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A hybrid convolutional neural network and support vector machine classifier for Amharic character recognition

Neural Computing and Applications 2024年第27期36卷 16839-16856页

作者： Tsegaye, Muluken Zemed Shashi, Mogalla Department of Information Technology Andhra University College of Engineering AP Visakhapatnam530003 India Department of Computer Science Andhra University College of Engineering AP Visakhapatnam530003 India

Optical character recognition is a way of converting scanned images of printed or handwritten documents into machine-encoded text, making it easier to store, browse, retrieve, and process electronic data. In this research, a Printed Amharic Characters Recognition dataset is prepared to train and test a model. Images in the dataset only contain 231 basic Amharic characters that are normalized to 32 × 32 pixels. In this work, a hybrid model of the two super classifiers is developed: the convolutional neural network (CNN) and the support vector machine (SVM). In this novel hybrid CNN-SVM model, CNN works as an automatic feature extractor from the raw images, and then, the extracted feature vectors are given as input to SVM for classification and recognition. A 99.84% accuracy was achieved on the own-prepared dataset and 95.59% accuracy on the benchmark Amharic Optical Character Recognition Database in classifying the testing dataset images. The proposed hybrid CNN-SVM model gave better results than the CNN with a fully connected layer. Moreover, the proposed model outperforms previously existing works attempted by others to recognize printed Amharic characters on the same and different datasets. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Support vector machines

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Disparity Computation With Low Intensity Quantization on Stereo Image Pairs

IEEE Transactions on Computational Imaging

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IEEE Transactions on Computational Imaging 2024年 10卷 318-328页

作者： Lin, Huei-Yung Hsu, Tsai-Yu National Taipei University of Technology Department of Computer Science and Information Engineering Taipei10608 Taiwan National Chung Cheng University Department of Electrical Engineering Minhsiung621301 Taiwan

From variate bit-rate stereo matching, it is observed that the image pair with a low intensity quantization level is still capable of providing good disparity maps. In this article, a mathematical model representing the level of disparity discontinuity is proposed to formulate the mismatching prediction based on the intensity quantization. It is used to derive the minimum quantization level for quality-assured stereo matching. Due to the high computational cost of stereo processing, the reduction of image data usage will benefit both network training and real-time inference. The formulation presented in this work is investigated extensively for various types of scenes for disparity computation. In the experiments, the feasibility of our approach is validated with Middlebury, KITTI 2015, and synthetic Scene Flow datasets. © 2015 IEEE.

关键词： Image coding

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An efficient Manuka honey purity classification technique with FSVM

An efficient Manuka honey purity classification technique wi...

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2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Huma, Shafia Nur Akter, Sabrina Akter, Subrina Nafisa, Nuren Patwary, M. Jamshed Alam International Islamic University Chittagong Department of Computer Science and Engineering Chittagong Bangladesh Chittagong University of Engineering and Technology Institute of Information and Communication Technology Chittagong Bangladesh

ISBN: (纸本)9798331529765

Manuka honey is renowned for its exceptional medicinal properties in healing wound infections and other conditions. Due to its high cost, this honey is a common target for fraud. Several machine-learning techniques are available for classifying the quality of Manuka honey. However, existing methods often struggle with accurate categorization. Imprecise data, high dimensionality, imbalances in various classes, and lengthy processing times are the root causes of misclassification. This research addresses these issues by providing a viable honey impurity classification method using Fuzzy Support Vector Machine (FSVM). The experiments utilize a freely available pre-processed Manuka honey dataset containing 3300 data points and 128 features. FSVM enhances the classification process by assigning fuzzy membership functions to each class, thereby handling imprecise data and resolving class imbalance problems. Furthermore, this study aims to minimize time and space complexity by reducing dimensions. For this purpose, four feature reduction techniques have been applied to the dataset, and the results have revealed that applying FSVM along with Class Embodiment Autoencoder (CEAE) has yielded 97% accuracy and F1 score. Lastly, a comparative analysis has been performed with other existing SVM methods, and it has been found that the proposed technique has outperformed previous SVMs in terms of accuracy and time and space complexity. The previous method takes (O(N!)) time complexity whereas the proposed method's time complexity is (O(N2)), where N represents the number of data points in the dataset. This significant reduction provides a clear picture of the feasibility of the suggested approach and its potential to enhance the procedures involved in the classification and authentication of honey. © 2024 IEEE.

关键词： Support vector machines

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Enhancing Security and Privacy in Distributed Face Recognition Systems through Blockchain and GAN Technologies

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computers, Materials & Continua 2024年第5期79卷 2609-2623页

作者： Muhammad Ahmad Nawaz Ul Ghani Kun She Muhammad Arslan Rauf Shumaila Khan Javed Ali Khan Eman Abdullah Aldakheel Doaa Sami Khafaga School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu611731China Department of Computer Science University of Science&TechnologyBannu28100Pakistan Department of Computer Science University of HertfordshireHatfieldAL109ABUK Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

The use of privacy-enhanced facial recognition has increased in response to growing concerns about data securityand privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a varietyof industries, including access control, law enforcement, surveillance, and internet communication. However,the growing usage of face recognition technology has created serious concerns about data monitoring and userprivacy preferences, especially in context-aware systems. In response to these problems, this study provides a novelframework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain,and distributed computing to solve privacy concerns while maintaining exact face recognition. The framework’spainstaking design and execution strive to strike a compromise between precise face recognition and protectingpersonal data integrity in an increasingly interconnected environment. Using cutting-edge tools like Dlib for faceanalysis,Ray Cluster for distributed computing, and Blockchain for decentralized identity verification, the proposedsystem provides scalable and secure facial analysis while protecting user privacy. The study’s contributions includethe creation of a sustainable and scalable solution for privacy-aware face recognition, the implementation of flexibleprivacy computing approaches based on Blockchain networks, and the demonstration of higher performanceover previous methods. Specifically, the proposed StyleGAN model has an outstanding accuracy rate of 93.84%while processing high-resolution images from the CelebA-HQ dataset, beating other evaluated models such asProgressive GAN 90.27%, CycleGAN 89.80%, and MGAN 80.80%. With improvements in accuracy, speed, andprivacy protection, the framework has great promise for practical use in a variety of fields that need face recognitiontechnology. This study paves the way for future research in privacy-enhanced face recognition systems, emphasizingt

关键词： Facial recognition privacy protection blockchain GAN distributed systems

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Preserving friendly stacking and weighted shadows in selective scalable secret image sharing

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Multimedia Tools and Applications 2023年第19期82卷 29283-29305页

作者： Lee, Jung-San Chen, Yin-Chin Hsieh, Yun-Hao Chang, Shih-Hao Huynh, Ngoc-Tu Department of Information Engineering and Computer Science Feng Chia University Taichung40724 Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan Department of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam

With advancement of technology, the technique of selective scalable secret image sharing (SSSIS) was first proposed in 2017 as a new alternative of secret image sharing. The region of interest (ROI) in the protected secret could be revealed progressively once the number of collected shadows has reached a predefined threshold. Accordingly, the ROIs of the secret image increase based on the number of collected shadows. Nonetheless, players without sufficient shadows may be able to learn the location and contour of hidden secret to perform advanced guessing attacks. Thus, we aim to introduce friendly stacking to yield a genuine outcome of mitigating this risk during the recovery process. Furthermore, the weighting concept is brought into constructing the meaningful shadow so that the priority of a specific participant can be emphasized to approach real applications. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Image segmentation

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Abnormal Activity Detection and Classification of Bus Passengers with In-Vehicle Image Sensing

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IEEE Access 2024年 12卷 23057-23065页

作者： Lin, Huei-Yung Tseng, Chun-Han National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106 Taiwan National Chung Cheng University Department of Electrical Engineering Chiayi621 Taiwan

As the self-driving technology is getting mature for public transportation applications, the safety concern of onboard passengers has become an important issue. It is essential to identify inappropriate or hazardous behaviors of passengers for the vehicles without human operators. In this work, we propose a technique to detect and classify the abnormal activities of passengers in a bus environment. Different from the existing human activity classification algorithms, our approach reduces the occlusion and increases the recognition rate by acquiring images from an overhead vision system. To overcome the increased complexity on feature extraction and classification, an action recognition network for top-view images are proposed by incorporating both spatial and temporal information. An image dataset, BUS-HAR, is generated for practical application scenarios with bus passengers. Experiments using real-world scene images have demonstrated the feasibility of our technique compared to existing approaches. The codes and image dataset are made available publicly at https://***/richardkuo1999/passenger-action-recognition. © 2013 IEEE.

关键词： Extraction

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Design and Analysis of a UWB Slotted Vivaldi Antenna for Microwave Imaging Applications

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IEIE Transactions on Smart Processing and Computing 2023年第4期12卷 350-357页

作者： Paul, Liton Chandra Majumder, Akash Rani, Tithi Hossain, Md. Najmul Rahim, Md. Abdur Shin, Jungpil Yun, Keun Soo Department of Electrical Electronic and Communication Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh Department of Electronics & Telecommunication Engineering Faculty of Electrical & Computer Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh Department of Computer Science and Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh School of Computer Science and Engineering The University of Aizu / Fukushima Aizuwakamatsu965-8580 Japan School of Computer and Information Technology Ulsan College / Dong-gu Ulsan44610 Korea Republic of

An ultra-wideband (UWB) slotted compact Vivaldi antenna with a microstrip line feed was evaluated for microwave imaging (MI) applications. The recommended FR4 substrate-based Vivaldi antenna is 50×50×1.5 mm3 in size. The proposed compact Vivaldi antenna showed good radiation characteristics and spanned an ultra-wide bandwidth of 10 GHz, ranging from 3.6 to 13.6 GHz, using a microstrip line feed with a radial stub, tapered slots, and resonant cavities. After analyzing the simulation findings, the proposed compact slotted UWB Vivaldi antenna was compared with the basic Vivaldi antenna. The maximum gain and efficiency were 7.35 dB and 82%, respectively. The antenna was simulated in the time domain using the computer simulation technology (CST) microwave studio. The frequency domain solver was also used for cross-validation, and the results were equally good. In conclusion, the proposed compact Vivaldi antenna is a good option for microwave imaging applications. © 2023 The Institute of Electronics and information Engineers.

关键词： Cavity resonators

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Single-Valued Neutrosophic Graph with Heptapartitioend Structure

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Neutrosophic Sets and Systems 2025年 80卷 728-748页

作者： Fathi, Hanaa Myvizhi, M. Abdelhafeez, Ahmed Abdellah, Mohamed Refaat Eassa, Mohamed Sawah, Mohamed S. Elbehiery, Hussam College of Information Technology Amman Arab University Amman Jordan KPR Institute of Engineering and Technology Tamilnadu Coimbatore India Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan The Department of Computer Science College of Information Technology Misr University for Science and Technology Cairo Egypt Department of Computer Science Faculty of Information Technology Ajloun National University P.O.43 Ajloun26810 Jordan

This study applies single-valued neutrosophic sets, which extend the frameworks of fuzzy and intuitionistic fuzzy sets, to graph theory. We introduce a new category of graphs called Single-Valued Heptapartitioned Neutrosophic Graphs (SVHNG) and investigate their characteristics through comprehensive proofs and illustrative examples. © 2025, University of New Mexico. All rights reserved.

关键词： Heptapartitioend Neutrosophic Set Neutrosophic Graph Neutrosophic Sets SVHN-Graph

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Speech cryptography algorithms: utilizing frequency and time domain techniques merging

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Journal of Ambient Intelligence and Humanized Computing 2024年第10期15卷 3617-3649页

作者： Faragallah, Osama S. Farouk, M. El-sayed, Hala S. El-bendary, Mohsen A. M. Department of Information Technology College of Computers and Information Technology Taif University Al- Hawiya21974 Saudi Arabia Department of Computer Science and Engineering Menoufia University Menouf32952 Egypt Department of Electrical Engineering Menoufia University Shebin El-kom32511 Egypt Department of Electronics Technology Faculty of Technology and Education Helwan University Cairo Egypt

Due to the importance security of sensitive speech and audio signals such as the countries president’s call phone, this research work presents an efficient audio cryptosystem. Audio speech communications play main and essential role in the human daily life, covering many important fields ranging from simple personal private information up to top secret, sensitive and critical information. It is difficult to prevent the eavesdropping by unauthorized person especially 1-D audio scrambling methods, it is built by simple algorithms and has low security level. So, there is a dire need for enhancing audio cryptosystem to be more secure against different types of attacks. In this work, the enhanced audio cryptosystem is proposed, the first approach enhances multiple key audio cryptosystem utilizing the chaotic baker map through enhancing the confusion level for both encryption/decryption algorithms employing time and transform domains. Simulation experiments revealed that the proposed boosted audio cryptosystem on time and transform domains is secure and robust against different types of attacks. The boosted multiple key based audio crypto-system is performed by increasing confusion and enlarging the secret-key space. Results of the simulation experiments revealed that the proposed multiple secret key-enhanced confusion audio cryptosystem is secure and robust with respect to different types of attacks. Moreover, results for transform domains show better results than results for time domain for the three proposed boosted audio cryptosystem. Also, the third proposed audio cryptosystem DWT-based shows the best results among all other proposed audio cryptosystem. Due to the results, robustness and reliability of proposed technique are higher the existing audio cryptographic system. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Cryptography

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Progressive secret image sharing based on Boolean operations and polynomial interpolations

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Multimedia Systems 2024年第4期30卷 1-14页

作者： Chen, Hao Xiong, Lizhi Yang, Ching-Nung School of Computer Science Nanjing University of Information Science and Technology Jiangsu Nanjing China Department of Computer Science & amp Information Engineering National Dong Hwa University Hualien Taiwan

With the expansion of network bandwidth and the rise of social networks, image sharing on open networks has become a trend. The ensuing privacy leakage events have aroused widespread concerns. Therefore, image sharing that protects privacy is desired. Progressive Secret Image Sharing (PSIS), a multilevel privacy protection technology for images, offers a promising solution. However, the progressivity of the majority of PSIS schemes depends on the preprocessing of a secret image, which increases the calculation costs. In addition, a block-based PSIS may have information leakage security risks when processing highly confidential images. Many existing PSIS schemes use a single operation to share secret images, which makes the schemes inflexible and limits the application scenarios. Therefore, we propose a PSIS based on Boolean operations and Polynomial interpolations (PSIS-BP). The proposed scheme divides the bit-plane of the pixel into two parts. One part is utilized to perform the Boolean operation, and the other part is used to perform the polynomial interpolation. Different assignment strategies can produce different progressive reconstruction levels and expand the application scenarios of the scheme. Theoretical analyses and experimental results demonstrate that the proposed scheme is secure, low-cost, and flexible. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Polynomials

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