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New York City Directory
  • Language: en
  • Pages: 1722

New York City Directory

  • Type: Book
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  • Published: 1876
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  • Publisher: Unknown

None

Trow's New York City Directory
  • Language: en
  • Pages: 1092

Trow's New York City Directory

  • Type: Book
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  • Published: 1860
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  • Publisher: Unknown

None

Generative AI with Python and TensorFlow 2
  • Language: en
  • Pages: 489

Generative AI with Python and TensorFlow 2

Fun and exciting projects to learn what artificial minds can create Key FeaturesCode examples are in TensorFlow 2, which make it easy for PyTorch users to follow alongLook inside the most famous deep generative models, from GPT to MuseGANLearn to build and adapt your own models in TensorFlow 2.xExplore exciting, cutting-edge use cases for deep generative AIBook Description Machines are excelling at creative human skills such as painting, writing, and composing music. Could you be more creative than generative AI? In this book, you’ll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. You’ll learn how to implement mode...

Gouldings New York City Directory
  • Language: en
  • Pages: 1702

Gouldings New York City Directory

  • Type: Book
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  • Published: 1877
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  • Publisher: Unknown

None

An English-Cornish Dictionary
  • Language: en
  • Pages: 250

An English-Cornish Dictionary

  • Type: Book
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  • Published: 1887
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  • Publisher: Unknown

None

An English-Cornish Dictionary
  • Language: en
  • Pages: 246

An English-Cornish Dictionary

  • Type: Book
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  • Published: 1887
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  • Publisher: Unknown

None

Lexicon cornu-britannicum
  • Language: en
  • Pages: 664

Lexicon cornu-britannicum

  • Type: Book
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  • Published: 1865
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  • Publisher: Unknown

None

Advances in Imaging and Electron Physics
  • Language: en
  • Pages: 369

Advances in Imaging and Electron Physics

Advances in Imaging and Electron Physics merges two long-running serials--Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. This series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains. Contributions from leading international scholars and industry experts Discusses hot topic areas and presents current and future research trends Invaluable reference and guide for physicists, engineers and mathematicians

Artificial Intelligence and Security
  • Language: en
  • Pages: 753

Artificial Intelligence and Security

This two-volume set of LNCS 12736-12737 constitutes the refereed proceedings of the 7th International Conference on Artificial Intelligence and Security, ICAIS 2021, which was held in Dublin, Ireland, in July 2021. The conference was formerly called “International Conference on Cloud Computing and Security” with the acronym ICCCS. The total of 93 full papers and 29 short papers presented in this two-volume proceedings was carefully reviewed and selected from 1013 submissions. Overall, a total of 224 full and 81 short papers were accepted for ICAIS 2021; the other accepted papers are presented in CCIS 1422-1424. The papers were organized in topical sections as follows: Part I: Artificial intelligence; and big data Part II: Big data; cloud computing and security; encryption and cybersecurity; information hiding; IoT security; and multimedia forensics

GANs for Data Augmentation in Healthcare
  • Language: en
  • Pages: 255

GANs for Data Augmentation in Healthcare

Computer-Assisted Diagnostics (CAD) using Convolutional Neural Network (CNN) model has become an important technology in the medical industry, improving the accuracy of diagnostics. However, the lack Magnetic Resonance Imaging (MRI) data leads to the failure of the depth study algorithm. Medical records often different because of the cost of obtaining information and the time-consuming information. In general, clinical data are unreliable, the training of neural network methods to distribute disease across classes does not yield the desired results. Data augmentation is often done by training data to solve problems caused by augmentation tasks such as scaling, cropping, flipping, padding, ro...