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Application of Deep Learning in Fundus Image Processing for Ophthalmic Diagnosis - A Review

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arXiv 2018年

作者： Sengupta, Sourya Singh, Amitojdeep Leopold, Henry A. Gulati, Tanmay Lakshminarayanan, Vasudevan Theoretical and Experimental Epistemology Lab School of Optometry and Vision Science University of Waterloo Ontario Canada Department of System Design Engineering University of Waterloo Ontario Canada Department of Computer Science and Engineering Manipal Institute of Technology India

An overview of the applications of deep learning in ophthalmic diagnosis using retinal fundus images is presented. We also review various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation of optic disk, blood vessels and retinal layer as well as detection of lesions are reviewed. Recent deep learning models for classification of diseases such as age-related macular degeneration, glaucoma, diabetic macular edema and diabetic retinopathy are also reported. Copyright © 2018, The Authors. All rights reserved.

关键词： Ophthalmology

Generating new classes of fixed-time stable systems with predefined upper bound for the settling time

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arXiv 2019年

作者： Aldana-López, Rodrigo Gómez-Gutiérrez, David Jiménez-Rodríguez, Esteban Sánchez-Torres, Juan Diego Defoort, Michael Department of Computer Science and Systems Engineering University of Zaragoza Zaragoza Spain Multi-Agent Autonomous Systems Lab Intel Labs Intel Tecnología de México Jalisco Mexico Tecnologico de Monterrey Escuela de Ingeniería y Ciencias Jalisco Mexico Relativity6 Inc. Computer Science & Artificial Intelligence Lab. Jalisco Mexico Research Laboratory on Optimal Design Devices and Advanced Materials -OPTIMA- Department of Mathematics and Physics ITESO Jalisco Mexico LAMIH UMR CNRS 8201 INSA Polytechnic University of Hauts-de-France Valenciennes France

This paper aims to provide a methodology for generating autonomous and nonautonomous systems with a fixed-time stable equilibrium point where an Upper Bound of the Settling Time (UBST) is set a priori as a parameter of the system. In addition, some conditions for such an upper bound to be the least one are provided. This construction procedure is a relevant contribution when compared with traditional methodologies for generating fixed-time algorithms satisfying time constraints since current estimates of an UBST may be too conservative. The proposed methodology is based on time-scale transformations and Lyapunov analysis. It allows the presentation of a broad class of fixed-time stable systems with predefined UBST, placing them under a common framework with existing methods using time-varying gains. To illustrate the effectiveness of our approach, we generate novel, autonomous and non-autonomous, fixed-time stable algorithms with predefined least UBST. Copyright © 2019, The Authors. All rights reserved.

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Toward the universal quantum cloner limit for designing compact photonic CNOT gate

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arXiv 2019年

作者： Gueddana, Amor Lakshminarayanan, Vasudevan Green & Smart Communication Systems Lab Gres'Com Engineering School of Communication of Tunis Sup'Com University of Carthage Ghazela Technopark Ariana2083 Tunisia Theoretical & Experimental Epistemology Lab TEEL School of Optometry and Vision Science University of Waterloo 200 University Avenue West WaterlooONN2l 3G1 Canada Department of Physics Department of Electrical and Computer Engineering Department of Systems Design Engineering University of Waterloo 200 University Avenue West WaterlooONN2l 3G1 Canada

We suggest a near deterministic compact model of a photonic CNOT gate based on a quantum dot trapped in a double sided optical microcavity and a universal cloner. Our design surpasses the cloner optimal limit of 5/6 and we show that it provides fidelity around 91 % in the weak coupling regime. Copyright © 2019, The Authors. All rights reserved.

关键词： Semiconductor quantum dots

A General protocol for Distributed Quantum Gates

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arXiv 2018年

作者： Sarvaghad-Moghaddam, Moein Zomorodi-Moghadam, Mariam Farouk, Ahmed Quantum Design Automation Lab Amirkabir University of Technology Tehran 1 Iran Department of Computer Engineering Ferdowsi University of Mashhad Mashhad Iran Department of Physics and Computer Science Wilfrid Laurier University Waterloo Canada

Distributed quantum computation requires to apply quantum remote gates on separate nodes or subsystems of network. On the other hand, Toffoli gate is a universal and well-known quantum gate. It is frequently used in synthesis of quantum circuits. In this paper, a general protocol for implementing a remote η-qubit controlled-U gate is presented with minimum required resources. Then, the proposed method is applied for implementing a Toffoli gate in bipartite and tripartite systems. This method also is optimal when group of the qubits belong to one part, section or subsystem of network. Beucase it only use one entangled qubit for each group of the qubits in mentioned conditions. Copyright © 2018, The Authors. All rights reserved.

关键词： Qubits

Not just functional, nutritious, but also experiential: designing eating experiences for space travel 69

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Not just functional, nutritious, but also experiential: Desi...

69th International Astronautical Congress: #InvolvingEveryone, IAC 2018

作者： Obrist, Marianna Tu, Yunwen Yao, Lining Velasco, Carlos Sussex Computer Human Interaction Lab School of Engineering and Informatics University of Sussex Chichester 1 BrightonBN1 9QJ United Kingdom Food Design 322 Crestview Circle Daly CityCA United States Carnegie Mellon University School of Computer Science 5000 Forbes Ave PittsburghPA15213 United States Center for Multisensory Marketing Department of Marketing BI Norwegian Business School Nydalsveien 37 Oslo0484 Norway

In light of short- and long-term space travels to the Moon and Mars, it is essential to design nutritious foods, but also to make eating an enjoyable experience. To date, though, most research on space food design emphasizes the functional and nutritional aspects of food, but there are no systematic studies that focus is on the human experience of eating in space. We know however that food has a multi-dimensional and multisensorial role in societies and that sensory, hedonic, and social features of eating and food design should not be underestimated. We present, how research in the field of Human-computer Interaction (HCI) can provide a user-centered design approach to co-create innovative ideas around the future of food and eating in space, balancing functional and experiential factors. Based on our research and inspired by advances in human food-interaction design, we developed three design concepts that integrate and tackle four crucial challenges for 'Eating in Space': to be functional, sensorial, emotional, and social. Moreover, we consider the environmental/atmospheric perspective in our design concepts. We can particularly capitalize on recent technological advances around digital fabrication, food 3D printing technology, and virtual and augmented reality to enable the design and integration of multisensory eating experiences. We also highlight that in future space travels, the target users will diversify. Thinking about future target users, we need to look at astronauts (current users, paid to do the job) but also beyond and consider paying customers (non-astronauts) who will be able to book a space holiday to the Moon or Mars. To create the right conditions for space travelling and to satisfy those users, we need to innovate beyond the initial excitement of designing an 'eating like an astronaut' experience and design for experiences beyond the novelty of the situation. To do so we can draw upon prior HCI research in human food-interaction design and build

关键词： Human computer interaction

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Preface

CEUR Workshop Proceedings 2020年 2617卷

作者： Baytas, Mehmet Aydin Funk, Markus Ljungblad, Sara Garcia, Jérémie La Delfa, Joseph Mueller, Florian Floyd Graduate School of Social Sciences and Humanities Koç University Istanbul Turkey Cerence Inc. Ulm Germany Department of Computer Science of Engineering University of Gothenburg Chalmers University of Technology Gothenburg Sweden ENAC University of Toulouse Toulouse France School of Design RMIT University Melbourne Australia Exertion Games Lab Monash University Melbourne Australia

Deformable object tracking with gated fusion

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arXiv 2018年

作者： Liu, Wenxi Song, Yibing Chen, Dengsheng He, Shengfeng Yu, Yuanlong Yan, Tao Hancke, Gerhard P. Lau, Rynson W.H. College of Mathematics and Computer Science Fuzhou University China Tencent AI Lab Shenzhen China Jiangsu Key Laboratory of Media Design and Software Technology Jiangnan University China School of Computer Science and Engineering South China University of Technology China City University of Hong Kong Hong Kong

—The tracking-by-detection framework receives growing attentions through the integration with the Convolutional Neural Networks (CNNs). Existing tracking-by-detection based methods, however, fail to track objects with severe appearance variations. This is because the traditional convolutional operation is performed on fixed grids, and thus may not be able to find the correct response while the object is changing pose or under varying environmental conditions. In this paper, we propose a deformable convolution layer to enrich the target appearance representations in the tracking-by-detection framework. We aim to capture the target appearance variations via deformable convolution, which adaptively enhances its original features. In addition, we also propose a gated fusion scheme to control how the variations captured by the deformable convolution affect the original appearance. The enriched feature representation through deformable convolution facilitates the discrimination of the CNN classifier on the target object and background. Extensive experiments on the standard benchmarks show that the proposed tracker performs favorably against state-of-the-art methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Convolution

Deep learning based video system for accurate and real-time parking measurement

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arXiv 2019年

作者： Cai, Bill Yang Alvarez, Ricardo Sit, Michelle Duarte, Fábio Ratti, Carlo Senseable City Lab Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Center for Computational Engineering Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States School of Architecture and Design Pontifical Catholic University of Paraná R. Imac. ConceiÃgÃ čo 1155 - Prado Velho Curitiba - PR80215-901 Brazil Department of Computer Science and Engineering University of California San Diego 9500 Gilman Drive La JollaCA92093 United States

Parking spaces are costly to build, parking payments are difficult to enforce, and drivers waste an excessive amount of time searching for empty lots. Accurate quantification would inform developers and municipalities in space allocation and design, while real-time measurements would provide drivers and parking enforcement with information that saves time and resources. In this paper, we propose an accurate and real-time video system for future Internet of Things (IoT) and smart cities applications. Using recent developments in deep convolutional neural networks (DCNNs) and a novel vehicle tracking filter, we combine information across multiple image frames in a video sequence to remove noise introduced by occlusions and detection failures. We demonstrate that our system achieves higher accuracy than pure image-based instance segmentation, and is comparable in performance to industry benchmark systems that utilize more expensive sensors such as radar. Furthermore, our system shows significant potential in its scalability to a city-wide scale and also in the richness of its output that goes beyond traditional binary occupancy statistics. Copyright © 2019, The Authors. All rights reserved.

关键词： Internet of things

Correction: CEPC Technical design Report: Accelerator

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Radiation Detection Technology and Methods 2024年第1期9卷 184-192页

作者： Abdallah, Waleed de Freitas, Tiago CarlosAdorno Afanaciev, Konstantin Ahmad, Shakeel Ahmed, Ijaz Ai, Xiaocong Aleem, Abid Altmannshofer, Wolfgang Alves, Fabio An, Weiming An, Rui Anderle, Daniele Paolo Antusch, Stefan Arai, Yasuo Arbuzov, Andrej Arhrib, Abdesslam Ashry, Mustafa Bai, Sha Bai, Yu Bai, Yang Bairathi, Vipul Balazs, Csaba Bambade, Philip Ban, Yong Bandyopadhyay, Triparno Bao, Shou-Shan Barber, Desmond P. Bat, Ays¸e Batozskaya, Varvara Behera, Subash Chandra Belyaev, Alexander Bertucci, Michele Bi, Xiao-Jun Bi, Yuanjie Bian, Tianjian Bianchi, Fabrizio Bieko¨tter, Thomas Biglietti, Michela Bilanishvili, Shalva Binglin, Deng Bodrov, Denis Bogomyagkov, Anton Bondarenko, Serge Boogert, Stewart Boonekamp, Maarten Borri, Marcello Bosotti, Angelo Boudry, Vincent Boukidi, Mohammed Boyko, Igor Bozovic, Ivanka Bozzi, Giuseppe Brient, Jean-Claude Budzinskaya, Anastasiia Bukhari, Masroor Bytev, Vladimir Cacciapaglia, Giacomo Cai, Hua Cai, Wenyong Cai, Wujun Cai, Yijian Cai, Yizhou Cai, Yuchen Cai, Haiying Cai, Huacheng Calibbi, Lorenzo Cang, Junsong Cao, Guofu Cao, Jianshe Chance, Antoine Chang, Xuejun Chang, Yue Chang, Zhe Chang, Xinyuan Chao, Wei Chatrabhuti, Auttakit Che, Yimin Che, Yuzhi Chen, Bin Chen, Danping Chen, Fuqing Chen, Fusan Chen, Gang Chen, Guoming Chen, Hua-Xing Chen, Huirun Chen, Jinhui Chen, Ji-Yuan Chen, Kai Chen, Mali Chen, Mingjun Chen, Mingshui Chen, Ning Chen, Shanhong Chen, Shanzhen Chen, Shao-Long Chen, Shaomin Chen, Shiqiang Chen, Tianlu Chen, Wei Chen, Xiang Chen, Xiaoyu Chen, Xin Chen, Xun Chen, Xurong Chen, Ye Chen, Ying Chen, Yukai Chen, Zelin Chen, Zilin Chen, Boping Chen, Chunhui Cheng, Hok Chuen Cheng, Huajie Cheng, Shan Cheng, Tongguang Chi, Yunlong Chimenti, Pietro Chiu, Wen Han Cho, Guk Chu, Ming-Chung Chu, Xiaotong Chu, Ziliang Coloretti, Guglielmo Crivellin, Andreas Cui, Hanhua Cui, Xiaohao Cui, Zhaoyuan D’Anzi, Brunella Dai, Ling-Yun Dai, Xinchen Dai, Xuwen De Maria, Antonio De Filippis, Nicola De La Taille, Christophe De Mori, Francesca De Sio, Chiara Del Core, Elisa Deng, Cairo University Giza Egypt Xi’an Jiaotong-Liverpool University Suzhou China Institute of Power Engineering of National Academy of Sciences of Belarus Minsk Belarus Pakistan Institute of Nuclear Science and Technology (PINSTECH) Islamabad Pakistan Applied Physics Department Science and Technology Federal Urdu University of Arts Islamabad Pakistan Zhengzhou University Zhengzhou China Institute of High Energy Physics Chinese Academy of Sciences Beijing China University of California Santa Cruz Santa Cruz USA Nanjing University Nanjing China Beijing Normal University Beijing China Harvard University Cambridge USA South China Normal University Guangzhou China University of Basel Basel Switzerland High Energy Accelerator Research Organization (KEK) Tsukuba Japan Joint Institute for Nuclear Research Dubna Russia Faculty of Sciences and Techniques Université Abdelmalek Essaadi Tangier Morocco Southeast University Nanjing China Department of Physics University of Wisconsin–Madison Madison USA Instituto de Alta Investigación Universidad de Tarapacá Arica Chile Monash University Melbourne Australia Laboratoire de Physique des 2 infinis Irène Joliot-Curie – IJCLab Orsay France Peking University Beijing China Department of Physics and Nanotechnology SRM Institute of Science and Technology Kattankulathur India Shandong University Jinan China University of New Mexico Albuquerque USA Bandirma Onyedi Eylul University Bandırma Turkey National Centre for Nuclear Research Warsaw Poland Indian Institute of Technology Madras (IN) Chennai India University of Southampton Southampton UK INFN Milano - LASA Segrate Italy Sun Yat-Sen University Guangzhou China China Institute of Atomic Energy Beijing China INFN-University of Torino Turin Italy Karlsruhe Institute of Technology Institute for Theoretical Physics Karlsruhe Germany INFN-Sezione di Roma Tre Rome Italy Kutaisi International University Kutaisi Georgia Soochow University Suzhou China Budker Institute