications

El-Shorbagy,

Bouaouda,

Nabwey

et al. 2024

IEEE Access

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“…Label the pairs as positive (1) or negative (0), depending on if it is the same character then that pair will be labelled 1 and if they are having different characters then that pair will be labelled 0, iii) Define the siamese neural network architecture with two identical networks that share the same set of weights. Both the network architecture works are based on CNN [11]- [14]. Two images are passed as input at the same time to both branches of the siamese networks and then are made to train on it and at the end the output of both the networks are compared using distance or similarity metrics, iv) Use of contrastive loss function to reduce the distance between positive data pairs and increase the distance between negative data pairs.…”

Section: Introductionmentioning

confidence: 99%

Optically processed Kannada script realization with Siamese neural network model

Parathra Sreedharanpillai,

Abraham,

Kotapuzakal Varghese

2024

IJ-AI

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<p><span>Optical character recognition (OCR) is a technology that allows computers to recognize and extract text from images or scanned documents. It is commonly used to convert printed or handwritten text into machine-readable format. This Study presents an OCR system on Kannada Characters based on siamese neural network (SNN). Here the SNN, a Deep neural network which comprises of two identical convolutional neural network (CNN) compare the script and ranks based on the dissimilarity. When lesser dissimilarity score is identified, prediction is done as character match. In this work the authors use 5 classes of Kannada characters which were initially preprocessed using grey scaling and convert it to pgm format. This is directly input into the Deep convolutional network which is learnt from matching and non-matching image between the CNN with contrastive loss function in Siamese architecture. The Proposed OCR system uses very less time and gives more accurate results as compared to the regular CNN. The model can become a powerful tool for identification, particularly in situations where there is a high degree of variation in writing styles or limited training data is available.</span></p>

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An efficient recognition of Handwritten Kannada Script using Variable Attention-based Coati Integrated Bi Directional Long Short-Term Memory

Siddanna,

Kiran

2024

Multimed Tools Appl

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Recognition of Kannada Character Scripts Using Hybrid Feature Extraction and Ensemble Learning Approaches

Cited by 6 publications

References 51 publications

Advances in Henry Gas Solubility Optimization: A Physics-Inspired Metaheuristic Algorithm With Its Variants and Applications

Advances in Henry Gas Solubility Optimization: A Physics-Inspired Metaheuristic Algorithm With Its Variants and Applications

Optically processed Kannada script realization with Siamese neural network model

An efficient recognition of Handwritten Kannada Script using Variable Attention-based Coati Integrated Bi Directional Long Short-Term Memory

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