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An Efficient Procedure for Removing Salt and Pepper Noise in Images

Informatica (Slovenia) 2022年第2期46卷 197-203页

作者： Xu, Guangyu Aminu, Muhammad Jibril School of Computer Science and Engineering Anhui University of Science and Technology Huainan China

In this paper, we propose an efficient algorithm for removing salt and pepper noise in images. The process of denoising is implemented in two stages: noise detection followed by noise removal. For noise detection, two extreme intensity values in an image are used to detect possible "noise pixels". For noise removal, the switching mechanism only selects "noise pixels" for processing to avoid altering any fine image details, and only the identified noise-free pixels are used to achieve better denoising performance. Two filtering techniques, the edge-preserving filtering (EPF) and the extremum-compressing median filtering (ECMF), are employed for edge-preserving and noise removal. The EPF provides higher correlation between the corrupted pixel and neighborhood pixel, which gives rise to better edge preservation. The ECMF can yield an appropriate estimation by selecting the median pixel from the noise-free pixels of current filtering window. The proposed algorithm is tested on different images and provides a better restoration performance over some of the salt and pepper noise filters. © 2022 Slovene Society Informatika. All rights reserved.

关键词： Salt and pepper noise

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Delineating emotional differences between depressed and non-depressed individuals using a novel multimodal framework

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Multimedia Tools and Applications 2024年 1-22页

作者： Gill, Rupali Singh, Jaiteg Hooda, Susheela Srivastava, Durgesh Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Department of Computer Science & amp Engineering Chitkara University Punjab Rajpura140417 India

Affective computing has garnered substantial attention for its potential in mental health diagnostics, including the nuanced differentiation of emotional states in depressed versus non-depressed individuals. This study significantly advances the field by introducing EmoFusion-AttNet, a state-of-the-art computational model that employs a multimodal approach for emotion classification. Leveraging a statistically robust and demographically diverse sample, participants were first screened for depressive symptoms using BDI & PHQ-Q questionnaires, ensuring a representative distribution. The EmoFusion-AttNet model employs Convolutional Neural Networks (CNNs) to extract spatial features from facial data, while Long Short-Term Memory (LSTM) networks capture the temporal intricacies of EEG signals. A fusion layer equipped with an attention mechanism synthesizes these multi-dimensional data streams, enhancing feature selection and accuracy. Impressively, the model achieved a classification accuracy of 95%, setting a new benchmark for emotion-based classification models. To validate these findings, we conducted an in-depth analysis of EEG data, focusing on Alpha and Theta band activities. Our results revealed a decrease in Alpha power and an increase in Theta power in the depressed group, aligning with current neurophysiological understandings. These findings validate the model’s clinical applicability and set the stage for future research in affective computing, particularly its implications for mental health diagnostics and treatment planning. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Clinical research

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Energy Efficient Transmitter Creation by Consuming Free Energy in Molecular Communication

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IEEE Transactions on Molecular, Biological, and Multi-Scale Communications 2025年第2期11卷 292-303页

作者： Jing, Dongliang Li, Linjuan Cheng, Zhen Lin, Lin Eckford, Andrew W. Northwest A and F University College of Mechanical and Electronic Engineering Yangling China Ministry of Agriculture and Rural Affairs Key Laboratory of Agricultural Internet of Things Yangling China Zhejiang University of Technology School of Computer Science and Technology Hangzhou310023 China Tongji University College of Electronics and Information Engineering Shanghai China York University Department of Electrical Engineering and Computer Science TorontoON Canada

Information molecules play a crucial role in molecular communication (MC), acting as carriers for information transfer. A common approach to get information molecules in MC involves harvesting them from the environment;however, the harvested molecules are often a mixture of various environmental molecules, and the initial concentration ratios in the reservoirs are identical, which hampers high-fidelity transmission techniques such as molecular shift keying (MoSK). This paper presents a transmitter design that harvests molecules from the surrounding environment and stores them in two reservoirs. To separate the mixed molecules, energy is consumed to transfer them between reservoirs. Given limited energy resources, this work explores energy-efficient strategies to optimize transmitter performance. Through theoretical analysis and simulations, we investigate different methods for moving molecules between reservoirs. The results demonstrate that transferring higher initial concentration molecules enhances transmitter performance, while using fewer molecules per transfer further improves efficiency. These findings provide valuable insights for optimizing MC systems through energy-efficient molecule transfer techniques. © 2015 IEEE.

关键词： Transmitters

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Content Analysis of Twitter Conversations Associated with Turkey–Syria Earthquakes

Content Analysis of Twitter Conversations Associated with ...

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International Conference on Data Analytics and Management, ICDAM 2023

作者： Kaur, Harkiran Kumar, Harishankar Singla, Abhinandan Department of Computer Science and Engineering Thapar Institute of Engineering and Technology Punjab Patiala147001 India

ISBN: (纸本)9789819965434

This research study performs content analysis of Twitter discussions associated with the earthquakes that occurred in Turkey and Syria in 2023. The authors investigated the main themes and topics of the discussions, expressed in the tweets. A dataset of tweets related to this topic has been collected using relevant hashtags and keywords. The obtained data has been analyzed using both manual and automated state-of-the-art methods. As the main findings of this study it has been observed that the most common themes in the tweets were expressions of sympathy and solidarity, calls for help and financial support, and news updates about the earthquakes. As per this proposed study, Twitter offers a worthwhile forum for people to express their state of mind and responses to natural catastrophes and may be used to segment information and assembly assistance in the times of need. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data Analytics

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Weighted Average Ensembled Probability Pipeline of Pre-trained CNN Models for Hand Gesture Classification 15

Weighted Average Ensembled Probability Pipeline of Pre-train...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Gunti, Rahul Rohan Reddy, B. Swathi, Gunti Sharath Kumar Reddy, G. Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai601103 India Vellore Institute of Technology School of Computer Science and Engineering Vellore India

ISBN: (纸本)9798350370249

The automatic detection of sign language from hand gesture images is fundamental for effective human-computer interaction, especially for individuals with hearing and speech disorders. Achieving accurate detection and classification of sign language gestures is paramount. However, accurately recognizing these gestures frequently presents challenges due to dull backgrounds, variations in gesture orientation, and fluctuations in lighting conditions. Previous approaches tried to overcome these challenges but still the model performance lacks recognition accuracy and visual quality. To address this need for accuracy, we proposed a Weighted Average Ensembled Probability Pipeline composed of EfficientNetB7, ResNet-50, and Xception models. Leveraging the Extensive Hand Gesture Recognition Database (HGRD), comprising 20,000 images, our individual models achieved notable accuracies: 96.498 % for EfficientNetB7, 93.2 % for ResNet-50, and 90.175 % for Xception. Through ensemble learning, we integrate these models to attain an impressive overall accuracy of 98.95 %. This research contributes to robust gesture recognition system and underscores the significance of ensemble techniques in enhancing performance for Gesture recognition systems. © 2024 IEEE.

关键词： Gesture recognition

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Pandemic Analysis and Prediction of COVID-19 Using Gaussian Doubling Times

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computers, Materials & Continua 2022年第7期72卷 833-849页

作者： Saleh Albahli Farman Hassan Ali Javed Aun Irtaza Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of Computer Science and Engineering Oakland UniversityMIUSA Department of Computer and Electrical Engineering University of MichiganDearbornUSA

COVID-19 has become a pandemic,with cases all over the world,with widespread disruption in some countries,such as Italy,US,India,South Korea,and *** and reliable detection of COVID-19 is mandatory to control the spread of ***,prediction of COVID-19 spread in near future is also crucial to better plan for the disease *** this purpose,we proposed a robust framework for the analysis,prediction,and detection of *** make reliable estimates on key pandemic parameters and make predictions on the point of inflection and possible washout time for various countries around the *** estimates,analysis and predictions are based on the data gathered fromJohns Hopkins Center during the time span of April 21 to June 27,*** use the normal distribution for simple and quick predictions of the coronavirus pandemic model and estimate the parameters of Gaussian curves using the least square parameter curve fitting for several countries in different *** predictions rely on the possible outcomes of Gaussian time evolution with the central limit theorem of statistics the predictions to be well *** parameters of Gaussian distribution,i.e.,maximumtime and width,are determined through a statisticalχ^(2)-fit for the purpose of doubling times after April 21,*** COVID-19 detection,we proposed a novel method based on the Histogram of Oriented Gradients(HOG)and CNN in multi-class classification scenario i.e.,Normal,COVID-19,viral pneumonia *** results show the effectiveness of our framework for reliable prediction and detection of COVID-19.

关键词： Prediction coronavirus time-series prediction gaussian mathematical model pandemic spreading

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Enhancing Cheque Security: Forgery Detection Via Signature Recognition Using Optical Character Recognition and Deep Learning

Enhancing Cheque Security: Forgery Detection Via Signature R...

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2024 IEEE International Conference on Recent Advances in science and engineering technology, ICRASET 2024

作者： Vidhya, S.G. Balarengadurai, C. Prasad, Boddu Ravi Vidyavardhaka College of Engineering Vtu Department of Computer Science & Engineering Mysuru India Marri Laxman Reddy Institute of Technology and Management Department of Computer Science & Engineering Hyderabad India

ISBN: (纸本)9798350388602

Trustworthy verification of bank checks is crucial for modern financial transaction security and the prevention of fraudulent activities. A novel approach to the authentication and categorization of bank check signatures is introduced in this study. It employs a comprehensive architecture that integrates CNN, line sweep algorithms, and optical character recognition (OCR). The proposed method aims to improve the accuracy and efficacy of signature verification processes by harnessing the potential of state-of-the-art technology. First, the system uses optical character recognition to extract text from images of checks;this allows it to recognize crucial components including account data and text-based attributes. The line sweep method to spatial connections within images of checks also helps to emphasize key features like account numbers and signatures. The technique relies heavily on Convolutional Neural Networks. The system is able to differentiate between authentic and false samples based on their distinct patterns and characteristics by training convolutional neural networks (CNNs) using a big collection of signatures. With this wealth of information at its disposal, the system can confidently assess the signatures' authenticity, resulting in a more robust and accurate verification procedure. Next, they came up with an innovative way to identify signatures and validate bank checks using convolutional neural networks (CNNs), optical character recognition (OCR), and line sweep analysis. With the automation and improvement of verification procedures, monetary transactions will be more trustworthy, less prone to errors, and more secure. © 2024 IEEE.

关键词： Convolution

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Gaining Technological Autonomy and Social-emotional Support: A Case Study of How and Why Chinese Older Adults Engage with a Semi-acquaintance Online Community

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Proceedings of the ACM on Human-computer Interaction 2024年第CSCW2期8卷 1-35页

作者： Qian, Zhigu Fu, Jiaojiao Zhou, Yangfan School of Computer Science Fudan University Shanghai Key Laboratory of Intelligent Information Processing Shanghai China School of Information Science and Engineering East China University of Science and Technology Shanghai China

Older adults are often underserved and marginalized in technology engagement due to their reluctance and the barriers they face in adopting and engaging with mainstream technology. However, Pinxiaoquan, a social feature of an e-commerce platform in China, has gained a large number of older users. This work investigates how and why Chinese older adults use Pinxiaoquan, aiming to unveil the underlying logic and inspire technology-inclusive design for older adults. To this end, we conducted a mixed-methods qualitative study over two years, which included online observation, and semi-interview. We found that Pinxiaoquan’s success among Chinese older adults is mainly due to its ability to inspire technological autonomy and provide social-emotional support. Rather than simply lowering technical barriers or asking them to seek assistance outside the platform, Pinxiaoquan builds a semi-acquaintance online community based on location and social ties that allows older adults to realize technical support mutually. Pinxiaoquan also fulfills their social-emotional needs, such as free online expression, memory creation and preservation, relationship expansion and maintenance, and a sense of value. Our research contributes to the HCI community by highlighting the importance of improving older adults’ technology autonomy following their specific social and cultural background and social-emotional needs. This work also provides unique insights and implications for building inclusive technology for the growing aging population. © 2024 Copyright held by the owner/author(s).

关键词： Marketplaces

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Improvement of Prior Image for Metal Artifact Reduction of Computed Tomography

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Journal of Shanghai Jiaotong University (science) 2025年第3期30卷 446-451页

作者： Sun, Wenwu Zhuang, Tiange Chen, Siping School of Computer Science and Engineering Hunan University of Science and Technology Hunan Xiangtan411201 China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Biomedical Engineering Shenzhen University Guangdong Shenzhen518060 China

It is not easy to reduce the metal artifacts of computed tomography images. However, the pixel values inside the metal artifact regions vary smoothly, while those on the borders of the metal and the bone regions vary sharply. When the Canny operation by adaptive thresholding is conducted on the raw image, the almost continuous edges can be formed obviously on the borders of the metal and the bone regions, but this kind of information cannot be formed for the metal artifact regions. In this paper, by searching the closed areas formed by the border edges of the bone regions in the Canny image, the metal artifact regions, which are very difficult to discriminate only by intensity thresholding, can be excluded effectively. A novel prior image-based method is thus developed for metal artifact reduction. The experiments demonstrate that the proposed method can be realized easily and reduce the metal artifacts effectively even if multiple large metal objects exist simultaneously in the image. The method is suitable for the clinical application. © Shanghai Jiao Tong University 2023.

关键词： computerized tomography

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Dual-band and high-isolation shared-aperture antenna for broadband airborne applications

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Journal of Electronic science and technology 2024年第4期22卷 9-18页

作者： Yuan Zhang Dong-Jun Wang Chuan Wu Qiang-Ming Cai Run-Ren Zhang Rong-Qiang Li Peng Gao Yan-Wen Zhao School of Electronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China AVIC Chengdu Aircraft Industrial(Group)Co. Ltd.Chengdu610091China Electronic Engineering College Chengdu University of Information TechnologyChengdu610225China School of Information Engineering Southwest University of Science and TechnologyMianyang621010China Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA

A dual-band and high-isolation shared-aperture antenna for unmanned aerial vehicle(UAV)platforms has been *** shared-aperture antenna consists of a rectangular monopole antenna and a 4-element multiple input multiple output(MIMO)*** order to increase the isolation,several double split ring metamaterial(MTM)structures are introduced between antenna *** antenna radiator and the MTM structure are located on the front and back of the same dielectric substrate,respectively,and are perpendicular to a circular metal *** overall size of the antenna substrate is 124 mm×38 mm×1.016 ***,the antenna prototype is constructed and measured,and the simulated and measured results are in good *** measured results show that the-10 dB bandwidth of the monopole antenna is 1.92 GHz to 2.75 GHz,and the common-6.0 dB bandwidth of the MIMO antenna element is 4.75 GHz to 4.91 GHz,covering 2.2 GHz to 2.4 GHz in the S-band and 4.8 GHz to 4.9 GHz in the 5G band,*** the 5G band,the isolation between any element of the MIMO antenna and the S-band monopole antenna is not less than 21 dB,and the isolation between the MIMO antenna elements is better than 23 dB,indicating t-hat the isolation between the antenna elements is *** proposed antenna is suitable for the application on UAV airborne platforms.

关键词： Dual-band antenna High-isolation Monopole antenna Multiple input multiple output(MIMO) Shared-aperture Unmanned aerial vehicle(UAV)

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