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Diagnosis of COVID-19 Pneumonia via a Novel Deep Learning architecture

Journal of computer science & Technology 2022年第2期37卷 330-343页

作者： Xin Zhang Siyuan Lu Shui-Hua Wang Xiang Yu Su-Jing Wang Lun Yao Yi Pan Yu-Dong Zhang Department of Medical Imaging The Fourth People's Hospital of Huai'anHuai'an 223002China School of Informatics University of LeicesterLeicesterLE17RHU.K. School of Architecture Building and Civil Engineering Loughborough UniversityLoughboroughLE113TUU.K. School of Mathematics and Actuarial Science University of LeicesterLeicesterLE17RHU.K. Key Laboratory of Behavior Sciences Institute of PsychologyChinese Academy of SciencesBeijing 100101China Department of Psychology University of the Chinese Academy of SciencesBeijing 100101China Department of Infection Diseases The Fourth People's Hospital of Huai'anHuaian 223002China Department of Computer Science Georgia State UniversityAtlanta 30302-5060U.S.A. Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz University Jeddah 21589Saudi Arabia

COVID-19 is a contagious infection that has severe effects on the global economy and our daily *** diagnosis of COVID-19 is of importance for consultants,patients,and *** this study,we use the deep learning network AlexNet as the backbone,and enhance it with the following two aspects:1)adding batch normalization to help accelerate the training,reducing the internal covariance shift;2)replacing the fully connected layer in AlexNet with three classifiers:SNN,ELM,and ***,we have three novel models from the deep COVID network(DC-Net)framework,which are named DC-Net-S,DC-Net-E,and DC-Net-R,*** comparison,we find the proposed DC-Net-R achieves an average accuracy of 90.91%on a private dataset(available upon email request)comprising of 296 images while the specificity reaches 96.13%,and has the best performance among all three proposed *** addition,we show that our DC-Net-R also performs much better than other existing algorithms in the literature.

关键词： pneumonia COVID-19 convolutional neural network AlexNet deep learning

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Self-adaptive vision-language model for 3D segmentation of pulmonary artery and vein

arXiv

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arXiv 2025年

作者： Guo, Xiaotong Yang, Deqian Wang, Dan Zhao, Haochen Li, Yuan Sui, Zhilin Zhou, Tao Zhang, Lijun Meng, Yanda State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China Department of Thoracic Surgery National Clinical Research Center for Cancer Cancer Hospital Shenzhen Hospital China School of Intelligent Science and Technology Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou310024 China R&D Center Guangxi Huayi Artificial Intelligence Medical Technology Co. Ltd. China School of Computer Science and Engineering Beihang University Beijing China Department of Computer Science University of Exeter Exeter United Kingdom Department of Cardiovascular & Metabolic Medicine University of Liverpool Liverpool United Kingdom Guangzhou Jiayi Software Technology Co. Ltd. China

Accurate segmentation of pulmonary structures is crucial in clinical diagnosis, disease study, and treatment planning. Significant progress has been made in deep learning-based segmentation techniques, but most require much labeled data for training. Consequently, developing precise segmentation methods that demand fewer labeled datasets is paramount in medical image analysis. The emergence of pre-trained vision-language foundation models, such as CLIP, recently opened the door for universal computer vision tasks. Exploiting the generalization ability of these pre-trained foundation models on downstream tasks, such as segmentation, leads to unexpected performance with a relatively small amount of labeled data. However, exploring these models for pulmonary artery-vein segmentation is still limited. This paper proposes a novel framework called Language-guided self-adaptive Cross-Attention Fusion Framework. Our method adopts pre-trained CLIP as a strong feature extractor for generating the segmentation of 3D CT scans, while adaptively aggregating the cross-modality of text and image representations. We propose a s pecially designed adapter module to fine-tune pre-trained CLIP with a self-adaptive learning strategy to effectively fuse the two modalities of embeddings. We extensively validate our method on a local dataset, which is the largest pulmonary artery-vein CT dataset to date and consists of 718 labeled data in total. The experiments show that our method outperformed other state-of-the-art methods by a large margin. Our data and code will be made publicly available upon acceptance. Copyright © 2025, The Authors. All rights reserved.

关键词： Visual languages

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mPose: Environment- and subject-agnostic 3D skeleton posture reconstruction leveraging a single mmWave device

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Smart Health 2022年 23卷

作者： Shi, Cong Lu, Li Liu, Jian Wang, Yan Chen, Yingying Yu, Jiadi WINLAB Department of Electrical and Computer Engineering Rutgers University New Brunswick NJ United States Key Laboratory of Blockchain and Cyberspace Governance of Zhejiang Province Zhejiang University Hangzhou China Min H. Kao Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN United States Department of Computer and Information Sciences Temple University Philadelphia PA United States Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

Human skeleton posture reconstruction is an essential component for human–computer interactions (HCI) in various application domains. Traditional approaches usually rely on either cameras or on-body sensors, which induce privacy concerns or inconvenient practical setups. To address these practical concerns, this paper proposes a low-cost contactless skeleton posture reconstruction system, mPose, which can reconstruct a user's 3D skeleton postures using a single mmWave device. mPose does not require the user to wear any sensors and can enable a broad range of emerging mobile applications (e.g., VR gaming and pervasive user input) via mmWave-5G ready Internet of Things (IoT) devices. Particularly, the system extracts multi-dimensional spatial information from mmWave signals which characterizes the skeleton postures in a 3D space. To mitigate the impacts of environmental changes, mPose dynamically detects the user location and extracts spatial features from the mmWave signals reflected only from the user. Furthermore, we develop a deep regression method with a domain discriminator to learn a mapping between the spatial features and the joint coordinates of human body while removing subject-specific characteristics, realizing robust posture reconstruction across users. Extensive experiments, involving 17 representative body postures, 7 subjects, and 3 indoor environments, show that mPose outperforms contemporary state-of-the-art RF-based solutions with a lower average joint error of only ∼30 mm, while achieving transferability across environments and subjects at the same time. © 2021 Elsevier Inc.

关键词： 3D skeleton posture reconstruction MmWave

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Learning spectral normalized adversarial systems with stacked structure for high-quality 3D object generation

Learning spectral normalized adversarial systems with stacke...

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作者： Zhang, Haoxu Qiu, Chenchen Wang, Chao Wei, Bin Yu, Zhibin Zheng, Haiyong Li, Juan Department of Electronic Engineering College of Information Science and Engineering Ocean University of China Qingdao China Shandong Key Laboratory of Digital Medicine and Computer Assisted Surgery The Affiliated Hospital of Qingdao University Qingdao China Department of Mathematics School of Science and Engineering University of Dundee Dundee United Kingdom College of Mechanical and Electrical Engineering Qingdao Agricultural University Qingdao China

This paper proposes a new method for generating 3D objects based on generative adversarial networks (GANs). Recently, GANs have been used in 3D object generation, but it is still very challenging to generate high-quality 3D objects because of the complex data distribution over 3D objects. In this paper, we propose a system based on GAN that makes the generated objects more realistic. We use multiple generators and discriminators to enhance the ability of the model for learning complex distributions. Such a stacked structure can be considered as a coarse-to-fine or low-to-high–resolution mechanism. We employ the spectral normalization technology to control the Lipschitz constant of the discriminators by literally constraining the spectral norm of each layer to get a more stable training process. In this way, the proposed model can generate realistic and high-quality 3D objects. Moreover, our system can also recover incomplete 3D objects into complete 3D objects. Experiments demonstrate that our model performs better in the quality of the generated objects than the baselines. © 2019 John Wiley & Sons, Ltd.

关键词： Generative adversarial networks

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Reverse-Bias Resilience of Monolithic Perovskite/Silicon Tandem Solar Cells

Reverse-Bias Resilience of Monolithic Perovskite/Silicon Tan...

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IEEE Conference Photovoltaic Specialists (PVSC)

作者： Zhaojian Xu Helen Bristow Maxime Babics Badri Vishal Erkan Aydin Randi Azmi Esma Ugur Bumin K. Yildirim Jiang Liu Ross A. Kerner Stefaan De Wolf Barry P. Rand Department of Electrical and Computer Engineering Princeton University Princeton NJ USA Physical Science and Engineering Division (PSE) KAUST Solar Center (KSC) King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia National Renewable Energy Laboratory Chemistry and Nanoscience Center Golden CO USA Andlinger Center for Energy and the Environment Princeton University Princeton NJ USA

ISBN: (数字)9781665464260

ISBN: (纸本)9781665475822

Metal halide perovskites have rapidly enabled a range of high-performance photovoltaic technologies. However, catastrophic failure under reverse voltage bias hinders their commercialization. In this work, we demonstrate that by employing a monolithic perovskite/silicon tandem structure, the perovskite subcell can be effectively protected by the silicon subcell under reverse bias, owing to the low reverse-bias diode current of the silicon subcell. As a result, the tested perovskite/silicon tandem devices show superior reverse-bias resilience compared to perovskite single-junction devices in both long-term reverse voltage biasing tests at the single-cell level and partial shading tests at the module level. These results highlight that, compared to other perovskite technologies, monolithic perovskite/silicon tandems are at a higher technology readiness level in terms of tackling the reverse-bias and partial shading challenge, which is a considerable advantage towards commercialization.

关键词： Photovoltaic systems Photovoltaic cells Metals Voltage Perovskites Silicon Commercialization Resilience

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Absolute Localization in Feature-Poor Industrial Confined Spaces

Absolute Localization in Feature-Poor Industrial Confined Sp...

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IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Rune Y. Brogaard Robert A. Hewitt Sarah Etter Arash Kalantari Evangelos Boukas Faculty of Electrical Engineering Technical University of Denmark Kgs Lyngby Denmark Mobility and Robotic Systems Section NASA Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA Department of Computer Science University of Texas Austin TX USA

Autonomous inspection of dark, confined, and feature-poor spaces requires robotic platforms to utilize accurate and reliable localization systems for safe and reliable operation. This paper presents an absolute localization system for highly feature-poor spaces, using visual inertial odometry and GPU-based point cloud registrations for limited field-of-view sensors. The extracted structural elements from sensor scans, along side IMU measurements, are used to limit the search area for the GPU-based point cloud registrations. We employ Stein-ICP which is an uncertainty aware variant of ICP. The 3D registrations are then fused with a visual-inertial odometry estimate in an Extended Kalman Filter to provide a fast and accurate absolute pose estimate. The proposed localization system is tested in both a simulated environment and in a mock-up model of a chemical distillation column - both highly feature-poor areas.

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Stimulated Generation of Indistinguishable Single Photons from a Quantum Ladder System

Stimulated Generation of Indistinguishable Single Photons fr...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Sbresny, Friedrich Hanschke, Lukas Schöll, Eva Rauhaus, William Scaparra, Bianca Boos, Katarina Casalengua, Eduardo Zubizarreta Riedl, Hubert del Valle, Elena Finley, Jonathan J. Jöns, Klaus D. Müller, Kai Walter Schottky Institut Department of Electrical and Computer Engineering and MCQST Technische Universitat Miinchen Garching85748 Germany Department of Physics Paderborn University Paderborn33098 Germany Faculty of Science and Engineering University of Wolverhampton WolverhamptonWV1 1LY United Kingdom Departamento de Fisica Teórica de la Materia Condensada andlFIMAC Universidad Autónoma de Madrid Madrid28049 Spain Walter Schottky Institut Department of Physics MCQST Technische Universität München Garching85748 Germany Institute for Advanced Study Technische Universität München Garching85748 Germany

Single photons play a key role for applications in photonic quantum technologies. Here we propose, model and demonstrate a scheme that enables the generation of high purity indistinguishable single photons from a quan... 详细信息

ISBN: (纸本)9781957171258

关键词： Ladders

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Inversion Symmetry Breaking in Epitaxial Ultrathin Bi (111) Films

arXiv

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arXiv 2023年

作者： Inbar, Hadass S. Zubair, Muhammad Dong, Jason T. Engel, Aaron N. Dempsey, Connor P. Chang, Yu Hao Nishihaya, Shinichi Khalid, Shoaib Fedorov, Alexei V. Janotti, Anderson Palmstrøm, Chris J. Materials Department UC Santa Barbara CA93106 United States Department of Physics and Astronomy University of Delaware NewarkDE19716 United States Department of Materials Science and Engineering University of Delaware NewarkDE19716 United States Department of Electrical & Computer Engineering UC Santa Barbara CA93106 United States Advanced Light Source Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

Bismuth (Bi) films hold potential for spintronic devices and topological one-dimensional edge transport. Large-area high-quality (111) Bi ultrathin films are grown on InSb (111)B substrates. Strong film-substrate interactions epitaxially stabilize the (111) orientation and lead to inversion symmetry breaking. We resolve the longstanding controversy over the 2 topological assignment of bismuth and show that the surface states are topologically trivial. Our results demonstrate that interfacial bonds prevent the semimetal-to-semiconductor transition predicted for freestanding bismuth layers, highlighting the importance of controlled functionalization and surface passivation in two-dimensional materials. Copyright © 2023, The Authors. All rights reserved.

关键词： Bismuth

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Machine Learning and IoT based Performance Improvement of Energy Efficiency in Smart Buildings

Machine Learning and IoT based Performance Improvement of En...

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Sustainable Computing and Data Communication Systems (ICSCDS), International Conference on

作者： Sowmya Jagadeesan C.N. Ravi M. Sujatha S Sree Southry J Sundararajan Ch. Venkata Krishna Reddy Departnent of BCA and IT iNurture Education Solutions Vels Institute of Science Technology and Advanced Studies Chennai Tamil Nadu India Department of Computer Science and Engineering CMR Engineering college Hyderabad Telangana India Department of Electrical and Electronics Engineering Easwari Engineering College Ramapuram Chennai Tamil Nadu India Department of Electronics and Communication Engineering Sona College of Technology Salem Tamil Nadu India Department of Electronics and Communication NPR College of Enggineering and Technology Dindugul Tamil Nadu India Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Hyderabad Telangana India

The energy plays a prominent role in the development of a country’s economic conditions. This helps to increase the overall performance index of a country. Thus a continuous energy system is needed to develop a country’s performance index. Thus to have an advancement in the energy management system, an improved system called smart grid is implemented. This helps in efficient usage of energy management through meeting the demand side managing in the smart buildings. This assistances to decrease the additional procedure of energy consumption through optimization techniques such as genetic algorithm used in smart buildings. This is done with the machine learning through optimization algorithm. This helps to proper scheduling of appliances. This is done through the priority scheduling. The overall performance is done through the internet of things with sensors. The sensors helps in the process of sensing the external physical parameters such as temperature, humidity, moisture, heat and light. This helps to enhance the energy efficiency in the smart buildings through the machine learning and IoT.

关键词： Temperature sensors Smart buildings Processor scheduling Machine learning Energy efficiency Performance analysis Smart grids

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Interpretable inverse-designed cavity for spontaneous photon-pair generation

Interpretable inverse-designed cavity for spontaneous photon...

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Frontiers in Optics + Laser science 2023, FiO, LS 203: Part of Frontiers in Optics + Laser science 2023

作者： Jia, Zhetao Qarony, Wayesh Park, Jagang Hooten, Sean Wen, Difan Zhiyenbayev, Yertay Seclì, Matteo Redjem, Walid Dhuey, Scott Schwartzberg, Adam Yablonovitch, Eli Kanté, Boubacar Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94720 United States Hewlett Packard Labs Hewlett Packard Enterprise 820 N. McCarthy Blvd. MilpitasCA95035 United States Applied Science and Technology Graduate Group University of California at Berkeley BerkeleyCA94720 United States Molecular Foundry Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

We demonstrate the first inverse-designed device for enhancing photon-pair generation rate in silicon photonics with compact footprint. The proposed inverse-design approach can be generalized to other nonlinear photon... 详细信息

ISBN: (纸本)9781957171296

关键词： Four wave mixing Grating coupler Nonlinear effects Optical confinement Scanning electron microscopy Silicon photonics

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