Working with TensorFlow Lite on Android with C++
(eVideo)
Author
Published
[Place of publication not identified] : O'Reilly Media, 2020.
Format
eVideo
Physical Desc
1 online resource (1 streaming video file (33 min., 39 sec.))
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Language
English
Notes
General Note
Title from resource description page (viewed July 22, 2020).
Participants/Performers
Presenter, Joe Bowser.
Description
"Other Videos in This Category Deep Learning with PyTorch Deep Learning with PyTorch Luca Pietro Giovanni Antiga; Thomas Viehmann; Eli Stevens Federated Learning Federated Learning Qiang Yang; Yang Liu; Yong Cheng; Yan Kang; Tianjian Chen; Han Yu Compatibility Modeling Compatibility Modeling Xuemeng Song; Liqiang Nie; Yinglong Wang; Gary Marchionini Representation and Understanding Representation and Understanding Allan Collins; Daniel G Bobrow Uncertainty in Artificial Intelligence Uncertainty in Artificial Intelligence MKP There are many cases where developers on mobile write lower-level C++ code for their Android applications using the Android NDK, OpenCV and other technologies. Joe Bowser (Adobe) explores how to use TF Lite's C++ API on Android with existing code so the code can interact directly with TF Lite without having to make a round trip through Java Native Interface (JNI) and the Android subsystem, allowing for cleaner, more portable code so that can even be used in iOS or other platforms. You'll also discover common pitfalls when working with TFLite as a C++ library, using TFLite with OpenCV and/or Halide on Android, as well as some techniques to do integration testing to allow your tests to work in a CI/CD environment."--Resource description page
Citations
APA Citation, 7th Edition (style guide)
Bowser, J. (2020). Working with TensorFlow Lite on Android with C++ . O'Reilly Media.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Bowser, Joe. 2020. Working With TensorFlow Lite On Android With C++. O'Reilly Media.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Bowser, Joe. Working With TensorFlow Lite On Android With C++ O'Reilly Media, 2020.
MLA Citation, 9th Edition (style guide)Bowser, Joe. Working With TensorFlow Lite On Android With C++ O'Reilly Media, 2020.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
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Grouped Work ID
1dbf3561-c4ba-ac04-fbd6-591fee8cf8b8-eng
Grouping Information
| Grouped Work ID | 1dbf3561-c4ba-ac04-fbd6-591fee8cf8b8-eng |
|---|---|
| Full title | working with tensorflow lite on android with c |
| Author | bowser joe |
| Grouping Category | movie |
| Last Update | 2024-09-06 16:31:08PM |
| Last Indexed | 2024-09-28 02:47:05AM |
Book Cover Information
| Image Source | default |
|---|---|
| First Loaded | Sep 29, 2024 |
| Last Used | Sep 29, 2024 |
Marc Record
| First Detected | Jul 29, 2024 04:05:36 PM |
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| Last File Modification Time | Sep 06, 2024 04:41:20 PM |
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| 520 | |a "Other Videos in This Category Deep Learning with PyTorch Deep Learning with PyTorch Luca Pietro Giovanni Antiga; Thomas Viehmann; Eli Stevens Federated Learning Federated Learning Qiang Yang; Yang Liu; Yong Cheng; Yan Kang; Tianjian Chen; Han Yu Compatibility Modeling Compatibility Modeling Xuemeng Song; Liqiang Nie; Yinglong Wang; Gary Marchionini Representation and Understanding Representation and Understanding Allan Collins; Daniel G Bobrow Uncertainty in Artificial Intelligence Uncertainty in Artificial Intelligence MKP There are many cases where developers on mobile write lower-level C++ code for their Android applications using the Android NDK, OpenCV and other technologies. Joe Bowser (Adobe) explores how to use TF Lite's C++ API on Android with existing code so the code can interact directly with TF Lite without having to make a round trip through Java Native Interface (JNI) and the Android subsystem, allowing for cleaner, more portable code so that can even be used in iOS or other platforms. You'll also discover common pitfalls when working with TFLite as a C++ library, using TFLite with OpenCV and/or Halide on Android, as well as some techniques to do integration testing to allow your tests to work in a CI/CD environment."--Resource description page | ||
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