Academic literature on the topic 'Appr. automatico'
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Journal articles on the topic "Appr. automatico"
Ayyal Awwad, Aiman M., and Wolfgang Slany. "Automated Bidirectional Languages Localization Testing for Android Apps with Rich GUI." Mobile Information Systems 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/2872067.
Full textLiao, Hsiu-Li, Chen-Huei Chou, and Wan-Chun Chao. "Functional Validation and Test Automation for Android Apps." International Journal of Machine Learning and Computing 4, no. 6 (2014): 553–58. http://dx.doi.org/10.7763/ijmlc.2014.v6.472.
Full textMao, Jian, Hanjun Ma, Yue Chen, Yaoqi Jia, and Zhenkai Liang. "Automatic permission inference for hybrid mobile apps." Journal of High Speed Networks 22, no. 1 (February 10, 2016): 55–64. http://dx.doi.org/10.3233/jhs-160538.
Full textAdams, Bruce W. "Automation and apps for clinical dental biomechanics." CRANIO® 34, no. 5 (April 7, 2016): 343–47. http://dx.doi.org/10.1080/08869634.2015.1113689.
Full textLuo, Qian, Jiajia Liu, Jiadai Wang, Yawen Tan, Yurui Cao, and Nei Kato. "Automatic Content Inspection and Forensics for Children Android Apps." IEEE Internet of Things Journal 7, no. 8 (August 2020): 7123–34. http://dx.doi.org/10.1109/jiot.2020.2982248.
Full textJordan, T. R., T. Welle, and M. D. Byrne. "Comparison of Manual versus Automated Data Collection Method for an Evidence-Based Nursing Practice Study." Applied Clinical Informatics 04, no. 01 (2013): 61–74. http://dx.doi.org/10.4338/aci-2012-09-ra-0037.
Full textAakre, Christopher, Mikhail Dziadzko, Mark Keegan, and Vitaly Herasevich. "Automating Clinical Score Calculation within the Electronic Health Record." Applied Clinical Informatics 08, no. 02 (April 2017): 369–80. http://dx.doi.org/10.4338/aci-2016-09-ra-0149.
Full textAltomare, Angela, Rocco Caliandro, Mercedes Camalli, Corrado Cuocci, Carmelo Giacovazzo, Anna Grazia Giuseppina Moliterni, and Rosanna Rizzi. "Automatic structure determination from powder data withEXPO2004." Journal of Applied Crystallography 37, no. 6 (November 11, 2004): 1025–28. http://dx.doi.org/10.1107/s0021889804021417.
Full textRauch, Edgar F., and Laurent Dupuy. "Comments on`On the reliability of fully automatic indexing of electron diffraction patterns obtained in a transmission electron microscope'by Morawiec & Bouzy (2006)." Journal of Applied Crystallography 39, no. 1 (January 12, 2006): 104–5. http://dx.doi.org/10.1107/s0021889805033157.
Full textChen, Junhan. "MiniWarner: An Novel and Automatic Malicious Phishing Mini-apps Detection Approach." Computer and Information Science 15, no. 1 (January 21, 2022): 57. http://dx.doi.org/10.5539/cis.v15n1p57.
Full textDissertations / Theses on the topic "Appr. automatico"
ZINI, SIMONE. "Image Enhancement and Restoration using Machine Learning Techniques." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/378899.
Full textDigital cameras record, manipulate, and store information electronically through sensors and built-in computers, which makes photography more available to final users which do not anymore need to rely on the use of chemicals and knowledge of mechanical procedures to develop their pictures. Different types of degradation and artifacts can affect images acquired using digital cameras, decreasing the perceptual fidelity of images and making harder many image processing and analysis tasks that can be performed on the collected images. Three elements can be identified as possible sources of artifacts in an image: the scene content, the hardware limitations and flaws, and finally the operations performed by the digital camera processing pipeline itself, from acquisition to compression and storing. Some artifacts are not directly treated in the typical camera processing pipeline, such as the presence of haze or rain that can reduce visibility of the scene in the depicted images. These artifacts require the design of ad hoc methods that are usually applied as post-processing on the acquired images. Other types of artifacts are related to the imaging process and to the image processing pipeline implemented on board of digital cameras. These include sensor noise, undesirable color cast, poor contrast and compression artifacts. The objective of this thesis is the identification and design of new and more robust modules for image processing and restoration that can improve the quality of the acquired images, in particular in critical scenarios such as adverse weather conditions, poor light in the scene etc… . The artifacts identified are divided into two main groups: “in camera-generated artifacts" and “external artifacts and problems". In the first group it has been identified and addressed four main issues: sensor camera noise removal, automatic white balancing, automatic contrast enhancement and compression artifacts removal. The design process of the proposed solutions has considered efficiency aspects, due to the possibility of directly integrating them in future camera pipelines. The second group of artifacts are related to the presence of elements in the scene which may cause a degradation in terms of visual fidelity and/or usability of the images. In particular the focus is on artifacts induced by the presence of rain in the scene. The thesis, after a brief review of the digital camera processing pipeline, analyzes the different types of artifacts that can affect image quality, and describes the design of the proposed solutions. All the proposed approaches are based on machine learning techniques, such as Convolutional Neural Networks and Bayesian optimization procedure, and are experimentally validated on standard images datasets. The overall contributions of this thesis can be summarized in three points: integration of classical imaging approaches with machine learning optimization techniques, design of novel deep learning architectures and approaches and analysis and application of deep learning image processing algorithms in other computer vision tasks.
Kerov, Ghiglianovich Claudio. "Rilevazione automatica di attacchi in architetture antifragili." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
Find full textGlanz, Leonid Verfasser], Mira [Akademischer Betreuer] [Mezini, and Awais [Akademischer Betreuer] Rashid. "Automatic Identification and Recovery of Obfuscated Android Apps / Leonid Glanz ; Mira Mezini, Awais Rashid." Darmstadt : Universitäts- und Landesbibliothek, 2020. http://d-nb.info/1224048601/34.
Full textGlanz, Leonid [Verfasser], Mira [Akademischer Betreuer] Mezini, and Awais [Akademischer Betreuer] Rashid. "Automatic Identification and Recovery of Obfuscated Android Apps / Leonid Glanz ; Mira Mezini, Awais Rashid." Darmstadt : Universitäts- und Landesbibliothek, 2020. http://d-nb.info/1224048601/34.
Full textBecaccia, Morris. "Machine Learning per il riconoscimento automatico delle attività umane da smartphone: una valutazione sperimentale." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19576/.
Full textBhatt, Mrunal Dipakkumar Bhatt. "INTELLIGENT VOICE ACTIVATED HOME AUTOMATION (IVA)." Cleveland State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=csu1463517275.
Full textMácha, Tomáš. "Využití nástroje MATLAB Coder pro automatické generování C kódu pro mikrokontroléry dsPIC." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-402535.
Full textAsher, Natali. "A Warmer Welcome : Application of a Chatbot as a Facilitator for New Hires Onboarding." Thesis, Linnéuniversitetet, Institutionen för medieteknik (ME), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-65887.
Full textChen, You-Syuan, and 陳佑宣. "Automatic Testing of Android Apps Using JUnit Framework." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/77277880696331330896.
Full text開南大學
資訊管理學系
103
App development for smart phones and tablets is one of the hottest technologies in recent years. As the app can be downloaded and updated via the Internet, the revision of the software is much faster than the traditional PC software. How to use tools to improve development efficiency and program quality becomes more and more important. Testing is a necessary phase in software development. This paper discusses how to use JUnit Framework to test Android apps automatically, including the creation of testing classes and test cases. We use three different types of Apps in our experiments. One is the Contact App that uses the SQLite database access functions to save the profile data; the second is a Service, whichcan execute in the background; the third app is a Content Provider app. We implemented automatic test classes and test cases for them, and compared the efficiency of automatic testing and human testing. Experimental results show that automatic testing can significantly reduce the time spent on testing and reduce the physical and mental burden of testers. Besides, automatic testing can also avoid erroneous operations. The test cases can also be used in the future when the program is modified, and they can be used as auxiliary program documentation. Our study shows that the automatic testing technology can effectively improve the development efficiency and the app quality.
Glanz, Leonid. "Automatic Identification and Recovery of Obfuscated Android Apps." Phd thesis, 2020. https://tuprints.ulb.tu-darmstadt.de/14647/7/Thesis_Leonid_Glanz.pdf.
Full textBooks on the topic "Appr. automatico"
Introduction to Google apps--productivity apps. Boston: Pearson, 2012.
Find full textInstitute, Pennsylvania Bar. Smartphones and mobile apps for lawyers. Mechanicsburg, Pennsylvania: Pennsylvania Bar Institute, 2015.
Find full textAssociation, American Bar, ed. Ipad apps in one hour for lawyers. Chicago, Ill: American Bar Association, 2012.
Find full textLegal practice in the digital age: The quest for the killer legal app. London: Bowerdean Pub. Co. Ltd., 1998.
Find full textservice), SpringerLink (Online, ed. Auditing and GRC Automation in SAP. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.
Find full textNitin, Indurkhya, and Zhang Tong 1971-, eds. Fundamentals of predictive text mining. London: Springer-Verlag, 2010.
Find full textMařík, Vladimír. Holonic and multi-agent systems for manufacturing: Proceedings. Berlin: Springer, 2003.
Find full textTest IOS Apps with UI Automation. The Pragmatic Programmers, 2013.
Find full textIntroducing Microsoft Flow: Automating Workflows Between Apps and Services. Apress, 2018.
Find full textClark, Mike. Pragmatic Project Automation: How to Build, Deploy, and Monitor Java Apps. The Pragmatic Programmers, 2004.
Find full textBook chapters on the topic "Appr. automatico"
Lopatin, Ben. "Automating." In Django Standalone Apps, 145–50. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5632-9_21.
Full textGarg, Shankar. "Automating Different Apps." In Appium Recipes, 49–76. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2418-2_3.
Full textRelan, Kunal. "Automating App Testing." In iOS Penetration Testing, 97–118. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2355-0_6.
Full textGupta, Rakesh. "Automating Business Processes." In Salesforce Platform App Builder Certification, 145–88. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5479-0_6.
Full textChandrasekara, Chaminda, and Pushpa Herath. "Functional Testing for Windows Apps." In Hands-On Functional Test Automation, 119–54. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4411-1_4.
Full textMaskrey, Molly K. "Home Automation Project." In App Development Recipes for iOS and watchOS, 461–504. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1820-4_16.
Full textRosenthal, Hanaan. "Scripting Apple Apps." In AppleScript: A Comprehensive Guide to Scripting and Automation on Mac OS X, 697–714. Berkeley, CA: Apress, 2004. http://dx.doi.org/10.1007/978-1-4302-5352-5_25.
Full textStefanovic, Vladimir, and Milos Katinski. "App Service and Containers in Azure Compute." In Pro Azure Administration and Automation, 97–125. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-7325-8_5.
Full textZhang, Mu, and Heng Yin. "Automatic Generation of Security-Centric Descriptions for Android Apps." In SpringerBriefs in Computer Science, 77–98. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47812-8_6.
Full textKapoor, Sheetika, Kalpna Sagar, and B. V. R. Reddy. "Speedroid: A Novel Automation Testing Tool for Mobile Apps." In International Conference on Innovative Computing and Communications, 271–85. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2354-6_29.
Full textConference papers on the topic "Appr. automatico"
Zhou, Chenyu, Xian Zhan, Linlin Li, and Yepang Liu. "Automatic Maturity Rating for Android Apps." In Internetware 2022: 13th Asia-Pacific Symposium on Internetware. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3545258.3545282.
Full textDai, Shuaifu, Alok Tongaonkar, Xiaoyin Wang, Antonio Nucci, and Dawn Song. "NetworkProfiler: Towards automatic fingerprinting of Android apps." In IEEE INFOCOM 2013 - IEEE Conference on Computer Communications. IEEE, 2013. http://dx.doi.org/10.1109/infcom.2013.6566868.
Full textGao, Cuiyun, Jichuan Zeng, Xin Xia, David Lo, Michael R. Lyu, and Irwin King. "Automating App Review Response Generation." In 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2019. http://dx.doi.org/10.1109/ase.2019.00025.
Full textYaqoob, Shamrose, and Salman Ali Khan. "COVID-19 Case Manager App for Oil & Gas Companies." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207329-ms.
Full textLin, Jun-Wei, Navid Salehnamadi, and Sam Malek. "Test automation in open-source Android apps." In ASE '20: 35th IEEE/ACM International Conference on Automated Software Engineering. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3324884.3416623.
Full textLi, Xiujiang, Yanyan Jiang, Yepang Liu, Chang Xu, Xiaoxing Ma, and Jian Lu. "User Guided Automation for Testing Mobile Apps." In 2014 21st Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2014. http://dx.doi.org/10.1109/apsec.2014.13.
Full textKim, Soohyun, Hyunsu Mun, and Youngseok Lee. "Automatic Mobile App Speed Measurement with Robot." In 2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2020. http://dx.doi.org/10.23919/apnoms50412.2020.9236980.
Full textVargas Orjuela, Mario Andres, Alvaro Uribe-Quevedo, Norman Jaimes, and Byron Perez-Gutierrez. "External automatic defibrillator game-based learning app." In 2015 IEEE Games Entertainment Media Conference (GEM). IEEE, 2015. http://dx.doi.org/10.1109/gem.2015.7377206.
Full textGreenheld, Georgia, Bastin Tony Roy Savarimuthu, and Sherlock A. Licorish. "Automating Developers' Responses to App Reviews." In 2018 25th Australasian Software Engineering Conference (ASWEC). IEEE, 2018. http://dx.doi.org/10.1109/aswec.2018.00017.
Full textFairhurst, Stuart R., Sara R. Koehler-McNicholas, Billie C. S. Slater, Eric A. Nickel, Karl A. Koester, Gregory O. Voss, Andrew H. Hansen, and John E. Ferguson. "Improving Automatic Control of an Ankle-Foot Prosthesis Using Machine Learning Algorithms." In 2017 Design of Medical Devices Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dmd2017-3464.
Full textReports on the topic "Appr. automatico"
Boruchowicz, Cynthia, Florencia López Bóo, Benjamin Roseth, and Luis Tejerina. Default Options: A Powerful Behavioral Tool to Increase COVID-19 Contact Tracing App Acceptance in Latin America? Inter-American Development Bank, December 2020. http://dx.doi.org/10.18235/0002983.
Full textLeitfaden für Aussagekräftige Metadaten. WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH, 2019. http://dx.doi.org/10.26128/2021.247.
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