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Bibliografias temáticas / FastAI

Literatura científica selecionada sobre o tema "FastAI"

Autor: Grafiati

Publicado: 23 de junho de 2021

Última modificação: 31 de maio de 2022

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Artigos de revistas
Teses / dissertações
Livros
Capítulos de livros
Trabalhos de conferências
Relatórios de organizações

Artigos de revistas sobre o assunto "FastAI":

1

Antić, Jovana. "KLASIFIKACIJA SLIKA PRIMENOM FASTAI BIBLIOTEKE". Zbornik radova Fakulteta tehničkih nauka u Novom Sadu 35, n.º 06 (26 de maio de 2020): 1062–65. http://dx.doi.org/10.24867/08be13antic.

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2

Howard, Jeremy, e Sylvain Gugger. "Fastai: A Layered API for Deep Learning". Information 11, n.º 2 (16 de fevereiro de 2020): 108. http://dx.doi.org/10.3390/info11020108.

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fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying patterns of many deep learning and data processing techniques in terms of decoupled abstractions. These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library. fastai includes: a new type dispatch system for Python along with a semantic type hierarchy for tensors; a GPU-optimized computer vision library which can be extended in pure Python; an optimizer which refactors out the common functionality of modern optimizers into two basic pieces, allowing optimization algorithms to be implemented in 4–5 lines of code; a novel 2-way callback system that can access any part of the data, model, or optimizer and change it at any point during training; a new data block API; and much more. We used this library to successfully create a complete deep learning course, which we were able to write more quickly than using previous approaches, and the code was more clear. The library is already in wide use in research, industry, and teaching.

3

Sieczka, Rafał, e Maciej Pańczyk. "Blender as a tool for generating synthetic data". Journal of Computer Sciences Institute 16 (30 de setembro de 2020): 227–32. http://dx.doi.org/10.35784/jcsi.2086.

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Acquiring data for neural network training is an expensive and labour-intensive task, especially when such data isdifficult to access. This article proposes the use of 3D Blender graphics software as a tool to automatically generatesynthetic image data on the example of price labels. Using the fastai library, price label classifiers were trained ona set of synthetic data, which were compared with classifiers trained on a real data set. The comparison of the resultsshowed that it is possible to use Blender to generate synthetic data. This allows for a significant acceleration of thedata acquisition process and consequently, the learning process of neural networks.

4

Kaliyugarasan, Satheshkumar, Arvid Lundervold e Alexander Selvikvåg Lundervold. "Pulmonary Nodule Classification in Lung Cancer from 3D Thoracic CT Scans Using fastai and MONAI". International Journal of Interactive Multimedia and Artificial Intelligence 6, n.º 7 (2021): 83. http://dx.doi.org/10.9781/ijimai.2021.05.002.

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5

Vulli, Adarsh, Parvathaneni Naga Srinivasu, Madipally Sai Krishna Sashank, Jana Shafi, Jaeyoung Choi e Muhammad Fazal Ijaz. "Fine-Tuned DenseNet-169 for Breast Cancer Metastasis Prediction Using FastAI and 1-Cycle Policy". Sensors 22, n.º 8 (13 de abril de 2022): 2988. http://dx.doi.org/10.3390/s22082988.

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Lymph node metastasis in breast cancer may be accurately predicted using a DenseNet-169 model. However, the current system for identifying metastases in a lymph node is manual and tedious. A pathologist well-versed with the process of detection and characterization of lymph nodes goes through hours investigating histological slides. Furthermore, because of the massive size of most whole-slide images (WSI), it is wise to divide a slide into batches of small image patches and apply methods independently on each patch. The present work introduces a novel method for the automated diagnosis and detection of metastases from whole slide images using the Fast AI framework and the 1-cycle policy. Additionally, it compares this new approach to previous methods. The proposed model has surpassed other state-of-art methods with more than 97.4% accuracy. In addition, a mobile application is developed for prompt and quick response. It collects user information and models to diagnose metastases present in the early stages of cancer. These results indicate that the suggested model may assist general practitioners in accurately analyzing breast cancer situations, hence preventing future complications and mortality. With digital image processing, histopathologic interpretation and diagnostic accuracy have improved considerably.

6

Ulum, Muchamad Eris Rizqul, Joko Purnomo, Elfitrin Syahrul e Erfiana Wahyuningsih. "Implementation of Machine Learning using Fastai for Image Classification on the Automatic Waste Sorter Prototype". International Journal of Computer Applications 184, n.º 7 (20 de abril de 2022): 1–8. http://dx.doi.org/10.5120/ijca2022922026.

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7

Tian, Bin, Bin Meng, Juan Wang, Guoqing Zhi, Zhenyu Qi, Siyu Chen e Jian Liu. "Spatio-Temporal Patterns of Fitness Behavior in Beijing Based on Social Media Data". Sustainability 14, n.º 7 (30 de março de 2022): 4106. http://dx.doi.org/10.3390/su14074106.

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Fitness is an important way to ensure the health of the population, and it is important to actively understand fitness behavior. Although social media Weibo data (the Chinese Tweeter) can provide multidimensional information in terms of objectivity and generalizability, there is still more latent potential to tap. Based on Sina Weibo social media data in the year 2017, this study was conducted to explore the spatial and temporal patterns of urban residents’ different fitness behaviors and related influencing factors within the Fifth Ring Road of Beijing. FastAI, LDA, geodetector technology, and GIS spatial analysis methods were employed in this study. It was found that fitness behaviors in the study area could be categorized into four types. Residents can obtain better fitness experiences in sports venues. Different fitness types have different polycentric spatial distribution patterns. The residents’ fitness frequency shows an obvious periodic distribution (weekly and 24 h). The spatial distribution of the fitness behavior of residents is mainly affected by factors, such as catering services, education and culture, companies, and public facilities. This research could help to promote the development of urban residents’ fitness in Beijing.

8

Hawley, Scott H. "Development tools for deep learning models of acoustical signal processing". Journal of the Acoustical Society of America 151, n.º 4 (abril de 2022): A230. http://dx.doi.org/10.1121/10.0011154.

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We present a survey of available frameworks for developing acoustical signal processing models based on deep neural networks. Given that this is a dynamic space with new frameworks, libraries, and even companies appearing on timescales measured in months, we provide an up-to-date assessment of the strength, popularity, and near-future directions of several tools and platforms available for research and product deployment for deep learning models of audio signal processing. Similarly, those new to these spaces may be unaware of software systems that will allow them to obtain and interrogate results more quickly and easily, while also integrating the nearly state-of-the-art optimization methods. Included tools, packages and platforms include PyTorch, Tensorflow, Keras, JAX, fastai, PyTorch Lightning, Julia, nbdev, HuggingFace, Weights and Biases, and Gradio. Examples will be drawn from the speaker's recent research publications in musical signal processing and computer vision applied to musical acoustics, as well as recent work by others. The goal of the talk is to provide acoustics researchers, educators, students with a set of helpful possibilities for pursuing and improving their understanding, research practices, and communications.

9

Neuner, Christoph, Roland Coras, Ingmar Blümcke, Alexander Popp, Sven M. Schlaffer, Andre Wirries, Michael Buchfelder e Samir Jabari. "A Whole-Slide Image Managing Library Based on Fastai for Deep Learning in the Context of Histopathology: Two Use-Cases Explained". Applied Sciences 12, n.º 1 (21 de dezembro de 2021): 13. http://dx.doi.org/10.3390/app12010013.

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Background: Processing whole-slide images (WSI) to train neural networks can be intricate and labor intensive. We developed an open-source library dealing with recurrent tasks in the processing of WSI and helping with the training and evaluation of neuronal networks for classification tasks. Methods: Two histopathology use-cases were selected and only hematoxylin and eosin (H&E) stained slides were used. The first use case was a two-class classification problem. We trained a convolutional neuronal network (CNN) to distinguish between dysembryoplastic neuroepithelial tumor (DNET) and ganglioglioma (GG), two neuropathological low-grade epilepsy-associated tumor entities. Within the second use case, we included four clinicopathological disease conditions in a multilabel approach. Here we trained a CNN to predict the hormone expression profile of pituitary adenomas. In the same approach, we also predicted clinically silent corticotroph adenoma. Results: Our DNET-GG classifier achieved an AUC of 1.00 for the ROC curve. For the second use case, the best performing CNN achieved an area under the curve (AUC) of 0.97 for the receiver operating characteristic (ROC) for corticotroph adenoma, 0.86 for silent corticotroph adenoma, and 0.98 for gonadotroph adenoma. All scores were calculated with the help of our library on predictions on a case basis. Conclusions: Our comprehensive and fastai-compatible library is helpful to standardize the workflow and minimize the burden of training a CNN. Indeed, our trained CNNs extracted neuropathologically relevant information from the WSI. This approach will supplement the clinicopathological diagnosis of brain tumors, which is currently based on cost-intensive microscopic examination and variable panels of immunohistochemical stainings.

10

Jakab, Balázs, Boudewijn van Leeuwen e Zalán Tobak. "Detection of Plastic Greenhouses Using High Resolution Rgb Remote Sensing Data and Convolutional Neural Network". Journal of Environmental Geography 14, n.º 1-2 (1 de abril de 2021): 38–46. http://dx.doi.org/10.2478/jengeo-2021-0004.

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Abstract Agricultural production in greenhouses shows a rapid growth in many parts of the world. This form of intensive farming requires a large amount of water and fertilizers, and can have a severe impact on the environment. The number of greenhouses and their location is important for applications like spatial planning, environmental protection, agricultural statistics and taxation. Therefore, with this study we aim to develop a methodology to detect plastic greenhouses in remote sensing data using machine learning algorithms. This research presents the results of the use of a convolutional neural network for automatic object detection of plastic greenhouses in high resolution remotely sensed data within a GIS environment with a graphical interface to advanced algorithms. The convolutional neural network is trained with manually digitized greenhouses and RGB images downloaded from Google Earth. The ArcGIS Pro geographic information system provides access to many of the most advanced python-based machine learning environments like Keras – TensorFlow, PyTorch, fastai and Scikit-learn. These libraries can be accessed via a graphical interface within the GIS environment. Our research evaluated the results of training and inference of three different convolutional neural networks. Experiments were executed with many settings for the backbone models and hyperparameters. The performance of the three models in terms of detection accuracy and time required for training was compared. The model based on the VGG_11 backbone model (with dropout) resulted in an average accuracy of 79.2% with a relatively short training time of 90 minutes, the much more complex DenseNet121 model was trained in 16.5 hours and showed a result of 79.1%, while the ResNet18 based model showed an average accuracy of 83.1% with a training time of 3.5 hours.

Mais fontes

Teses / dissertações sobre o assunto "FastAI":

1

Панченко, І. О. Н. М. Голего. "Програмний засіб автоматичного визначення вподобань відвідувачів веб-порталів". Thesis, Національний авіаційний університет, 2020. https://er.nau.edu.ua/handle/NAU/51153.

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Завдання рекомендаційної системи – проінформувати користувача про товар, який йому може бути найбільш цікавий в даний момент часу. Клієнт отримує інформацію, а сервіс заробляє на наданні якісних послуг. Персоналізація онлайн-маркетингу - очевидний тренд останнього десятиліття. По оцінкам Маккінсі, 35% виручки Amazon або 75% Netflix припадає саме на рекомендовані товари і відсоток цей, ймовірно, буде рости.

2

Nicklasson, Emma, e Erik Nyqvist. "Ansiktsautentiseringssystem med neuralt nätverk : Baserat på bildklassificering". Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-84338.

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Ansiktsigenkänning med hjälp av maskininlärning är ett växande område och används i många sammanhang i dagens samhälle, till exempel som autentiseringsmetod i mobiltelefoner. De flesta system för ansiktsigenkänning har haft stor budget och starka utvecklare bakom sig, men går det att skapa ett fungerande system med begränsade resurser och datamängd? Det här projektet undersöker hur mycket data som krävs för att producera en fungerande ansiktsautentiseringssmodul för kontorsmiljö baserad på bildklassificering. I projektet används ett förtränat Convolutional Neural Network (ResNet34), data som är insamlad med hjälp av uppdragsgivaren samt en bilddatabas från NVIDIA. Resultaten visar att mängden data som krävs för att producera en tillförlitlig modell troligtvis överstiger den mängd som är rimlig att samla in från användaren.
Face recognition using machine learning is a changing field and is used in many contexts in today’s society, for example as an authentication method in mobile phones. Most face recognition systems have had large budgets and strong developers behind them, but is it possible to create a working system with a limited amount of resourses and data? This project investigates how much data is required to produce a working face recognition module for an office environment based on image classification. This project used a pretrained Convolutional Neural Network (ResNet34), data collected with the help of the client, and an image database from NVIDIA. The results show that the amount of data required to produce and reliable model probably exceeds the amount that is reasonable to collect from the user.

3

Karlsson, Robin. "Taktikanalys Ishockey : Ishockeyns fasta situationer". Thesis, Gymnastik- och idrottshögskolan, GIH, Tränarlänken, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:gih:diva-2293.

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4

Blomdell, Sebastian, e Boström Carl. "Byteskostnader på svenska fasta bredbandsmarknaden". Thesis, Karlstads universitet, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-35351.

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5

Lindström, Joanna, e Frida Wilkman. "Patienters följsamhet till preoperativ fasta". Thesis, Luleå tekniska universitet, Institutionen för hälsovetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-79892.

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Abstrakt Bakgrund: Preoperativ fasta syftar till att minska innehållet- och sänka pH värdet i magsäcken och i sin tur reducera risken för aspiration i samband med induktion. Rekommendationerna som råder idag för preoperativ fasta är sex timmar från fast föda och två timmar från klar vätska. Trots dessa rekommendationer har patienter tendens till att överskrida tiden för fasta från föda respektive vätska vilket kan leda till fysiologiska konsekvenser och postoperativa obehag. Anledningen till detta har bland annat beskrivits bero på bristande information från sjukhus och vårdpersonal. Syfte: Syftet med denna studie var att undersöka patienters följsamhet till preoperativ fasta. Metod: Designen som användes var en kvantitativ ansats med en icke-experimentell retrospektiv design. Urvalet bestod av ett bekvämlighetsurval och sammanlagt deltog 186 personer från arton regioner i Sverige. Deltagarna besvarade en egenkonstruerad webbaserad enkät som var distribuerad via sociala medier och e-post. Elva frågor analyserades i programmet SPSS version 26 och tre öppna frågor analyserades med en kvantitativ innehållsanalys. Resultat: Resultatet visade att deltagarna i snitt fastade från fast föda i tretton timmar respektive vätska i sex timmar och fyrtiotvå minuter. Majoriteten av deltagarna erhöll information om preoperativ fasta från ett informationsblad från sjukhuset eller från vårdpersonal och de flesta av deltagarna upplevde informationen som tydlig eller mycket tydlig. En vanlig känsla hos deltagarna som upplevdes inför operation var oro. Den främsta orsaken och konsekvensen till varför man ska fasta inför operation beskrev deltagarna bero på aspiration eller kräkning. De främsta riskerna med lång fasta beskrevs av deltagarna vara fysiologiska konsekvenser men en del av deltagarna mindes inte eller visste inte några risker förenat med en lång fasta. Slutsats: Deltagarna i detta examensarbete upplevde att informationen de erhållit om fasta var tydlig eller mycket tydlig, dock visade resultatet att deltagarnas medeltid för fasta överskred nuvarande rekommendationer. Detta indikerar att informationen som patienter erhåller för preoperativ fasta behöver förbättras. Nyckelord: Följsamhet, Preoperativ, Fasta, Information, Kunskap, Anestesi Keywords: Adherence, Preoperative, Fast, Information, Knowledge, Anesthesia

6

Arvidsson, Sebastian. "RMA och det fasta kustartilleriet : En analys av diskussioner kring RMA och det fasta kustartilleriet". Thesis, Försvarshögskolan, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-2631.

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Under 1990-talet accelererade avvecklingen av det fasta kustartilleriet. Det skedde samtidigt med implementeringen av Revolution in Military Affairs(RMA)-konceptet i Sverige, snabb militärteknisk utvecklingen och Försvarsmaktens omställning från en stor organisation med lång mobilisering till insatsförsvar med hög beredskap. Syftet med studien är att med hjälp av argumentationsanalys och kvalitativ textanalys, studera relationen mellan RMA och avvecklingen av fasta kustartilleriet, genom analys av Kungliga Krigsvetenskaps Akademiens Handlingar och Tidskrifter. Resultatet visar att fast kustartilleri spelar en viktig roll även i en värld präglad av RMA och modern teknologi. Det fasta kustartilleriet ersattes av rörligt. Även detta avvecklades i förtid.
During the 1990´s the liquidation of coastal fortifications accelerated. During the same period of time the concept of Revolution in Military Affairs is being implemented in Sweden, military technology is rapidly evolving and Swedish Armed Forces is transforming its organization from a large quantity - long mobilization, to a small mission-based armed force with high response. The purpose of the study is to analyze the relation between RMA and the liquidation of the coastal fortifications, through argumentative analysis and qualitative text analysis, by studying the publications of the Royal Swedish Academy of War Sciences. The result shows that costal fortifications are important even in a world characterized by RMA and modern technology. The costal fortifications were replaced by mobile units. They got liquidated before there time as well.

7

Eriksson, Freya. "Fasta uttryck i svenskt barnriktat tal". Thesis, Stockholms universitet, Institutionen för lingvistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-131237.

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Fasta uttryck definieras i den här studien som ordsekvenser som helt eller delvis finns lagrade i det mentala lexikonet, vilket både innefattar idiom och mer flexibla uttryck där vissa enheter kan bytas ut mot andra. Användningen av fasta uttryck i vuxenriktat tal har undersökts mycket, och är något som förekommer ofta. När det gäller fasta uttryck i barnriktat tal har det föreslagits att det är en hjälp för språkutvecklingen, i och med att barnen får ramar att sätta in nya ord i, samtidigt som det precis som hos vuxna tros underlätta processandet av språket. I den här studien undersöks användningen av fasta uttryck i svenskt barnriktat tal under det första levnadsåret och vid 24 månaders ålder hos 10 förälder-barndyader. Syftet är att utröna både hur användningen ser ut gällande kvantitet och kvalitet och om det finns ett samband mellan användningen av fasta uttryck och barnens produktiva ordförråd vid 30 månaders ålder. Resultaten visade en stor variation i hur många fasta uttryck som användes, men fördelningen mellan de olika kategorierna var snarlik hos föräldrarna. Gällande ett eventuellt samband mellan användningen av fasta uttryck och barnens språkutveckling hittades inga signifikanta resultat.

8

Edvinsson, Johan. "Slaget om Liège : lärdomar från fasta försvar". Thesis, Försvarshögskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-1607.

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I augusti 1914 invaderade Tyskland sitt västra grannland Belgien, som förklarat sig neutralt i konflikten mellan centralmakterna och de allierade. Belgarnas försvar byggde på den uttalade politiska viljan att vara neutral och var därför inte kraftsamlat i någon riktning. Tysklands anfall inleddes med en attack på de stora fasta försvarsanläggningarna vid Liège. Försvaret var knutet till de fasta försvarsanläggningarna uppförda 40 år tidigare. Trots relativt små medel och dåliga förberedelser lyckades försvararna göra väl ifrån sig. Nyttjandet av fasta försvarsanläggningar är gammalt men det finns fortfarande mycket lärdom att dra. Den här uppsatsen är en teoribildande fallstudie baserad på kvalitativ litteraturstudie. Därför beskrivs slaget i förhållande till fördelar och nackdelar med nyttjandet av fasta försvarsanläggningar. Jag presenterar också ett försök att dra rimliga slutsatser ur det som inträffat som mynnar ut i en teori. Den viktigaste slutsatsen kan sammanfattas med att fasta försvarsanläggningar kommer bäst till sin rätt när de nyttjas av förband vars uppgift gör dem oberoende av hög rörlighet men ställer krav på hög verkan med kvantitativt liten trupp. De gör sig sämst då involverade med stora fältförband med uppgifter som ställer krav på mobilitet och knappa tidsförhållanden
Germany invaded its western neighbour Belgium in august 1914. Belgium had declared herself neutral in the conflict between the central powers and the allied but was still invaded. The Belgian defence revolved largely around the political will to remain neutral and was therefore ill prepared in either direction. Germany’s first attack struck at the great fortresses outside Liège. The defence of this town was tied to the local forts, which had been erected some 40 years before. The outnumbered defenders with poorly executed preparations were able to perform well against the German might. The use of forts is an old practice in war but there are still lessons to be learned from its utilisation. This study is a theory constructive case study based on a quality text study. Therefore, the battle with its pros and cons of the use of forts are presented in an attempt to derive reasonable conclusions towards the use of fixed fortifications These facts led me to form a foundation of a theory on the usefulness of fixed fortifications.

9

Fasterud, Kamilla, e Mirjana Milinkovic. "Evidensbaserad omvårdnad i samband med preoperativ fasta". Thesis, Halmstad University, School of Social and Health Sciences (HOS), 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-949.

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Patienter ska fasta inför elektiv kirurgi på grund av risken för kräkning och aspiration av ventrikelinnehållet till lungorna, oberoende av anestesimetod. Under de senaste decennierna har forskning gjorts angående preoperativ fasta och därigenom har riktlinjerna förändrats mot en mer liberal riktning. I den kliniska verksamheten är det idag mer regel än undantag att fasta från midnatt för patienter som ska genomgå elektiv kirurgi på förmiddagen och tidig eftermiddag, vilket dock inte styrks av evidens utan baseras mer på erfarenheter. Det finns stark evidens som stödjer att preoperativ fasta borde vara två timmar för vätska och sex timmar för fast föda. Sjuksköterskan är den som är ansvarig för patienternas omvårdnad i den kliniska verksamheten. Det är viktigt att sjuksköterskan gör en preoperativ bedömning av nutritions- och vätskestatus. Sjuksköterskans kliniska bedömning har stor betydelse för hur patienterna klarar det pre-, peri- och postoperativa förloppet. Syftet med litteraturstudien var att belysa användningen av evidensbaserad omvårdnad i samband med preoperativ fasta. Sökning av vetenskapliga artiklar gjordes i databaserna CINAHL och PubMed. Ur resultatet framkommer det att genomsnittstiden för preoperativ fasta fortfarande är 11-14 timmar. De vanligaste orsakerna till varför evidensen brister är ostrukturerade operationsprogram och oklara riktlinjer. Enligt lagar och författningar, ska sjuksköterskor kritiskt reflektera över rutiner och arbeta evidensbaserat. Ytterligare forskning behövs angående vårdpersonalens följsamhet av riktlinjerna i Sverige, samt om tillämpning av omvårdnadsdiagnoser skulle bidra till att individanpassad omvårdnad prioriteras när det gäller den preoperativa fastans längd.

10

Herbert-Brown, Geraldine. "Ovid and the Fasti : an historical study". Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314889.

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Mais fontes

Livros sobre o assunto "FastAI":

1

Ovid. Fasti. 2^a ed. Cambridge, Mass: Harvard University Press, 1989.

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2

Ovid. Fasti. Cambridge, U.K: Cambridge University Press, 1998.

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3

Ovid. Fasti. London: Penguin Books, 2000.

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4

Ovid. Fasti. 2^a ed. Cambridge, Mass: Harvard University Press, 1996.

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5

Black, Jonah. Faster, Faster, Faster. New York: HarperCollins, 2002.

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6

Black, Jonah. Faster, faster, faster. New York: Avon Books, 2002.

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7

Black, Jonah. Faster, faster, faster. New York: Avon Books, 2002.

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8

Black, Jonah. Faster, faster, faster. New York: Avon Books, 2002.

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9

Black, Jonah. Faster, faster, faster. New York: Avon Books, 2002.

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10

Patricelli, Leslie. Faster! Faster! Somerville, Mass: Candlewick Press, 2012.

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Mais fontes

Capítulos de livros sobre o assunto "FastAI":

1

Francis, Chiramel Riya, Unik Lokhande, Prabhjyot Kaur Bamrah e Arlene D’costa. "Alzheimer’s Disease Prediction Using Fastai". In Information and Communication Technology for Intelligent Systems, 765–75. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7078-0_76.

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2

Kadri, Rahma, Mohamed Tmar e Bassem Bouaziz. "Alzheimer’s Disease Prediction Using EfficientNet and Fastai". In Knowledge Science, Engineering and Management, 452–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82147-0_37.

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3

Gullapalli, Ujwal, Lei Chen e Jinbo Xiong. "Image Classification with Transfer Learning and FastAI". In Mobile Multimedia Communications, 796–806. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89814-4_59.

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4

Badura, Christian. "Fasti". In Ovid-Handbuch, 106–11. Stuttgart: J.B. Metzler, 2021. http://dx.doi.org/10.1007/978-3-476-05685-6_15.

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Bucanek, James. "Faster, Faster". In Learn iOS App Development, 691–712. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-5063-0_23.

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6

Mellein, Richard. "Ovid: Fasti". In Kindlers Literatur Lexikon (KLL), 1–2. Stuttgart: J.B. Metzler, 2020. http://dx.doi.org/10.1007/978-3-476-05728-0_15883-1.

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Hernandez, Arthur E. "Fascia". In Encyclopedia of Child Behavior and Development, 642. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-79061-9_1105.

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Sóbester, András. "Faster". In Stratospheric Flight, 95–109. New York, NY: Praxis, 2011. http://dx.doi.org/10.1007/978-1-4419-9458-5_5.

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Faloutsos, Christos. "Fastmap". In Searching Multimedia Databases by Content, 83–93. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4613-1445-5_11.

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von Braun, Christina. "Fasten". In Metzler Lexikon Religion, 355. Stuttgart: J.B. Metzler, 2005. http://dx.doi.org/10.1007/978-3-476-00091-0_133.

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Trabalhos de conferências sobre o assunto "FastAI":

1

Chakraborty, Aditya, Debarun Kumer e K. Deeba. "Plant Leaf Disease Recognition Using Fastai Image Classification". In 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. http://dx.doi.org/10.1109/iccmc51019.2021.9418042.

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Roungroongsom, Chittra, e Orachat Chitsobhuk. "Ship Classification in Remote Sensing Images using FastAI". In 2021 13th International Conference on Knowledge and Systems Engineering (KSE). IEEE, 2021. http://dx.doi.org/10.1109/kse53942.2021.9648787.

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Tandjung, Mirna Danisa, J. Chao-Min Wu, Jia-Ching Wang e Yung-Hui Li. "An Implementation of FastAI Tabular Learner Model for Parkinson’s Disease Identification". In 2021 9th International Conference on Orange Technology (ICOT). IEEE, 2021. http://dx.doi.org/10.1109/icot54518.2021.9680650.

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4

Deutschel, Brian W., Richard B. Katnik, David W. Doerr e Ravi B. Cherukuri. "FASTAR: A Faster Analysis of Structures Using Test and Analytical Results". In International Congress & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1992. http://dx.doi.org/10.4271/920770.

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Schwahn, Oliver, Nicolas Coppik, Stefan Winter e Neeraj Suri. "FastFI: Accelerating Software Fault Injections". In 2018 IEEE 23rd Pacific Rim International Symposium on Dependable Computing (PRDC). IEEE, 2018. http://dx.doi.org/10.1109/prdc.2018.00035.

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Heo, Jae-Pil, Duksu Kim, Joon-Kyung Seong, Jeong-Mo Hong, Min Tang e Sung-Eui Yoon. "FASTCD". In ACM SIGGRAPH 2010 Posters. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1836845.1836961.

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Samanta, Soumitra, e Bhabatosh Chanda. "FaSTIP". In the Eighth Indian Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2425333.2425341.

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Liu, Jinglin, Yi Ren, Zhou Zhao, Chen Zhang, Baoxing Huai e Jing Yuan. "FastLR". In MM '20: The 28th ACM International Conference on Multimedia. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3394171.3413740.

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Wu, Fei, Jiaona Zhou, Shunzhuo Wang, Yajuan Du, Chengmo Yang e Changsheng Xie. "FastGC". In DAC '18: The 55th Annual Design Automation Conference 2018. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3195970.3196051.

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Chandramouli, Badrish, Guna Prasaad, Donald Kossmann, Justin Levandoski, James Hunter e Mike Barnett. "FASTER". In SIGMOD/PODS '18: International Conference on Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3183713.3196898.

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Relatórios de organizações sobre o assunto "FastAI":

1

Scanlan, John M. FastFAC or FastDAC? Fort Belvoir, VA: Defense Technical Information Center, janeiro de 1997. http://dx.doi.org/10.21236/ada526306.

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2

Fox, Jeffrey, Jean Fox, Mitchell Song e David Gillen. Fast Access Situation Awareness Toolkit (FASAT). Fort Belvoir, VA: Defense Technical Information Center, janeiro de 2004. http://dx.doi.org/10.21236/ada425781.

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3

Aghaie, Hamid. Solar District Heating Perspective in Austria. IEA SHC Task 55, novembro de 2020. http://dx.doi.org/10.18777/ieashc-task55-2020-0013.

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Resumo:

Austrian district heating (DH) has experienced a fast increasing trend for the last 30 years (with the exception of the period 2010-2014), resulting in a triplication of delivered heat; in the year 2018, with about 2400 networks and 20 TWh supply, DH covered 6.4% of the final energy consumption (1122.5 PJ). Worth to underline is also that this growth of Austrian district heating has been about twice faster than the one of the energy demand in the same period. Currently, district heating provides about 26% of the Austrian households with the energy requested for space heating and domestic hot water preparation.

4

Wissink, Andrew, Jude Dylan, Buvana Jayaraman, Beatrice Roget, Vinod Lakshminarayan, Jayanarayanan Sitaraman, Andrew Bauer, James Forsythe, Robert Trigg e Nicholas Peters. New capabilities in CREATE™-AV Helios Version 11. Engineer Research and Development Center (U.S.), junho de 2021. http://dx.doi.org/10.21079/11681/40883.

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CREATE™-AV Helios is a high-fidelity coupled CFD/CSD infrastructure developed by the U.S. Dept. of Defense for aeromechanics predictions of rotorcraft. This paper discusses new capabilities added to Helios version 11.0. A new fast-running reduced order aerodynamics option called ROAM has been added to enable faster-turnaround analysis. ROAM is Cartesian-based, employing an actuator line model for the rotor and an immersed boundary model for the fuselage. No near-body grid generation is required and simulations are significantly faster through a combination of larger timesteps and reduced cost per step. ROAM calculations of the JVX tiltrotor configuration give a comparably accurate download prediction to traditional body-fitted calculations with Helios, at 50X less computational cost. The unsteady wake in ROAM is not as well resolved, but wake interactions may be a less critical issue for many design considerations. The second capability discussed is the addition of six-degree-of-freedom capability to model store separation. Helios calculations of a generic wing/store/pylon case with the new 6-DOF capability are found to match identically to calculations with CREATE™-AV Kestrel, a code which has been extensively validated for store separation calculations over the past decade.

5

Lehotay, Steven J., e Aviv Amirav. Ultra-Fast Methods and Instrumentation for the Analysis of Hazardous Chemicals in the Food Supply. United States Department of Agriculture, dezembro de 2012. http://dx.doi.org/10.32747/2012.7699852.bard.

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Original proposal objectives: Our main original goal was to develop ultra-fast methods and instrumentation for the analysis of hazardous chemicals in the food supply. We proposed to extend the QuEChERS approach to veterinary drugs and other contaminants, and conduct fast and ultra-fast analyses using novel 5MB-MS instrumentation, ideally with real samples. Background to the topic: The international trade of agricultural food products is a $1.2 trill ion annual market and growing. Food safety is essential to human health, and chemical residue limits are legislated nationally and internationally. Analytical testing for residues is needed to conduct risk assessments and regulatory enforcement actions to ensure food safety and environmental health, among other important needs. Current monitoring methods are better than ever, but they are still too time-consuming, laborious, and expensive to meet the broad food testing needs of consumers, government, and industry. As a result, costs are high and only a tiny fraction of the food is tested for a limited number of contaminants. We need affordable, ultra-fast methods that attain high quality results for a wide range of chemicals. Major conclusions, solutions and achievements: This is the third BARD grant shared between Prof. Amirav and Dr. Lehotay since 2000, and continual analytical improvements have been made in terms of speed, sample throughput, chemical scope, ease-of-use, and quality of results with respect to qualitative (screening and identification) and quantitative factors. The QuEChERS sample preparation approach, which was developed in conjunction with the BARD grant in 2002, has grown to currently become the most common pesticide residue method in the world. BARD funding has been instrumental to help Dr. Lehotay make refinements and expand QuEChERS concepts to additional applications, which has led to the commercialization of QuEChERS products by more than 20 companies worldwide. During the past 3 years, QuEChERS has been applied to multiclass, multiresidue analysis of veterinary drug residues in food animals, and it has been validated and implemented by USDA-FSIS. QuEChERS was also modified and validated for faster, easier, and better analysis of traditional and emerging environmental contaminants in food. Meanwhile, Prof. Amirav has commercialized the GC-MS with 5MB technology and other independent inventions, including the ChromatoProbe with Agilent, Bruker, and FUR Systems. A new method was developed for obtaining truly universal pesticide analysis, based on the use of GC-MS with 5MB. This method and instrument enables faster analysis with lower LaDs for extended range of pesticides and hazardous compounds. A new approach and device of Open Probe Fast GC-MS with 5MB was also developed that enable real time screening of limited number of target pesticides. Implications, both scientific and agricultural: We succeeded in achieving significant improvements in the analysis of hazardous chemicals in the food supply, from easy sample preparation approaches, through sample analysis by advanced new types of GC-MS and LCMS techniques, all the way to improved data analysis by lowering LaD and providing greater confidence in chemical identification. As a result, the combination of the QuEChERS approach, new and superior instrumentation, and the novel monitoring methods that were developed will enable vastly reduced time and cost of analysis, increased analytical scope. and a higher monitoring rate. This provides better enforcement, an added impetus for farmers to use good agricultural practices, improved food safety and security, increased trade. and greater consumer confidence in the food supply.

6

Schmid, Oona. Faster and Cheaper. New York: Ithaka S+R, agosto de 2014. http://dx.doi.org/10.18665/sr.24897.

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Wu, Kesheng. FastBit Reference Manual. Office of Scientific and Technical Information (OSTI), agosto de 2007. http://dx.doi.org/10.2172/913270.

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Sauers, Aaron G. DITAC FASPAX / ASIC Development. Office of Scientific and Technical Information (OSTI), outubro de 2017. http://dx.doi.org/10.2172/1460391.

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Feldstein, Martin. Why is Productivity Growing Faster? Cambridge, MA: National Bureau of Economic Research, março de 2003. http://dx.doi.org/10.3386/w9530.

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Blue, James L., Isabel Beichl e Francis Sullivan. Faster BKL Monte Carlo simulations. Gaithersburg, MD: National Institute of Standards and Technology, 1994. http://dx.doi.org/10.6028/nist.ir.5489.

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