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IEEE World Symposium on Communication engineering (WSCE)

作者： Vasileios Christofas Petros Amanatidis Dimitris Karampatzakis Thomas Lagkas Sotirios K. Goudos Konstantinos E. Psannis Panagiotis Sarigiannidis Department of Computer Science International Hellenic University Kavala Greece Department of Physics Aristotle University of Thessaloniki Thessaloniki Greece Department of Applied Informatics University of Macedonia Thessaloniki Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece

Embedded AI development has been rapidly im-proving for the past few years and has had a great impact on edge AI networks. However, as neural networks become deeper and deeper it becomes more difficult to execute complicated tasks without sacrificing a good amount of power and performance. In this paper, we make a comparative evaluation between two AI acceleration devices. The first one features a RISC- V 64-bit processor while the other one is ARM powered. These devices are combined with AI co-processors, or ASICs, with computer vision capabilities. Our benchmark consists of a simple classification task split into multiple versions. The results showed that the RISC- V inference machine had 4 times lower consumption while the ARM machine was up to 15 times faster in our largest network. We discuss the results in great detail while keeping our focus on all aspects equally. Finally, we make recommendations based on their usage and application.

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Affine-invariant diffusion geometry for the analysis of deformable 3D shapes

Affine-invariant diffusion geometry for the analysis of defo...

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IEEE Conference on computer Vision and Pattern Recognition

作者： Dan Raviv Michael M. Bronstein Alexander M. Bronstein Ron Kimmel Nir Sochen Dept. of Computer Science Technion Dept. of Informatics Universita della Svizzera Italiana Dept. of Electrical Engineering Tel Aviv University Dept. of Applied Mathematics Tel Aviv University

ISBN: (纸本)9781457703942

We introduce an (equi-)affine invariant diffusion geometry by which surfaces that go through squeeze and shear transformations can still be properly analyzed. The definition of an affine invariant metric enables us to construct an invariant Laplacian from which local and global geometric structures are extracted. Applications of the proposed framework demonstrate its power in generalizing and enriching the existing set of tools for shape analysis.

关键词： Invariant Tool Sets geometry shape analysis diffusion geometrical construction Laplacian operator Energy sources

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RoboMNIST: A Multimodal Dataset for Multi-Robot Activity Recognition Using WiFi Sensing, Video, and Audio

arXiv

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arXiv 2024年

作者： Behzad, Kian Zandi, Rojin Motamedi, Elaheh Salehinejad, Hojjat Siami, Milad Department of Electrical & Computer Engineering Northeastern University BostonMA United States Kern Center for the Science of Health Care Delivery Department of Artificial Intelligence and Informatics Mayo Clinic RochesterMN United States

We introduce a novel dataset for multi-robot activity recognition (MRAR) using two robotic arms integrating WiFi channel state information (CSI), video, and audio data. This multimodal dataset utilizes signals of opportunity, leveraging existing WiFi infrastructure to provide detailed indoor environmental sensing without additional sensor deployment. Data were collected using two Franka Emika robotic arms, complemented by three cameras, three WiFi sniffers to collect CSI, and three microphones capturing distinct yet complementary audio data streams. The combination of CSI, visual, and auditory data can enhance robustness and accuracy in MRAR. This comprehensive dataset enables a holistic understanding of robotic environments, facilitating advanced autonomous operations that mimic human-like perception and interaction. By repurposing ubiquitous WiFi signals for environmental sensing, this dataset offers significant potential aiming to advance robotic perception and autonomous systems. It provides a valuable resource for developing sophisticated decision-making and adaptive capabilities in dynamic environments. © 2024, CC BY.

关键词： Wi-Fi

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Nondestructive Chicken Egg Fertility Detection Using CNN-Transfer Learning Algorithms

arXiv

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arXiv 2023年

作者： Saifullah, Shoffan Drezewski, Rafal Yudhana, Anton Pranolo, Andri Kaswijanti, Wilis Suryotomo, Andiko Putro Putra, Seno Aji Khaliduzzaman, Alin Prabuwono, Anton Satria Japkowicz, Nathalie Institute of Computer Science AGH University of Krakow Krakow30-059 Poland Department of Informatics Universitas Pembangunan Nasional Veteran Yogyakarta Yogyakarta55281 Indonesia Center of Knowledge Engineering and Data Science Department of Electrical Engineering and Informatics Universitas Negeri Malang Malang65145 Indonesia Department of Electrical Engineering Universitas Ahmad Dahlan Yogyakarta55191 Indonesia College of Computer and Information Hohai University Nanjing211100 China Department of Informatics Faculty of Industrial Technology Universitas Ahmad Dahlan Yogyakarta55166 Indonesia Faculty of Agricultural Engineering and Technology Sylhet Agricultural University Sylhet3100 Bangladesh Faculty of Computing and Information Technology in Rabigh King Abdulaziz University Jeddah21589 Saudi Arabia Department of Computer Science American University WashingtonDC20016 United States

This study explored the application of CNN-Transfer Learning for nondestructive chicken egg fertility detection for precise poultry hatchery practices. Four models, VGG16, ResNet50, InceptionNet, and MobileNet, were trained and evaluated on a dataset (200 single egg images) using augmented images (rotation, flip, scale, translation, and reflection). The training results demonstrated that all models achieved high accuracy, indicating their ability to learn and classify chicken eggs’ fertility. However, variations in accuracy and performance were observed when these models were evaluated on the testing datasets. The InceptionNet exhibited the best overall performance, accurately classifying fertile and non-fertile eggs. It demonstrated excellent performance in all parameters of the evaluation metrics for both training and testing datasets. When evaluated on the testing datasets, it achieved an accuracy of 0.98, a sensitivity of 1 for detecting fertile eggs, and a specificity of 0.96 for identifying non-fertile eggs. The higher performance is attributed to its unique architecture, efficiently capturing features at different scales, which leads to improved accuracy and robustness. Further optimization and fine-tuning of the models might be necessary to address the limitations in accurately detecting fertile and non-fertile eggs using other models. This study highlighted the potential of CNN-transfer learning for nondestructive fertility detection and emphasized the need for further research to enhance the models’ capabilities and to ensure accurate *** Codes CS-Class: 68T07, 68T45, 68U10, ICT-Class: 94A08 © 2023, CC BY-SA.

关键词： Image classification

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On Concept Algebra and Knowledge Representation

On Concept Algebra and Knowledge Representation

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Firth IEEE International Conference on Cognitive informatics(第五届认知信息国际会议)

作者： Yingxu Wang International Center for Cognitive Informatics (ICfCI) Dept of Electrical and Computer Engineering University of Calgary 2300 University Drive NW Calgary Alberta Canada T2N 1N4

ISBN: (纸本)9781424404759

A concept is a basic unit of cognition that carries certain meanings. In cognitive informatics, a concept is formally modeled as an abstract and dynamic mathematical structure that encapsulates attributes, objects, and relations. The most important feature of an abstract concept is its networking capability, or the adaptive capability to interrelate itself to other concepts. This paper presents a formal theory for abstract concepts and knowledge manipulation known as concept algebra. The mathematical models of concepts and knowledge are developed based on the object-attribute-relation (OAR) theory. The formal methodology for manipulating knowledge as a concept network is described. Case studies demonstrate that the concept network and concept algebra provide a generic and formal knowledge manipulation means that are capable to deal with complex knowledge structures and their algebraic operations.

关键词： Cognitive informatics natural intelligence mathematics concept knowledge concept algebra knowledge network the OAR model and case studies.

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Doppler radar sensor positioning in a fall detection system

Doppler radar sensor positioning in a fall detection system

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Liang Liu Mihail Popescu K. C. Ho Marjorie Skubic Marilyn Rantz Electrical and Computer Engineering Department University of Missouri Columbia MO USA Health Management and informatics Department University of Missouri Columbia MO USA Inclair School of Nursing University of Missouri Columbia MO USA

Falling is a common health problem for more than a third of the United States population over 65. We are currently developing a Doppler radar based fall detection system that already has showed promising results. In this paper, we study the sensor positioning in the environment with respect to the subject. We investigate three sensor positions, floor, wall and ceiling of the room, in two experimental configurations. Within each system configuration, subjects performed falls towards or across the radar sensors. We collected 90 falls and 341 non falls for the first configuration and 126 falls and 817 non falls for the second one. Radar signature classification was performed using a SVM classifier. Fall detection performance was evaluated using the area under the ROC curves (AUCs) for each sensor deployment. We found that a fall is more likely to be detected if the subject is falling toward or away from the sensor and a ceiling Doppler radar is more reliable for fall detection than a wall mounted one.

关键词： Doppler radar Floors Support vector machines Radar detection Medical services Conferences

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Donor Selection for Hematopoietic Stem Cell Transplant Using Cost-Sensitive SVM

Donor Selection for Hematopoietic Stem Cell Transplant Using...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Adarsh Sivasankaran Vladimir Cherkassky Mark Albrecht Eric Williams Martin Maiers Biomedical Informatics and Computational Biology Department of Electrical and Computer Engineering University of Minnesota Minneapolis Minnesota U.S.A. Bioinformatics Research National Marrow Donor Program Minneapolis Minnesota U.S.A.

ISBN: (纸本)9781509002887

Donor selection for Hematopoietic Stem Cell Transplant often requires physicians to manually select 3 to 5 donors from a list of 100s of genetically compatible donors as identified by HLA-based matching algorithms. The decision process is complicated by a lack of strict guidelines governing a "secondary" selection process, which is based upon non-HLA donor attributes. Our research is aimed at modeling this "secondary" decision process which can help physicians choose the right donors, based on donor attributes and historical choice behavior. Proposed black box models will help in improving selection consistency.

关键词： Medical services Support vector machines Data models Stem cells Mathematical model Numerical models Training

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Video supported bilateral teleoperation system: Design and implementation

Video supported bilateral teleoperation system: Design and i...

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International Symposium on Computational Intelligence and informatics

作者： Hunor Sándor Tamás Szabó Tamás Vajda Piroska Haller Zoltán Szántó Lőrinc Márton Department of Electrical Engineering Sapientia Hungarian University of Transylvania Mures Romania Department of Informatics ‘Petru Maior’ University Mures Romania Department of Computer Science Technical University of Cluj Napoca Cluj Napoca Romania

In bilateral teleoperation systems, beside the haptic feedback, the human operator also needs video information about the motion of the distantly controlled robot to complete the teleoperation task. In this study a software design approach is presented for such bilateral teleoperation systems that include one or more video channels. A control algorithm is also presented that regulates the traffic in the video channels in order to assure good communication properties for the communication channels over which the control signals are interchanged by the master and slave side of the teleoperation system. Solutions are also given for the implementation of such teleoperation systems. Experimental measurements are presented to validate the proposed communication and software design approach.

关键词： Haptic interfaces Robot sensing systems Delays Streaming media Communication channels Force

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Skin lesion segmentation using co-operative neural network edge detection and colour normalisation

Skin lesion segmentation using co-operative neural network e...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Gerald Schaefer Maher I. Rajab M. Emre Celebi Hitoshi Iyatomi Department of Science Loughborough University Loughborough UK Department of Computer Engineering Umm Al-Qura University Makkah Saudi Arabia Department of Computer Science Louisiana State University Shreveport USA Department of Electrical Informatics Hosei University Tokyo Japan

Lesion segmentation is an important step in analysing dermoscopic skin lesion images. In this paper we achieve accurate lesion segmentation using a co-operative neural network-based edge detection approach coupled with a pre-processing step that enhances colour information and contrast of the images. Extensive experiments are carried out on a dataset of 100 dermoscopic images with known ground truths obtained from three expert dermatologists. The results show that our approach is capable of providing good segmentation performance while the colour enhancement step leads to improved segmentation accuracy.

关键词： Skin Lesions Neural networks Image edge detection Image segmentation Image color analysis Image analysis Malignant tumors Pigmentation Cancer

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Enhanced surrogate models for statistical design exploiting space mapping technology

Enhanced surrogate models for statistical design exploiting ...

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Microwave, MTT-S International Symposium

作者： S. Koziel J.W. Bandler A.S. Mohamed K. Madsen Simulation Optimization Systems Research Laboratory Department of Electrical and Computer Engineering McMaster University Hamilton ONT Canada McMaster University Hamilton ONT Canada Informatics and Mathematical Modelling Technical University of Denmark Denmark

We present advances in microwave and RF device modeling exploiting space mapping (SM) technology. We propose new SM modeling formulations utilizing input mappings, output mappings, frequency scaling and quadratic approximations. Our aim is to enhance circuit models for statistical analysis and yield-driven design. We illustrate our results using a capacitively-loaded two-section impedance transformer, a single-resonator waveguide filter and a six-section H-plane waveguide filter.

关键词： Space technology Samarium Electromagnetic waveguides Statistical analysis Microwave filters Circuit simulation Microwave devices Radio frequency Microwave technology Impedance

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