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computer Vision Approaches for Automated Bee Counting Application

IFAC-PapersOnLine 2024年第9期58卷 43-48页

作者： Simon Bilik Ilona Janakova Adam Ligocki Dominik Ficek Karel Horak Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic and Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Lappeenranta Finland Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic

Many application from the bee colony health state monitoring could be efficiently solved using a computer vision techniques. One of such challenges is an efficient way for counting the number of incoming and outcoming bees, which could be used to further analyse many trends, such as the bee colony health state, blooming periods, or for investigating the effects of agricultural spraying. In this paper, we compare three methods for the automated bee counting over two own datasets. The best performing method is based on the ResNet-50 convolutional neural network classifier, which achieved accuracy of 87% over the BUT1 dataset and the accuracy of 93% over the BUT2 dataset.

关键词： Signal Processing Biomedical systems bee counting bee traffic monitoring computer vision deep classification object detection

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MAVEN: Multi-modal Attention for Valence-Arousal Emotion Network

arXiv

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arXiv 2025年

作者： Ahire, Vrushank Shah, Kunal Khan, Mudasir Nazir Pakhale, Nikhil Sookha, Lownish Rai Ganaie, M.A. Dhall, Abhinav Department of Computer Science and Engineering Indian Institute of Technology Punjab Ropar India Faculty of Information Technology Monash University Melbourne Australia

—This paper introduces MAVEN (Multi-modal Attention for Valence-Arousal Emotion Network), a novel architecture for dynamic emotion recognition through dimensional modeling of affect. The model uniquely integrates visual, audio, and textual modalities via a bi-directional cross-modal attention mechanism with six distinct attention pathways, enabling comprehensive interactions between all modality pairs. Our proposed approach employs modality-specific encoders to extract rich feature representations from synchronized video frames, audio segments, and transcripts. The architecture’s novelty lies in its cross-modal enhancement strategy, where each modality representation is refined through weighted attention from other modalities, followed by self-attention refinement through modality-specific encoders. Rather than directly predicting valence-arousal values, MAVEN predicts emotions in a polar coordinate form, aligning with psychological models of the emotion circumplex. Experimental evaluation on the Aff-Wild2 dataset demonstrates the effectiveness of our approach, with performance measured using Concordance Correlation Coefficient (CCC). The multistage architecture demonstrates superior ability to capture the complex, nuanced nature of emotional expressions in conversational videos, advancing the state-of-the-art (SOTA) in continuous emotion recognition in-the-wild. Code can be found at: https://***/Vrushank-Ahire/MAVEN_8th_ABAW. © 2025, CC BY.

关键词： Emotion Recognition

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Voice Enabled Intelligent Programming Assistant 4

Voice Enabled Intelligent Programming Assistant

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Wataketiya, Ravindu Chandrasiri, Navinda Kithsiri, Ramesh Malwatta, Hirush Nadeeshani, Madhuka Siriwardana, Samanthi Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

In modern era where software development is of vital importance, software developers are challenged with conditions like Repetitive Strain Injury (RSI) which hinders their ability to work effectively. Furthermore, people with difficulties with using their hands also find it challenging to program in the traditional manner. As a solution, coding with one's voice has been experimented with, but current solutions lack interactivity and are harder to use and setup leaving much room for improvement in this domain. In this research work, by using input classifier models with accuracies over 90%, intent classifiers with accuracies over 70%, code parsing and various human computer interaction techniques, we developed a conversationally interactive, programming language agnostic, easy to setup and easy to use Voice Coding Assistant. This will potentially help a global audience of programmers to achieve their goals and improve productivity and lead a healthier life. We have named the system thus developed, "Venic". © 2022 IEEE.

关键词： Human computer interaction

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Comparative Analysis of Machine Learning Techniques for Arabic Text Classification Using the SANAD Dataset 11

Comparative Analysis of Machine Learning Techniques for Arab...

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11th International Conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Attar, Hani Sharrab, Yousef Smadi, Saja Jbaily, Safa Zarqa University Faculty of Engineering Zarqa Jordan University of Business and Technology College of Engineering Jeddah21448 Saudi Arabia Isra University Department of Data Science and Artificial Intelligence Amman Jordan Yarmouk University Dept. Computer Science Irbid Jordan

ISBN: (纸本)9798331509293

Applying Machine Learning (ML) models for Arabic text classification is a growing research field that has recently raised a large number of research. Generally, classifying text involves selecting a category based on its content from a list of pre-established categories. Data classification is among the most popular Natural Language Processing (NLP) activities. Moreover, automatic article classifications, such as the Single-label Arabic News Articles Dataset (SANAD), are desperately needed to improve the retrieval of the requested data, which this paper investigates. The ML leverages large datasets to improve efficiency;indeed, by locating focal spots within the text, the learning mechanisms facilitate attention tools better suited for handling lengthy texts. The proposed work employs a dataset of 7,000 articles of separately classified Arab news items and then breaks them into seven categories of 1,000 news stories each: politics, education, sports, religion, culture, finance, and medicine. The investigated SANAD consists of three primary datasets from three news portals: Akhbarana, AlArabiva, and AlCtrl. Finally, to obtain trustable information, this study implements a variety of Conventional ML techniques, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN), Support Vector Machine (SVM), and Logistic Regression model to classify the investigated dataset. Our results show that the suggested solution outperformed the analytical search in the Arabic language in terms of accuracy, whereas the Logistic Regression model shows the best results among the seven utilized publicly available dataset classifications. © 2025 IEEE.

关键词： Logistic regression

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An enhanced scheme for mutual authentication for healthcare services

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Digital Communications and Networks 2022年第2期8卷 150-161页

作者： Salman Shamshad Muhammad Faizan Ayub Khalid Mahmood Saru Kumari Shehzad Ashraf Chaudhry Chien-Ming Chen Department of Computer Science COMSATS University IslamabadSahiwal Campus57000Pakistan Department of Mathematics Ch.Charan Singh UniversityMeerutUttar Pradesh250004India Department of Computer Engineering Faculty of Engineering and ArchitectureIstanbul Gelisim UniversityIstanbulTurkey College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China Riphah School of Computing&Innovation(RSCI) Riphah International UniversityLahore CampusLahore 55150Pakistan Department of Mathematics University of Padua35131 PaduaItaly

With the advent of state-of-art technologies,the Telecare Medicine Information System(TMIS)now offers fast and convenient healthcare services to patients at their ***,this architecture engenders new risks and challenges to patients'and the server's confidentiality,integrity and *** order to avoid any resource abuse and malicious attack,employing an authentication scheme is widely considered as the most effective approach for the TMIS to verify the legitimacy of patients and the ***,several authentication protocols have been proposed to this *** recently,Chaudhry et *** that there are vulnerabilities of impersonation attacks in Islam et al.'s ***,they introduced an improved protocol to mitigate those security ***,Qiu et *** that these schemes are vulnerable to the man-in-the-middle,impersonation and offline password guessing ***,they introduced an improved scheme based on the fuzzy verifier techniques,which overcome all the security flaws of Chaudhry et al.'s ***,there are still some security flaws in Qiu et al.'s *** this article,we prove that Qiu et al.'s protocol has an incorrect notion of perfect user anonymity and is vulnerable to user impersonation ***,we introduce an improved protocol for authentication,which reduces all the security flaws of Qiu et al.'s *** also make a comparison of our protocol with related protocols,which shows that our introduced protocol is more secure and efficient than previous protocols.

关键词： Authentication protocol Security protocol Anonymous protocol Impersonation attack TMIS

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Mars crater detection based on Yolo structure using TIR data

Mars crater detection based on Yolo structure using TIR data

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2022 IEEE International Conference on Artificial Intelligence and computer Applications, ICAICA 2022

作者： Li, Mingyang Liang, Jiarui Yan, Pengcheng Tian, Xiaolin Macau University of Science and Technology School of Computer Science and Engineering Faculty of Innovation Engineering China Lunar and Planetary Science Laboratory Space Science Institute Macau University of Science and Technology China

ISBN: (数字)9781665499910

ISBN: (纸本)9781665499910

This article aims to detect Mars craters for the geological research and planetary research. The main method is to use deep learning method to identify craters on Mars using Mars TIR images. YOLOv5 is chosen as the basic neural network in this method. To improve the efficiency, the author chose a system that can automatically generate training dataset for YOLO, and the results shows that it is feasible to use neural network to identify the Mars craters. © 2022 IEEE.

关键词： Deep learning

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Penetration Testing: A Cost-Benefit Analysis of Best Practices Implementation for Software Startups

Penetration Testing: A Cost-Benefit Analysis of Best Practic...

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Novel Intelligent and Leading Emerging Sciences Conference (NILES)

作者： Ahmed Ali Gaafar Khaled M. Fouad Mohamed A. Sadek Faculty of Information Technology and Computer Science Nile University Cairo Egypt Faculty of Computers and Artificial Intelligence Benha University Faculty of Computer Science and Engineering New Mansoura University Nile University

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378528

Despite software startups often not handlingsensitive data, the implementation of robust security measures is crucial to mitigate significant financial and reputational risks. This study investigates the cost-benefit analysis of implementing best practices in penetration testing (Pentest) versus notimplementing them, using Roboost as a case study. It emphasizes that proactive security investments not only protect current assets but also prepare organizations for future growthThe research employs a mixed-methods approach, combining quantitative analysis of financial data with qualitative insights from stakeholder interviews. The findings indicate that while the initial costs of hiring penetration testers and implementing security protocols are substantial, the benefits far outweigh these expenses. Securing new clients and retaining existing ones, which constitute a significant portion of Roboost’ s revenue, underscores the financial prudence of these investments. Our analysis demonstrates that the costs of not implementing security practices, such as potential losses from security breaches, are substantially higher than the investments in proactive measures. This underscores the critical importance of embedding security best practices within organizational frameworks to ensure long-term sustainability and success.

关键词： Statistical analysis Current measurement Software Loss measurement Security Cost benefit analysis Sustainable development Best practices Investment Penetration testing

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Detecting Retinal Nerve Fiber Layer Using Gray Level Co-occurrence Matrix and Machine Learning Approach

Detecting Retinal Nerve Fiber Layer Using Gray Level Co-occu...

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2022 International Conference on Information technology Research and Innovation, ICITRI 2022

作者： Septiarini, Anindita Hamdani, Hamdani Setyaningsih, Emy Maharani, Septya Munir, Aam Shodiqul Winarno, Edy Mulawarman University Faculty of Engineering Department of Informatics Samarinda Indonesia Institut Sains Teknologi AKPRIND Department of Computer System Engineering Yogyakarta Indonesia Universitas Stikubank Faculty of Information Technology Semarang Indonesia

ISBN: (数字)9781665461849

ISBN: (纸本)9781665461849

The retinal nerve fiber layer (RNFL) is the white scratch part in the fundus image. It could be an indicator of several diseases characterized by depletion of RNFL. This study intends to construct an RNFL method using Gray Level Cooccurrence Matrix (GLCM) as texture features and implementing random forest as the classifier. The approach has four primary steps: defining the region of interest (ROI), forming the area of features extraction, pre-processing, feature extraction, and classification. Forming the ROI was applied through two main steps: The segmentation with K-means clustering and dividing the fundus image into 12 sub-sectors. The image was then turned into a grayscale as part of the pre-processing. Afterward, the features were extracted using GLCM, followed by features reduction with Correlation-based Feature Selection (CFS). The last step was to use the artificial neural network (ANN) method to classify the data. In this study, the RNFL detection method achieved the accuracy value of 96.7% against the dataset consisting of 40 images. © 2022 IEEE.

关键词： Neural networks

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A Review on the Role of Microrobots and Nanorobots Used in Healthcare Domain

A Review on the Role of Microrobots and Nanorobots Used in H...

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engineering and technology (PICET), Parul International Conference on

作者： Shravan Kumar Praveen Kumar Rajan Kumar Mukesh Kumar Dhiraj Kumar Gulshan Kumar Department of Computer Science and Design Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Wardha Maharashtra India Department of Computer Science and Medical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Wardha Maharashtra India

ISBN: (数字)9798350369748

ISBN: (纸本)9798350369755

Advanced technology such as microrobots and nanorobots have the potential to completely transform the healthcare industry. These tiny robotic devices provide fine control for a range of biological applications since they operate at the micro and nanoscales. This review explores the various healthcare uses, fabrication ideas, and design concepts of microrobots and nanorobots. It specifically looks at their works in tissue engineering, minimally invasive surgery, and targeted drug administration. Aiming to harness the transformative impact of these emerging technologies in healthcare, research and practitioners can recive significant insights from the discussion of challenges and future directions in the sector. Design-wise, microrobots and nanorobots display a range of configurations suited to particular uses, such as payload delivery systems, sensing capabilities, and propulsion mechanisms.

关键词： Fabrication Minimally invasive surgery Reviews Service robots Tissue engineering Medical services Transforms Nanoscale devices Nanobioscience Standards

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Innovative Investigation of the Resilience of EV Charging Infrastructure Under Cyber-Physical Threats Based on a Real-Time Co-Simulation Testbed

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IET Cyber-Physical Systems: Theory and Applications 2025年第1期10卷

作者： Alasali, Feras Ghalyon, Salah Abu El-Naily, Naser Abuashour, Mohammed I. AlMajali, Anas Itradat, Awni Holderbaum, William Department of Electrical Engineering Faculty of Engineering The Hashemite University Zarqa Jordan Department of Computer Engineering Faculty of Engineering The Hashemite University Zarqa Jordan College of Electrical and Electronics Technology Benghazi Libya Department of Computer Science and Engineering American University of Sharjah Sharjah United Arab Emirates School of Science Engineering & Environment University of Salford Salford United Kingdom

The rapid expansion of electric vehicle (EV) charging infrastructure has introduced significant vulnerabilities to cyber-physical threats, raising concerns about the resilience of both charging and smart power grid systems. This paper presents an innovative investigation into the resilience of EV charging infrastructure using a real-time co-simulation testbed, integrating both power network models and communication protocols such as IEC 61850. The study addresses gaps in existing research by implementing a realistic smart grid environment that incorporates EVs, charging stations and communication networks to simulate cyber-physical interactions. Key cyber-attacks, such as remote charging station status and configuration manipulations and their impact on it, are analysed in real-time simulations. Results show that even a relatively small attack utilising an IEEE 9-bus system with two EV charging stations can severely disrupt grid stability. The paper also explores various attacks targeting EV infrastructure, including charging stations, communication protocols, and management systems. The combined effects of cyber-attacks on power consumption and current variation highlight the critical importance of ensuring that charging infrastructure can adapt to sudden changes in demand while maintaining operational integrity. © 2025 The Author(s). IET Cyber-Physical Systems: Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and technology.

关键词： Vehicle-to-grid

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