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CELL SEGMENTATION IN FLUORESCENCE MICROSCOPY IMAGES

CELL SEGMENTATION IN FLUORESCENCE MICROSCOPY IMAGES

引用

2024 IET International Conference on engineering Technologies and Applications, ICETA 2024

作者： Yin, Shao-Yun Hsu, Wei-Wen Hsia, Chih-Hsien Master Program of Artificial Intelligence National Ilan University Ilan Taiwan Dept. of Computer Science and Information Engineering National Taitung University Taitung Taiwan Dept. of Computer Science and Information Engineering National Ilan University Ilan Taiwan

ISBN: (纸本)9781837242672

For microscopic cells images, cells’ morphologies are widely varied among different imaging modalities and staining methods. For fluorescence microscopy images, Poisson noises present in images due to the lightening, causing photobleaching, which makes it challenging in analysis with the deep learning models. Traditionally, median filtering can be applied to the original image for denoising, however, it also results in a blurry image, which is harmful to segmentation. In this study, the Haar Wavelet Transform is used to alleviate the photobleaching problem for cell segmentation, integrated to the framework without interfering with feature extraction by the backbone model. For our experiments, instance segmentation for fluorescence-stained cells was performed based on U-Net architecture with the method of.gradient flow tracking proposed by Cellpose. And the Haar wavelet downsampling is embedded in the skip connections to verify if it can improve the segmentation performance for fluorescence images. The experimental results show that the approach of.Haar wavelet downsampling embedded in the skip connections achieve superior performance among the other settings. Compared with the performance of.the baseline model, the performance of.the proposed model reached 0.732 in F1-score, which surpassed the one of.baseline model (0.6341) by almost 0.1. © The Institution of.engineering & Technology 2024.

关键词： Fluorescence microscopy

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How to Spatial Audio with the WebXR API: a comparison of.the tools and techniques for creating immersive sonic experiences on the browser

How to Spatial Audio with the WebXR API: a comparison of the...

引用

2023 Immersive and 3D Audio: from Architecture to Automotive, I3DA 2023

作者： Tomasetti, Matteo Boem, Alberto Turchet, Luca University of Trento Dept. of Information Engineering and Computer Science Trento Italy

ISBN: (纸本)9798350311044

The WebXR Device API provides a powerful set of.functionalities that can be used for creating immersive experiences that can be accessed directly from a web browser. However, while creating a compelling visual experience is easy to implement using the WebXR API and related tools, creating the audio part of.the experience is less clear and with more open questions and possibilities. This paper presents a comparison of.six tools oriented to practitioners and used for implementing and delivering interactive spatial audio experiences in XR applications running on a browser. These tools are selected and evaluated based on their compatibility with the WebXR Device API, ease of.use, provided support and documentation, and specific features like reverberation, head-related transfer functions (HRTFs), sound scene rotation, and real-time microphone input. The paper then discusses the integration of.these spatial audio tools into WebXR applications, highlighting their potential and limitations. It also addresses the absence of.standardized spatial audio frameworks for the web. The challenges of.choosing the right tool regarding resource allocation, learning curve, and compatibility with XR systems are acknowledged. This overview aims to provide insights into the current state of.spatial audio tools for the web, making them more accessible to developers, musicians, and researchers seeking guidance on selecting suitable 3D spatial audio tools for experiences based on WebXR. © 2023 IEEE.

关键词： Audio acoustics

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An Introduction of.Explainable Artificial Intelligence to Winter Sports Performance Analysis

An Introduction of Explainable Artificial Intelligence to Wi...

引用

2023 IEEE International Workshop on Sport, Technology and Research, STAR 2023

作者： Odong, Lawrence A. Bouquet, Paolo University of Trento Dept. of Information Engineering and Computer Science Trento Italy

ISBN: (纸本)9798350316056

In recent years, the utilization of.machine learning techniques has revolutionized performance analysis in the field of.sports. However, a crucial drawback of.these algorithms is their inherent black box nature, which hinders stakeholders' ability to comprehend the underlying rationale behind their decisions. This lack of.transparency presents challenges for coaches, trainers, and athletes who heavily rely on analysis outcomes to shape their strategies and training approaches. To address this limitation, this paper introduces the concept of.Explainable Artificial Intelligence (XAI) to sports performance analysis. We employ SHAP (SHapley Additive exPlanations), a model-agnostic explainable method, to provide a clear and interpretable representation of.the contribution of.different features towards the final model prediction. Ski jumping is chosen as the initial test case to illustrate the effectiveness of.this approach. © 2023 IEEE.

关键词： Sports

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5G the Missing Piece in Digital Transformation of.the Construction Sector 28

5G the Missing Piece in Digital Transformation of the Constr...

引用

28th International computer science and engineering Conference, ICSEC 2024

作者： Chnaidini, Shaik Khan, M. Jebran Ullah, Fasee Khan, Arafat Ahmad Prashar, Deepak Gulf American University Dept. of Civil Engineering Fujairah United Arab Emirates Sarhad University of Science and Information Technology Dept of Computing and Information Technology Peshawar Pakistan Uinversiti Teknology Petronas Dept. of Computer and Information Sciences Seri Iskandar Malaysia Khonkaen University Dept. of Computer Science Khon Kaen Thailand Lovely Professional University Dept. of Computer Science and Engineering Punjab India

ISBN: (纸本)9798350366860

The 5th generation of.wireless technology with a continuum leap rushing towards the future in the world of.communication has a puzzle that enables the autonomous machine to work in site making a louder voice that shows the era where even if we cannot be fully robotic, we can make the machines do the work by sitting on a faraway control room. Making ways clear to see the work done miles away on construction sites the 5th generation has not only brought the people close through communication but also made them work collegiately with a clearer view front. The paper discusses 5G and the other related technologies that are emerging all over the world and how it is needed specifically in the construction industry. In the present paper, we tried to shed light on the acceptance and implementation of.5G technology in the construction sector. It is seen that the construction sector in India is lagging behind when it comes to implementation and availability of.required support and resources for the 5G implementation. © 2024 IEEE.

关键词： Construction industry

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Immersive networked music performance systems: identifying latency factors

Immersive networked music performance systems: identifying l...

引用

2023 Immersive and 3D Audio: from Architecture to Automotive, I3DA 2023

作者： Turchet, Luca Tomasetti, Matteo University of Trento Dept. of Information Engineering and Computer Science Trento Italy

ISBN: (纸本)9798350311044

Music playing with binaural systems has thus far received remarkably little attention by the research community. Such an activity is particularly relevant for the case of.networked music performances (NMPs), where geographically displaced musicians play together over a telecommunication network. Recent findings obtained in simulated settings have shown the preference of.musicians for spatialized listening during collaborative playing using headphones, as opposed to listening with conventional stereophonic systems. This result has highlighted the need to enhance current NMP systems with the spatial rendering of.the acoustic scene, leading to the development of.immersive networked music performance (INMP) systems. A crucial aspect that needs to be addressed is the contribution of.the spatial audio system to the overall latency of.the audio processing and transmission chain between the network nodes. In this paper, we provide an overview of.the INMP topic and identify the latency contributions of.the components of.an INMP system. We then relate such components to state-of.the-art hardware and sof.ware systems. Based on our analysis, we draw concluding remarks and discuss the open challenges for progressing the INMP field. © 2023 IEEE.

关键词： Music

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Unleashing Machine Learning for Hepatitis C Prediction: A Holistic Exploration of.Clinical Insights

Unleashing Machine Learning for Hepatitis C Prediction: A Ho...

引用

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

作者： Al-Amain Janin, Fatema Tuj Ahmed Robin, Faizul Ahmed, Shifat Mohi Uddin, Khandaker Mohammad Southeast University Dept. of Computer Science and Engineering Dhaka Bangladesh Hamburg University of Applied Sciences Dept. of Information and Electrical Engineering Hamburg Germany

ISBN: (纸本)9798331529765

Chronic diseases, characterized by long-term effects and persistent symptoms, pose significant challenges to human health and well-being. The hepatitis C virus (HCV) is the cause of.chronic hepatitis C, which affects 58 million people globally. It also causes 290,000 deaths annually due to liver cancer and cirrhosis, two conditions connected to HCV. Taking advantage of.machine learning (ML) algorithms' ability to analyze large datasets and identify patterns and relationships that aid in diagnosis, this effort focuses on employing algorithms for machine learning to identify and forecast hepatitis C precisely. Various techniques were utilized, including Random Forest, Cat Boost, SVM, and others to create predictive models using blood values from 615 patients, including both hepatitis patients and healthy blood donors. The dataset underwent comprehensive preprocessing, including handling missing values, scaling, and dimensionality reduction via Principal Component Analysis (PCA). Various ML algorithms were evaluated, and the Cat Boost classifier achieved the highest accuracy of.99.17%, recall of.92.00%, precision of.100.00% and F1-score is 96.00%. This study demonstrates the potential of.ML in enhancing HCV diagnosis, of.ering less invasive and cost-effective alternatives to traditional methods, and providing predictive insights for personalized treatment plans. The findings underscore the importance of.advanced data preprocessing and feature selection in improving model efficiency. This study adds to the ongoing efforts to lessen the prevalence of.hepatitis C worldwide, aligning with the World Health Organization's goal to significantly decrease new HCV cases and related deaths by 2030. © 2024 IEEE.

关键词： Adversarial machine learning

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Relating Muscle Activity and Mouse Sensitivity in FPS Game Players Using Surface EMG Signals 5

Relating Muscle Activity and Mouse Sensitivity in FPS Game P...

引用

5th International Conference on Biomedical engineering, IBIOMED 2024

作者： Prajapati, Vaibhav Turlapaty, Anish C. Sarma, Himangshu Ghorai, Mrinmoy Indian Institute of Information Technology Dept. of Electronics and Communication Engineering Sri City India Indian Institute of Information Technology Dept. of Computer Science and Engineering Sri City India

ISBN: (纸本)9798350389265

In the domain of.first-person shooter (FPS) gaming, mouse sensitivity is crucial for performance. This paper presents an analysis showing the correlation between specific muscle activity and mouse movement. We analyzed mouse movements from twelve subjects with varying sensitivity levels. A new dataset electromyography analysis of.human activity database 8 (EMAHA-DB8), is introduced which involved four mouse designs and two game modes: Medium (normal movement) and Hard (aggressive movement). Sensitivity settings were standardized using effective dots per inch (eDPI), calculated as Mouse DPI multiplied by in-game sensitivity. Hand muscle activity was measured using five Noraxon Ultium wireless surface electromyography (sEMG) sensors with Ag/AgCl electrodes. Various regression models, including Random Forest, Support Vector Regressor, K-Nearest Neighbors Regressor, MLP Regressor, and Gradient Boost Regressor, were used to predict eDPI from muscle movement patterns. Sequential feature selection identified the top ten features, highlighting the most significant muscles for predicting sensitivity. The results demonstrate that the Extensor Carpi Radialis (ECR) is the most active muscle, followed by the Extensor Digitorum (ED), while playing the chosen FPS game. These findings give insights for ergonomic and personalized equipment design to enhance gaming experience and performance. © 2024 IEEE.

关键词： Decision trees

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Detecting adversarial examples using constraint-based learning

Detecting adversarial examples using constraint-based learni...

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Kumar, Vivek Kumar, Kamal Singh, Maheep National Institute of Technology Dept. of Computer Science -and Engineering Uttarakhand Pauri India IGDTUW Department of Information Technology New Delhi India Doon University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350394412

Deep learning models have been applied in various fields and continue producing exceptional results. However, these models are vulnerable to adversarial attacks, which are modified data samples maliciously crafted to cause misclassification by a target model. Fields like Network intrusion detection systems (NIDS) are security-critical;therefore, adversarial attacks pose a high risk in such applications. The attacker not only aims for evasion but also tries to launch an attack once the adversarial example has evaded detection by a NIDS. This paper presents a novel technique for detecting adversarial examples targeted towards a NIDS by learning the dependencies between features known as domain constraints. Our proposed method detects adversarial examples that violate these constraints learned during training. Compared with prevalent detection techniques, our method does not require generating adversarial examples for training, which reduces its computational requirement. We assume a grey-box threat model where the attacker can access the training data. We perform experiments on the CICIDS2017 dataset against five state-of.the-art adversarial attacks: FGSM, BIM, PGD, Deep fool and BIM. The results show that our method can detect up to 100% adversarial attacks, outperforming the contemporary schemes. © 2024 IEEE.

关键词： Adversarial machine learning

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Advancements in Distributed Deep Learning: Federated Learning, AutoML Integration, and Beyond

Advancements in Distributed Deep Learning: Federated Learnin...

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2024 IEEE International Conference on Innovation and Novelty in engineering and Technology, INNOVA 2024

作者： Kavitha, T. Manikandan, S.P. Patil, Bhimaraya Patil, Anita Dept. of Computer Science and Engineering New Horizon College of Engineering Bangalore India CMR University Bengaluru India Dept. of Computer Science Engineering New Horizon College of Engg. Bangalore India Dept. of Information Science and Engg. City Engineering College Bengaluru India

ISBN: (纸本)9798331505134

This paper present advancements in distributed deep learning, focusing on federated learning, AutoML integration, and beyond. Leveraging the latest developments in machine learning (ML) and artificial intelligence (AI), our research explores novel approaches to enhance the efficiency, scalability, and security of.distributed deep learning systems. This paper introduces federated learning techniques to enable collaborative model training across decentralized edge devices, thereby minimizing data privacy concerns and reducing communication overhead. Additionally, Proposed work investigate the integration of.automated machine learning (AutoML) capabilities into distributed training pipelines, streamlining the model selection and hyperparameter tuning processes. Furthermore, Paper also explores cutting-edge advancements beyond traditional deep learning paradigms, such as generative adversarial networks (GANs) and reinforcement learning (RL), to unlock new opportunities in distributed AI. Through experimental evaluations and case studies, Paper demonstrate the effectiveness and potential impact of.our proposed advancements, paving the way for future breakthroughs in distributed deep learning research. © 2024 IEEE.

关键词： Federated learning

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Smart Waste Management System Using IoT

Smart Waste Management System Using IoT

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2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Dhar, Mainak Roy, Alak Mandal, Purnendu Icfai University Dept. of Computer Science and Engineering Tripura Agartala India Tripura University Dept. of Information Technology Agartala India

ISBN: (纸本)9798331540821

It is thereby noticed that the rapid rate of.urbanization has increased the quantum of.waste generation manifold, which imposes significant challenges in waste management for traditional systems. In this paper, a Smart Waste Management System (SWMS) is proposed at a time when Internet of.Things (IoT) and Artificial Intelligence (AI) technologies are about to reach the mainstream. The SWMS will reduce operations costs and its impact on the environment with its architecture, which provides real-time monitoring, data analytics, and intelligent decision-making methods to enhance efficiency. The IoT part of.SWMS involves setting up sensor nodes in the waste bins to observe fill levels and other environmental parameters. The sensors transmit the data without wires to a central cloud platform for storage and analysis. AI algorithms on the cloud process this information to produce optimized disposal schedules, fill-level predictions, and anomaly detection, like fires or spills. Moreover, by using techniques of.machine learning, system performance will be improved further by available historical data and real-time feedback. © 2024 IEEE.

关键词： Decision making

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