Relevant bibliographies by topics / COVID-19 detection

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'COVID-19 detection'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "COVID-19 detection"

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Mohammed, Abduh Hummadi, Hamdi Al Shammari Safooq, Abdulrahman Al Oraini Abdullah, Musaad Alabdulmunim Adel, Abdullah Alarifi Saud, and Ali Jarah Ahmed. "COVID-19 LABORATORY TESTING." International Journal of Life Sciences Research 10, no. 4 (2022): 64–72. https://doi.org/10.5281/zenodo.7406553.

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<strong>Abstract:</strong> Rapid and accurate laboratory diagnosis of active COVID-19 infection is one of the cornerstones of pandemic control. With the large number of tests available on the market, using the correct sample type and laboratory testing technique in the&nbsp; clinical setting will be challenging for laypersons. In this mini-review, we will discuss the difference in diagnostic performance of different upper and lower airway samples and the role of blood and stool samples. We will discuss the performance characteristics of nucleic acid laboratory testing techniques in Acid Enhanc
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Malpe, Prof Kalpana. "COVID-19 Face Mask Detection." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 1312–15. http://dx.doi.org/10.22214/ijraset.2022.40005.

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Abstract: Face mask detection involves in detection the placement of the face then crucial whether or not it's a mask thereon or not. the problem is proximately cognate to general object notion to detect the categories of objects. Face identification flatly deals with identifying a particular cluster of entities i.e., Face. it's varied applications, like autonomous driving, education, police work, and so on. This paper presents a simplified approach to serve the above purpose using the basic Machine Learning (ML) packages such as TensorFlow, Keras, OpenCV and Scikit-Learn. The planned techniqu
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Echtioui, Amira, Wassim Zouch, Mohamed Ghorbel, Chokri Mhiri, and Habib Hamam. "Detection Methods of COVID-19." SLAS TECHNOLOGY: Translating Life Sciences Innovation 25, no. 6 (2020): 566–72. http://dx.doi.org/10.1177/2472630320962002.

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Since being first detected in China, coronavirus disease 2019 (COVID-19) has spread rapidly across the world, triggering a global pandemic with no viable cure in sight. As a result, national responses have focused on the effective minimization of the spread. Border control measures and travel restrictions have been implemented in a number of countries to limit the import and export of the virus. The detection of COVID-19 is a key task for physicians. The erroneous results of early laboratory tests and their delays led researchers to focus on different options. Information obtained from compute
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Kalaiselvi, Dr K. "Covid 19 Detection Using Deep Learning and Covid 19 Symptoms Checker." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (2023): 1–10. http://dx.doi.org/10.55041/ijsrem27783.

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Abstract--The goal of this project is to classify healthy individuals, COVID-19 cases, and viral pneumonia cases. Deep learning is a type of machine learning. It enables us to teach artificial intelligence to anticipate outcomes given a set of data.Artificial intelligence can be trained through supervised learning. Voice and facial recognition, disease diagnosis, defence, and security are all domains where deep learning is applied. Artificial neuralnetworks are represented by the word deep in deep learning. The human brain inspired artificial neural networks. It is made up of neurons, just lik
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Akram, Khelili Mohamed, Slatnia Sihem, and Kazar Okba. "Deep Learning Technique for Covid-19 Detection." Eurasia Proceedings of Health, Environment and Life Sciences 1 (December 16, 2021): 15–19. http://dx.doi.org/10.55549/ephels.3.

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Nowadays, the detection of coronavirus disease 2019 (COVID-19) is one of the main challenges in the world, due to the rapid spreading of this viral disease. Currently, new variant of covid-19 virus was discovered in south Africa, India, and United Kingdom (UK) due to the mutation of the virus. Owing this critical situation of the world health and with increased number of the cases with the absence of efficient a cure vaccine, early and accurate detection of COVID-19 is necessity of time to prevent and control this pandemic by timely quarantine and medical treatment. Chest x-ray is the most sui
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Arifin, Fatchul, Herjuna Artanto, Nurhasanah, and Teddy Surya Gunawan. "Fast COVID-19 Detection of Chest X-Ray Images Using Single Shot Detection MobileNet Convolutional Neural Networks." Journal of Southwest Jiaotong University 56, no. 2 (2021): 235–48. http://dx.doi.org/10.35741/issn.0258-2724.56.2.19.

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COVID-19 is a new disease with a very rapid and tremendous spread. The most important thing needed now is a COVID-19 early detection system that is fast, easy to use, portable, and affordable. Various studies on desktop-based detection using Convolutional Neural Networks have been successfully conducted. However, no research has yet applied mobile-based detection, which requires low computational cost. Therefore, this research aims to produce a COVID-19 early detection system based on chest X-ray images using Convolutional Neural Network models to be deployed in mobile applications. It is expe
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Vandit Gupta. "COVID-19 Detection using Deep Learning." International Journal for Modern Trends in Science and Technology 6, no. 12 (2020): 421–25. http://dx.doi.org/10.46501/ijmtst061281.

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Deep learning is an artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning and recognizing patterns from data that is unstructured or unlabelled. It is also known as deep neural learning or deep neural network. Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. ConvNets h
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Deng, Yue, Siming Xing, Meixia Zhu, and Jinzhi Lei. "Impact of insufficient detection in COVID-19 outbreaks." Mathematical Biosciences and Engineering 18, no. 6 (2021): 9727–42. http://dx.doi.org/10.3934/mbe.2021476.

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&lt;abstract&gt;&lt;p&gt;The COVID-19 (novel coronavirus disease 2019) pandemic has tremendously impacted global health and economics. Early detection of COVID-19 infections is important for patient treatment and for controlling the epidemic. However, many countries/regions suffer from a shortage of nucleic acid testing (NAT) due to either resource limitations or epidemic control measures. The exact number of infective cases is mostly unknown in counties/regions with insufficient NAT, which has been a major issue in predicting and controlling the epidemic. In this paper, we propose a mathemati
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Kou, Ziyi, Lanyu Shang, Yang Zhang, and Dong Wang. "HC-COVID." Proceedings of the ACM on Human-Computer Interaction 6, GROUP (2022): 1–25. http://dx.doi.org/10.1145/3492855.

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The proliferation of social media has promoted the spread of misinformation that raises many concerns in our society. This paper focuses on a critical problem of explainable COVID-19 misinformation detection that aims to accurately identify and explain misleading COVID-19 claims on social media. Motivated by the lack of COVID-19 relevant knowledge in existing solutions, we construct a novel crowdsource knowledge graph based approach to incorporate the COVID-19 knowledge facts by leveraging the collaborative efforts of expert and non-expert crowd workers. Two important challenges exist in devel
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Benny, Cijil. "AI INFLUENCE IN COVID-19 DETECTION." Journal of University of Shanghai for Science and Technology 23, no. 07 (2021): 1116–20. http://dx.doi.org/10.51201/jusst/21/07235.

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This paper is on analyzing the feasibility of AI studies and the involvement of AI in COVID interrelated treatments. In all, several procedures were reviewed and studied. It was on point. The best-analyzing methods on the studies were Susceptible Infected Recovered and Susceptible Exposed Infected Removed respectively. Whereas the implementation of AI is mostly done in X-rays and CT- Scans with the help of a Convolutional Neural Network. To accomplish the paper several data sets are used. They include medical and case reports, medical strategies, and persons respectively. Approaches are being
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Dissertations / Theses on the topic "COVID-19 detection"

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SINGH, BHUPINDER. "A HYBRID MSVM COVID-19 IMAGE CLASSIFICATION ENHANCED USING PARTICLE SWARM OPTIMIZATION." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18864.

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COVID-19 (novel coronavirus disease) is a serious illness that has killed millions of civilians and affected millions around the world. Mostly as result, numerous technologies that enable both the rapid and accurate identification of COVID-19 illnesses will provide much assistance to healthcare practitioners. A machine learning- based approach is used for the detection of COVID-19. In general, artificial intelligence (AI) approaches have yielded positive outcomes in healthcare visual processing and analysis. CXR is the digital image processing method that plays a vital role in the a
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Vandi, Mattia. "Detecting Face Masks and Social Distancing Against COVID-19 with Embedded Systems and Deep Learning Technologies." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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Social distancing and face mask wearing have been proven as effective measures against the spread of the infectious COronaVIrus Disease 2019 (COVID-19). However, individuals are still adapting to COVID-19 regulations. In fact, you can often see people in public places wearing face masks incorrectly or not wearing face masks at all, besides not tracking the required two meters (6 feet) distance between themselves and their surroundings. An active surveillance system that can both determine whether or not a person is wearing a face mask and tracking distances between individuals would be able
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Chen, Yulu. "Spatial Temporal Analysis of Traffic Patterns during the COVID-19 Epidemic by Vehicle Detection using Planet Remote Sensing Satellite Images." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1609843145639886.

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Altaf, Fouzia. "Deep learning augmentation for medical image analysis." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2022. https://ro.ecu.edu.au/theses/2603.

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Deep learning is at the center of the current rise of computer aided diagnosis in medical imaging. This technology has the ability to mimic extremely complex mathematical functions for predictive tasks. These functions are encoded as computational models that are learned directly from data. Deep learning models are known to achieve human-level accuracy for predictive tasks. However, such a performance requires that the model is trained on a huge amount of training data. For computer aided diagnosis tasks, the relevant training data needs to be carefully annotated by medical experts. This proce
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Jamil, Ahsan Adnan, and Daniel Landberg. "Detecting COVID-19 Using Transfer Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280352.

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COVID-19 is currently an ongoing pandemic and the large demand for testing of the disease has led to insufficient resources in hospitals. In order to increase the efficiency of COVID- 19 detection, computer vision based systems can be used. However, a large set of training data is required for creating an accurate and reliable model, which is currently not feasible to be acquired considering the novelty of the disease. Other models are currently being used within the healthcare sector for classifying various diseases, one such model is for identifying pneumonia cases by using radiographs and i
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gupta, Devansh. "Smart-Scooter Rider Assistance System using Internet of Wearable Things and Computer Vision." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1619611136736967.

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Silva, Clístenes Fernandes da. "DOTS - detection of covid-19 contagion symptoms and self-diagnosis in social networks." Master's thesis, 2021. http://hdl.handle.net/10198/23769.

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Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do Paraná<br>Social media present ways for people to share emotions, feelings, ideas, and even symptoms of disease, and is a great source of data for a variety of analyses. At the end of 2019, an alert was raised for a global pandemic of a virus that has a very high contamination rate and can cause respiratory complications in the contaminated people. To help identify those who may have the symptoms of this disease or to control who are already infected, this paper analyzed the performance of KNN, Naive Bayes, Dec
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Ferreira, Victor Leonel Vieira. "SARS-CoV-2 detection methods: where are we now?" Master's thesis, 2020. http://hdl.handle.net/10316/93052.

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Dissertação de Mestrado em Biotecnologia Farmacêutica apresentada à Faculdade de Farmácia<br>SARS-CoV-2 (Síndrome Respiratória Aguda Grave Coronavírus 2) é um coronavírus (CoVs) que pertence à família Coronaviridae e ao género Betacoronavirus, sendo considerado o maior grupo de vírus que causam infeções respiratórias e gastrointestinais em humanos e animais. Os primeiros casos da doença provocada pelo novo membro dos CoVs em humanos (Doença causada pelo Coronavírus 2019 (COVID-19)) surgiram em dezembro de 2019 na cidade de Wuhan, na China. SARS-CoV-2 é um vírus com uma maior capacidade de infe
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Mota, Pedro Nuno Ângelo. "Assessing COVID-19 impact on user opinion towards videogames - Sentiment analysis and structural break detection on steam data." Master's thesis, 2022. http://hdl.handle.net/10362/134292.

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Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence<br>As we live in a world where the videogame industry grows day by day and new media is constantly emerging, user feedback can be widely found online. User reviews are a highly valuable data source when studying player perception of a videogame. They are also apparently volatile to updates released by developers and other external events, which may change user opinion over time. Here we assess whether the COVID-19 pand
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Melo, César Gonçalo Macedo. "Sistema EdgeAI para monitorização e notificação de diferentes graus de risco em contexto Covid19." Master's thesis, 2021. http://hdl.handle.net/1822/76550.

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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores<br>Atualmente, a população atravessa uma situação epidemiológica e sanitária graves a uma escala mundial, provocada pela doença da Covid-19, originada pelo vírus SARS-CoV-2. Conhecida pela grande velocidade de progragação e facilidade de transmissão, tem conduzido a efeitos sociais, económicos e políticos devastadores em todo o mundo. A elevada taxa de pessoas assintomáticas à doença, isto é, que a têm presente no seu organismo, mas que não apresentam quaisquer sintomas, faz com que por vezes existam descu
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Books on the topic "COVID-19 detection"

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Features, Transmission, Detection, and Case Studies in COVID-19. Elsevier Science & Technology, 2024.

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Features, Transmission, Detection, and Case Studies in COVID-19. Elsevier Science & Technology Books, 2024.

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Bhardwaj, Anuj, Parag Verma, Ankur Dumka, Alaknanda Ashok, and Amit Dumka. Covid-19: Origin, Detection and Impact Analysis Using Artificial Intelligence Computational Techniques. Taylor & Francis Group, 2021.

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Bhardwaj, Anuj, Parag Verma, Ankur Dumka, Alaknanda Ashok, and Amit Dumka. Covid-19: Origin, Detection and Impact Analysis Using Artificial Intelligence Computational Techniques. Taylor & Francis Group, 2021.

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Bhardwaj, Anuj, Parag Verma, Ankur Dumka, Alaknanda Ashok, and Amit Dumka. Covid-19: Origin, Detection and Impact Analysis Using Artificial Intelligence Computational Techniques. Taylor & Francis Group, 2021.

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Hussain, Chaudhery Mustansar, and Sudheesh K. Shukla. Sensing Tools and Techniques for COVID-19: Developments and Challenges in Analysis and Detection of Coronavirus. Elsevier, 2021.

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Hussain, Chaudhery Mustansar, and Sudheesh K. Shukla. Sensing Tools and Techniques for COVID-19: Developments and Challenges in Analysis and Detection of Coronavirus. Elsevier, 2022.

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Madhu, G., Sandeep Kautish, A. Govardhan, and Avinash Sharma, eds. Emerging Computational Approaches in Telehealth and Telemedicine: A Look at The Post-COVID-19 Landscape. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150792721220101.

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This book gives an overview of innovative approaches in telehealth and telemedicine. The Goal of the content is to inform readers about recent computer applications in e-health, including Internet of Things (IoT) and Internet of Medical Things (IoMT) technology. The 9 chapters will guide readers to determine the urgency to intervene in specific medical cases, and to assess risk to healthcare workers. The focus on telehealth along with telemedicine, encompasses a broader spectrum of remote healthcare services for the reader to understand. Chapters cover the following topics: - A COVID-19 care s
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Daimon P. Simmons MD PhD and Peter H. Schur MD. Detection of SARS-CoV-2 Antibodies in Diagnosis and Treatment of COVID-19, An Issue of the Clinics in Laboratory Medicine. Elsevier, 2022.

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Deruelle, Thibaud. The Paradox of Communicable Diseases Governance in the EU. Oxford University PressOxford, 2025. https://doi.org/10.1093/9780198951339.001.0001.

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Abstract The European Centre for Disease Prevention and Control (ECDC) is an EU agency responsible for detecting and assessing communicable diseases. However, due to member states’ reluctance to relinquish control over public health, the Centre’s powers have historically been limited, including a ban on offering advice about how to manage public health risks. During the Covid-19 pandemic, the ECDC’s mandate was expanded, formally ending the paradox of assessing threats without being allowed to provide guidance on how to address them. Yet, even prior to this change, the Centre had occasionally
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Book chapters on the topic "COVID-19 detection"

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Caetano, Fabio Roberto, Marcia Gabriela Pianaro Valenga, Dhésmon Lima, Bruno C. Janegitz, Márcio F. Bergamini, and Luiz H. Marcolino-Junior. "Microfluidic Devices with Electrochemical Detection Towards Covid-19 Detection." In COVID-19 Metabolomics and Diagnosis. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-15889-6_2.

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Sharif, Shahzad, Maham Saeed, Javed Hussain Shah, et al. "Detection Assays and Techniques Against COVID-19." In The Covid-19 Pandemic. Apple Academic Press, 2022. http://dx.doi.org/10.1201/9781003283607-5.

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Hassan, Syed Ale, Sahar Gull, Shahzad Akbar, Israr Hanif, Sajid Iqbal, and Muhammad Waqas Aziz. "Artificial Intelligence in Coronavirus Detection." In Intelligent Computing Applications for COVID-19. CRC Press, 2021. http://dx.doi.org/10.1201/9781003141105-2.

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Ünal, Serhat, Yeşeren Saylan, Özge Altıntaş, Seçkin Kılıç, and Adil Denizli. "COVID-19 Detection with Plasmonic Nanosensors." In Plasmonic Nanosensors for Biological and Chemical Threats. CRC Press, 2024. http://dx.doi.org/10.1201/9781003459316-14.

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Gandomkar, Z., P. C. Brennan, and M. E. Suleiman. "Optimizing Radiologic Detection of COVID-19." In Artificial Intelligence in Medicine. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58080-3_285-1.

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Gandomkar, Z., P. C. Brennan, and M. E. Suleiman. "Optimizing Radiologic Detection of COVID-19." In Artificial Intelligence in Medicine. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-64573-1_285.

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Rani, Muthu Vairavan, and Arunkumar. "Thermal Camera-Based COVID-19 Detection." In Advances in Intelligent Systems and Computing. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7330-6_30.

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Madhavi, K. R., G. Madhavi, C. V. Krishnaveni, and Padmavathi Kora. "COVID-19 Detection Using Deep Learning." In Hybrid Intelligent Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73050-5_26.

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Rai, Manjeet, Sudhanshu Saini, and Arvind Dagur. "Covid 19 Detection Using Advanced CNN." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4860-0_20.

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da Costa Oliveira, Thiago, Giovana Rosso Cagnani, and Frank Nelson Crespilho. "Carbon Nanomaterials for Electrochemical Detection of SARS-CoV-2 Infections." In Covid-19 Metabolomics and Diagnosis. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27922-5_3.

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Conference papers on the topic "COVID-19 detection"

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Li, Qingqiu, Runtian Yuan, Junlin Hou, et al. "Advancing COVID-19 Detection in 3D CT Scans." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2024. http://dx.doi.org/10.1109/cvprw63382.2024.00522.

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V, Punya Prabha, M. D. Nandeesh, and Tejaswini S. "Detection of COVID-19 based on Deep Learning." In 2024 International Conference on IoT, Communication and Automation Technology (ICICAT). IEEE, 2024. https://doi.org/10.1109/icicat62666.2024.10923176.

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Shaik, A., J. Suram, and R. Dugyala. "Symptomatic Covid-19 detection." In 4th Smart Cities Symposium (SCS 2021). Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/icp.2022.0338.

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Maurya, Parul. "COVID-19 Face Mask Detection." In 2nd International Conference on Advanced Research in Science, Engineering and Technology. Acavent, 2021. http://dx.doi.org/10.33422/2nd.icarset.2021.03.127.

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Glandt, Kyle, Sarthak Khanal, Yingjie Li, Doina Caragea, and Cornelia Caragea. "Stance Detection in COVID-19 Tweets." In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.acl-long.127.

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Srivastava, Rohit, R. P. Mishra, Vivek Kumar, Himanshu Kumar Shukla, Neha Goyal, and Chandrabhan Singh. "Android Malware Detection Amid COVID-19." In 2020 9th International Conference System Modeling and Advancement in Research Trends (SMART). IEEE, 2020. http://dx.doi.org/10.1109/smart50582.2020.9337105.

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Vanitha, V., R. Srinidhi, R. Darshana, and S. K. M. Nivetha. "COVID-19 Detection using CT-Scan." In 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT). IEEE, 2022. http://dx.doi.org/10.1109/gcat55367.2022.9972136.

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Srivastava, Rahul S., Abhishek R, Rahul P O, J. S. Noor Mohammed, Shoaib Kamal, and Trupthi Rao. "COVID-19 Detection Using Deep Learning." In 2023 International Conference on Computational Intelligence for Information, Security and Communication Applications (CIISCA). IEEE, 2023. http://dx.doi.org/10.1109/ciisca59740.2023.00076.

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Patgar, Chitra Chandrashekhar, Diksha Dinesh Patil, Shweta Hemant Rahate, and Santosh Randive. "Covid-19 Detection using Deep Learning." In 2022 International Conference on Signal and Information Processing (IConSIP). IEEE, 2022. http://dx.doi.org/10.1109/iconsip49665.2022.10007465.

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Jebur, Sabah Abdulazeez, Mohanad Ali Mohammed, and Alia Karim Abdulhassan. "Covid-19 detection using medical images." In AL-KADHUM 2ND INTERNATIONAL CONFERENCE ON MODERN APPLICATIONS OF INFORMATION AND COMMUNICATION TECHNOLOGY. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0119758.

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Reports on the topic "COVID-19 detection"

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Moayeri, Nader. On the Feasibility of COVID-19 Proximity Detection Using Bluetooth Low Energy Signals. National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.ir.8437.

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Campi, Mercedes, and Marco Dueñas. Clusters and Resilience during the COVID–19 Crisis: Evidence from Colombian Exporting Firms. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004474.

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In this paper, we characterize the geography of Colombian exporting clusters and analyze how the COVID-19 crisis has affected Colombian exporters. We contribute to the industrial clusters literature by defining exporting clusters with bipartite network analysis and community detection tools. The methodology allows us to empirically detect product clusters, which are compared with an alternative definition of industrial clusters, and to consider the centrality of firms within clusters. Then, we analyze the firms trade margins during the COVID-19 crisis to evaluate whether belonging to an export
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Stall, Nathan M., Kevin A. Brown, Antonina Maltsev, et al. COVID-19 and Ontario’s Long-Term Care Homes. Ontario COVID-19 Science Advisory Table, 2021. http://dx.doi.org/10.47326/ocsat.2021.02.07.1.0.

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Key Message Ontario long-term care (LTC) home residents have experienced disproportionately high morbidity and mortality, both from COVID-19 and from the conditions associated with the COVID-19 pandemic. There are several measures that could be effective in preventing COVID-19 outbreaks, hospitalizations, and deaths in Ontario’s LTC homes, if implemented. First, temporary staffing could be minimized by improving staff working conditions. Second, homes could be further decrowded by a continued disallowance of three- and four-resident rooms and additional temporary housing for the most crowded h
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Giesen, Christine, Laura Diez-Izquierdo, Cristina Garcia-Fernandez, et al. Detection of Healthcare-Related Infections Due to Multidrug-Resistant Microorganisms in COVID-19 Patients at an Intensive Care Unit in a Secondary Hospital in Spain. Peeref, 2022. http://dx.doi.org/10.54985/peeref.2209p9082550.

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Lalovic, Ivan, Fernando Miralles-Wilhelm, Philipp Grötsch, et al. Remote Sensing Analysis of Water Quality in Four Waterbodies of Latin America. Edited by Eveline Vasquez and José Rosales. Banco Interamericano de Desarrollo, 2024. http://dx.doi.org/10.18235/0005498.

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The pilot study introduces remote sensing methods for monitoring water quality to measure, understand, and manage impacts on vulnerable water bodies that are part of the IDBs Water and Sanitation portfolio. The water bodies selected for this study include: Guanabara Bay in Río de Janeiro, Brazil; Lake Titicaca in Bolivia and Peru; Ypacaraí Lake near Asunción, Paraguay; and the Río Reconquista Basin near Buenos Aires, Argentina. This study focuses on the development and implementation of an automated remote sensing data processing chain enabling detection of phytoplankton abundance (chlorophyll
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Sills, David. Northern Tornadoes Project. Annual Report 2021. Western Libraries, Western University for Northern Tornadoes Project, 2022. http://dx.doi.org/10.5206/ntpar1003.

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The Northern Tornado Project’s third year of detecting, assessing and documenting tornadoes and other damaging wind events across Canada saw some interesting extremes – tornadoes in parts of both the Atlantic and Pacific coasts for the first time in decades, an apparent absence of tornadoes on the Prairies over the 60 days with the highest climatological frequency, a record number of significant (EF2+) tornadoes in Ontario, and massive downbursts in NE British Columbia, NW Alberta and SW Northwest Territories associated with an historic ‘heat dome’. On top of this, the COVID-19 pandemic was st
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Quinn, Meghan. Geotechnical effects on fiber optic distributed acoustic sensing performance. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41325.

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Distributed Acoustic Sensing (DAS) is a fiber optic sensing system that is used for vibration monitoring. At a minimum, DAS is composed of a fiber optic cable and an optic analyzer called an interrogator. The oil and gas industry has used DAS for over a decade to monitor infrastructure such as pipelines for leaks, and in recent years changes in DAS performance over time have been observed for DAS arrays that are buried in the ground. This dissertation investigates the effect that soil type, soil temperature, soil moisture, time in-situ, and vehicle loading have on DAS performance for fiber opt
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Bryant, C. A., S. A. Wilks, and C. W. Keevil. Survival of SARS-CoV-2 on the surfaces of food and food packaging materials. Food Standards Agency, 2022. http://dx.doi.org/10.46756/sci.fsa.kww583.

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COVID-19, caused by the SARS-CoV-2 virus, was first reported in China in December 2019. The virus has spread rapidly around the world and is currently responsible for 500 million reported cases and over 6.4 million deaths. A risk assessment published by the Foods Standards Agency (FSA) in 2020 (Opens in a new window) concluded that it was very unlikely that you could catch coronavirus via food. This assessment included the worst-case assumption that, if food became contaminated during production, no significant inactivation of virus would occur before consumption. However, the rate of inactiva
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Hall, Linnea, Peter Larramendy, Lena Lee, and Annie Little. Landbird monitoring 2020 annual report: Channel Islands National Park. National Park Service, 2023. http://dx.doi.org/10.36967/2301088.

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The National Park Service (NPS) began monitoring landbirds at Channel Islands National Park in 1993 as part of its long-term inventory and monitoring program. The park?s landbird monitoring later became part of the NPS Inventory and Monitoring Division?s Mediterranean Coast Network long-term monitoring programs. Consequently, landbird monitoring has been conducted in the park during every breeding season since 1993. In this report, we summarize data collected during the 2020 breeding season. Landbird monitoring was conducted between 1 April and 30 June 2020. Using distance-based sampling metho
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