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Fingerspelling Classification for Robot Control

Fingerspelling Classification for Robot Control

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IEEE international conference on Industrial Informatics (INDIN)

作者： Kevin McCready Sonya Coleman Dermot Kerr Nazmul Siddique Emmett Kerr Yiannis Aloimonos Cornelia Fermüller School of Computing Engineering and Intelligent Systems Ulster University Londonderry Northern Ireland Department of Electronic and Mechanical Engineering Atlantic Technological University Letterkenny Ireland Institute for Advanced Computer Studies University of Maryland College Park Maryland USA

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Improvements to human-robot interaction methods could increase the ease of use of robots in manufacturing environments. Many of these environments are noisy and therefore preclude the use of audio communication between humans or in human-robot interactions. Therefore, this paper proposes using a gesture based communication system for robot control. To that end, the VGG16 and VGG19 convolutional neural network (CNN) structures are used for gesture classification along with 3 datasets of American Sign Language (ASL) fingerspelling images. The model performance is evaluated, and modifications made to their parameters to improve performance, before applying them to robot control tasks. The results show that with parameter tuning, test accuracies of up to, 100% are achievable.

关键词： Sign language Accuracy Computational modeling Robot control Human-robot interaction Convolutional neural networks Noise measurement Tuning Testing Residual neural networks

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ColorViTAN: A hybridised approach using Vision Transformers and CycleGAN to add color to greyscale images

ColorViTAN: A hybridised approach using Vision Transformers ...

引用

Intelligent Computing and Emerging Communication Technologies (ICEC), international conference on

作者： Sarah Pendhari Khushi Tripathi Bushra Attarwala Nazneen Pendhari Computer Engineering Department Thadomal Shahani Engineering College Mumbai India Department of Computer Engineering M.H. Saboo Siddik College of Engineering Mumbai India

ISBN: (数字)9798331508432

ISBN: (纸本)9798331508449

In this paper we introduce ColorViTGAN, an approach to image colorization that leverages the power of Vision Transformers (ViT) and the cyclic consistency of CycleGANs. While traditional colorization methods often struggle with semantic understanding and global consistency, our hybrid model addresses these challenges by combining the long-range dependency modelling of ViTs with the image-to-image translation capabilities of CycleGANs. Training our model is done on the diverse Places365 dataset and the CIFAR10 dataset, using the L channel of the Lab* color space as input and generating the corresponding a* and b* channels. The ViT-based generator captures intricate spatial relationships and contextual information, enabling more accurate and semantically consistent colorization. The discriminator, also ViT-based, ensures the generated colors are realistic and coherent. Our results show that ColorViTGAN outperforms state-of-the-art colorization methods in both qualitative human evaluations and quantitative metrics such as PSNR of 22.659, SSIM of 0.928 for Places365. The model shows particular strength in handling complex scenes with multiple objects and varying lighting conditions. Furthermore, the cyclic consistency loss of the CycleGAN component allows our model to learn from unpaired data, significantly expanding the potential training dataset.

关键词： Training measurement computer vision Translation Image color analysis Computational modeling Semantics Lighting Transformers Real-time systems

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Efficient Detection of Black Box Adversarial Attacks in Machine Learning systems Using Cluster-Based and Class-Based Input Patterns

Efficient Detection of Black Box Adversarial Attacks in Mach...

引用

international conference on computer Theory and Applications (ICCTA)

作者： Rghda Salah Tarek Sharaf Nada Tayel Doaa Shawky Communication and Information Engineering University of Science and Technology Zewail City Giza Egypt Software Development Program University of Science and Technology Zewail City Giza Egypt

ISBN: (数字)9798331529680

ISBN: (纸本)9798331529697

Adversarial attacks pose a significant challenge to the security and reliability of machine learning models. This paper focuses on detecting black-box adversarial attacks, where attackers operate without access to the model's internal parameters or architecture—a scenario more relevant to real-world threats than white-box settings, where such knowledge is assumed. Two novel detection methodologies are introduced: (1) a clustering-based approach that groups input data to identify anomalies and (2) a class-centric method that uses statistical properties of labeled data to compute class centers and boundaries for detecting deviations. These methods utilize thresholds derived from dynamic statistical metrics to ensure robust, efficient, and scalable *** experiments validate the effectiveness of these approaches using the Iris dataset. Results demonstrate that the clustering-based method excels in detecting adversarial samples, achieving high accuracy, while the class-based method offers a conservative alternative by minimizing false positives. Both methodologies provide practical solutions for enhancing model security, particularly in scenarios where model details are unavailable, thereby addressing the limitations of existing defense mechanisms. Future work will explore scalability and application to higher-dimensional datasets.

关键词： measurement Gradient methods Computational modeling Scalability Closed box Machine learning Robustness computer security Iris recognition Glass box

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Computing tools in a synchronization signals monitoring system for mobile communication and SMART technologies based networks

Computing tools in a synchronization signals monitoring syst...

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international computer Sciences and Information Technologies (CSIT)

作者： Valerii Koval Vitaliy Lysenko Sergey Shvorov Vyacheslav Vakas Vadym Yarmoliuk Oleksandr Osinskiy Igor Shkliarevskyi Taras Semeniv Olexander Samkov Educational and Scientific Institute of Energy Automation and Energy Saving National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Private Joint Stock Company “Kyivstar” Kyiv Ukraine Odesa Military Academy Odesa Ukraine National Academy of Sciences of Ukraine Kyiv Ukraine “Information service technologies” LTD Kyiv Ukraine National Academy of Sciences of Ukraine Institute of Electrodynamics Kyiv Ukraine

ISBN: (纸本)9798350334326

The analysis of functioning for mobile communication networks and electric energy systems of SMART technologies was carried out depending on the parameters of the synchronization signals. The justified need to create an automated computer-integrated multi-channel monitoring system that ensures the formation of synchronous signals with a given quality and increased reliability. Developed software for operational processing of monitoring data in real time using machine intelligence, both computational and artificial. The results of experimental studies of US-1588 equipment (PTP-protocol) are given.

关键词： Productivity computer network reliability Unified modeling language Mobile communication Software Real-time systems Frequency measurement

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Robust and Efficient Text-based Speech Editing using Noise Conditioning and Rectified Flow

Robust and Efficient Text-based Speech Editing using Noise C...

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international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Haowen Yin Kai Wang Hongli Yang Hao Huang Wushour Silamu School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Key Laboratory of Multi-Lingual Information Technology Urumqi China Joint International Research Laboratory of Silk Road Multilingual Cognitive Computing Urumqi China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Significant advancements have been made in text-based speech editing (TSE) for clear speech, but effectively editing the noise-contaminated speech remains a challenge. Background noise degrades the quality of generated speech, and edited speech that fails to maintain noise context consistency often sounds unnatural. We propose Reflow-TSE, a robust and efficient TSE model for noise-consistent speech editing. For noise robustness, 1) we design a noise condition module to extract frame-level noise sequences as the conditioning information, and 2) we introduce an enhanced context-conditioned prediction module that predicts masked noise sequences along with conventional duration and pitch, using these conditions to guide generation. For boosting efficiency, 3) we introduce the rectified flow model, leveraging speech context and predicted conditions to achieve high-quality editing with limited sampling steps. Experimental results show that with just two steps of sampling, Reflow-TSE achieves context-consistent noisy speech editing, a capability absent in other TSE models. Additionally, for clean speech, Reflow-TSE also matches or surpasses baseline models. Audio samples are available at https://***.

关键词： Noise Predictive models Boosting Acoustics Noise robustness Noise measurement Human voice Data mining Background noise Context modeling

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Quantum Communication based Image Transmission over Error-Prone Channels with Three-Qubit Stabilizer Code

Quantum Communication based Image Transmission over Error-Pr...

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IEEE international conference on Consumer Electronics (ICCE)

作者： Udara Jayasinghe Nimesh Pollwaththage Yasith Ganearachchi Prabhath Samarathunga Thanuj Fernando Anil Fernando Department of Computer and Information Sciences University of Strathclyde Glasgow UK

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

As quantum communication emerges as a key technology for the future, it offers promising solutions to the limitations of classical communication systems. However, quantum communication also vulnerable to various forms of channel noise, which can introduce errors during transmission. Quantum error correction methods are critical to mitigating these errors, thereby preserving the integrity and reliability of quantum communication systems. In this study, we explore the effectiveness of the three-qubit stabilizer code for transmitting images over noisy quantum channels. We conduct a comparative analysis between the three-qubit stabilizer code and 1/3 rate polar codes, assessing their performance across uncompressed images, as well as joint Photographic Experts Group (JPEG) and High-Efficiency Image Format (HEIF) images. Our findings indicate that the three-qubit stabilizer code offers significant advantages in quantum communication, achieving the Peak Signal-to-Noise Ratio (PSNR) up to infinity and the Structural Similarity Index Measure (SSIM) up to 1 for uncompressed images. For JPEG images, it achieves the PSNR up to 58.27 dB and the SSIM up to 0.9994, while for HEIF images, the PSNR reaches up to 64.72 dB and the SSIM up to 0.9999. These results highlight the three-qubit stabilizer code as a highly effective approach for enhancing the robustness of quantum communication systems.

关键词： Image quality Codes PSNR Image communication Quantum channels Noise Transform coding Noise measurement Polar codes Quantum communication

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Development of Deep Learning-Based Laser Weeding Robot

Development of Deep Learning-Based Laser Weeding Robot

引用

international conference on Computational Cybernetics (ICCC)

作者： Kien Bui Huy Thang Nguyen Van Hieu Nguyen Duc Hieu Dang Minh Vietnam Japan Univiersity Vietnam National University Hanoi Vietnam

ISBN: (数字)9798350350159

ISBN: (纸本)9798350350166

Agriculture is an important sector that contributes significantly to Vietnam's GDP. The use of pesticides and herbicides, however, raises great concern due to their harm to the environment and human health. The government is taking action to eliminate the use of these chemicals, meanwhile, alternative solutions are needed. The aim of this paper is to develop an effective solution for weed control using a computer vision-based laser weed-killing robot. To ensure efficiency and accuracy, computer vision models must be evaluated based on different metrics such as performance, speed, and computational cost represented by mean average precision, speed of inferences (in fps), and the size of the model in FLOPs and params. The study focuses on deploying the state-of-the-art object detection model YOLOv8 on a dataset of 9,000 labeled images taken from fields in Pakistan. YOLOv8 outperforms YOLOv5 in a previous study with an accuracy of 0.9043@IOU 0.5, particularly suited for hardware efficient integration due to its 'n' and ‘s’ versions. Both models in “n” version demonstrated similar real-time frame processing times, operating at an FPS rate of approximately 62.5ms using the same computer configuration. The results show that YOLOv8n is a fitting choice for the laser weedkilling robot due to its superior weed detection capabilities.

关键词： YOLO measurement Accuracy Computational modeling Government Fitting Pesticides

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Comparative Analysis of The Effective Grounding System on External LPS modeling in PV Fields

Comparative Analysis of The Effective Grounding System on Ex...

引用

international conference on Electrical, Telecommunication and computer Engineering (ELTICOM)

作者： Rohana Rohana Surya Hardi Nasaruddin Nasaruddin Yuwaldi Away Doctoral Program. School of Engineering Universitas Syiah Kuala Banda Aceh Indonesia and Universitas Muhammadiyah Sumatera Utara Indonesia Dept. of Electrical Engineering Universitas Sumatera Utara Medan Indonesia Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia

Solar energy is environmentally friendly energy and is available in large quantities. The energy produced is commonly converted into electricity by using solar panel (PV) systems for utilization. PV systems are generally located in open areas such as hillsides, deserts, and water surfaces, so they become more sensitive against lightning strikes. Commonly, the PV is equipped with a lightning protection system (LPS). This paper discusses the grounding system at the solar power center (PLTS) Weh Island, Sabang City. Evaluation and comparison under certain conditions are carried out through measurements, calculations, and simulations. The grounding system is modeled for one rod, four rods in parallel, and plate rod. The measurement process during field observations and the induce voltage simulation are carried out to get the results of the analysis calculations. The result obtained shows that the grounding system fulfills the PUIL standard, namely being smaller than $5 \Omega$. When using plate electrodes, the resistance value is greater than that of rod electrodes. So that the lower conductor can be more resistant and easier to maintain. Improving the quality of the protection system, this research is used as a reference to evaluate LPS conditions in PV fields.

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Analyzing Temporal Change in LoRa Communication Quality Using Massive measurement Data 1

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17th Pacific Rim Knowledge Acquisition Workshop, PKAW 2020 held in conjunction with the international joint conference on Artificial Intelligence - Pacific Rim international conference on Artificial Intelligence, IJCAI-PRICAI 2020

作者： Suzuki, Kazuya Takahashi, Takuya Faculty of Systems Science and Technology Akita Prefectural University Yurihonjo Akita Japan Graduate School of Systems Science and Technology Akita Prefectural University Yurihonjo Akita Japan

ISBN: (数字)9783030698867

ISBN: (纸本)9783030698850

This paper proposes a method to analyze the temporal change in the quality of LoRa communication, which is a low-power wide-area (LPWA) wireless technology for the IoT, using massive measurement data from a bus location management system. To analyze this temporal change in LoRa communication quality, many measurement data at the same position must be compared. However, buses do not always follow the same route every day. Even if buses follow the same route on different days, the measurement data are not acquired from exactly the same position. To solve these problems, we use locality-sensitive hashing (LSH) to extract comparable data from massive measurement data. Furthermore, we treat the extracted data with different distances on the same day as a series and compare regression formulas determined respectively from the plural series. As a result, it was confirmed that the received signal strength indicator (RSSI) of LoRa communication had almost no effect even in heavy rainfall of 30 mm/h. In addition, we confirmed that the radio attenuation was smaller about 2 dB than usual when there was over 7 cm of snow cover. © 2020, Springer Nature Switzerland AG.

关键词： Information management

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Research on Multi-Target Tracking Model of Data Fusion between Autonomous Driving Millimeter-Wave Radar and Visual Sensors 24

Research on Multi-Target Tracking Model of Data Fusion betwe...

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Proceedings of the 2024 4th international conference on Computational modeling, Simulation and Data Analysis

作者： Xinzhen Long Tao Lin Xingzhi Lin Faculty of Computer and Information Engineering GuangXi Vocational Normal University Nanning Guangxi China Guangxi Minzu University Nanning Guangxi China GuangXi Vocational Normal University Nanning Guangxi China

ISBN: (纸本)9798400711831

The research mainly addresses the multi-target tracking problem encountered in the data fusion process of millimeter-wave radar and visual sensors in unmanned systems. Multi-sensor data fusion models are investigated to optimize target detection performance and improve the accuracy of tracking models. The research analyzed the accuracy of the Kalman filter and the convolutional neural network, and used joint data association technology to achieve high-precision target detection, stable real-time tracking, and excellent adaptability to dynamic environments. The tracking accuracy reached 97.87% and the false detection rate was less than 2.13% through simulation experiments in a simulated driving environment. The experimental results verified that the fusion model performs excellently in complex driving scenarios, maintaining high-precision target tracking, proving that the technical methods used are feasible.

关键词： Autonomous driving

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