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▼a GBB898003
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▼a 794.81526
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| 100 | 1 |
▼a Tang, Xiaofei ""Jeff"". |
| 245 | 10 |
▼a Intelligent Mobile Projects with TensorFlow :
▼b Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi. |
| 260 | |
▼a Birmingham:
▼b Packt Publishing,
▼c 2018. |
| 300 | |
▼a 1 online resource (396 pages). |
| 336 | |
▼a text
▼b txt
▼2 rdacontent |
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▼a computer
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▼a online resource
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▼a Training the drawing classification model. |
| 505 | 0 |
▼a Cover; Copyright and Credits; Dedication; Packt Upsell; Foreword; Contributors; Table of Contents; Preface; Chapter 1: Getting Started with Mobile TensorFlow; Setting up TensorFlow; Setting up TensorFlow on MacOS; Setting up TensorFlow on GPU-powered Ubuntu; Setting up Xcode; Setting up Android Studio; TensorFlow Mobile vs TensorFlow Lite; Running sample TensorFlow iOS apps; Running sample TensorFlow Android apps; Summary; Chapter 2: Classifying Images with Transfer Learning; Transfer learning -- what and why; Retraining using the Inception v3 model; Retraining using MobileNet models. |
| 505 | 8 |
▼a Using the retrained models in the sample iOS appUsing the retrained models in the sample Android app; Adding TensorFlow to your own iOS app; Adding TensorFlow to your Objective-C iOS app; Adding TensorFlow to your Swift iOS app; Adding TensorFlow to your own Android app; Summary; Chapter 3: Detecting Objects and Their Locations; Object detection-a quick overview; Setting up the TensorFlow Object Detection API; Quick installation and example ; Using pre-trained models; Retraining SSD-MobileNet and Faster RCNN models; Using object detection models in iOS. |
| 505 | 8 |
▼a Building TensorFlow iOS libraries manuallyUsing TensorFlow iOS libraries in an app; Adding an object detection feature to an iOS app; Using YOLO2-another object-detection model; Summary; Chapter 4: Transforming Pictures with Amazing Art Styles; Neural Style Transfer -- a quick overview; Training fast neural-style transfer models; Using fast neural-style transfer models in iOS; Adding and testing with fast neural transfer models; Looking back at the iOS code using fast neural transfer models; Using fast neural-style transfer models in Android. |
| 505 | 8 |
▼a Using the TensorFlow Magenta multi-style model in iOSUsing the TensorFlow Magenta multi-style model in Android; Summary; Chapter 5: Understanding Simple Speech Commands; Speech recognition -- a quick overview; Training a simple commands recognition model; Using a simple speech recognition model in Android; Building a new app using the model; Showing model-powered recognition results; Using a simple speech recognition model in iOS with Objective-C; Building a new app using the model; Fixing model-loading errors with tf_op_files.txt; Using a simple speech recognition model in iOS with Swift. |
| 520 | |
▼a Chapter 6: Describing Images in Natural Language; Image captioning - how it works; Training and freezing an image captioning model; Training and testing caption generation; Freezing the image captioning model; Transforming and optimizing the image captioning model; Fixing errors with transformed models; Optimizing the transformed model; Using the image captioning model in iOS; Using the image captioning model in Android; Summary; Chapter 7: Recognizing Drawing with CNN and LSTM; Drawing classification - how it works; Training, predicting, and preparing the drawing classification model. |
| 520 | |
▼a Google TensorFlow is used to train all the models deployed and running on mobile devices. This book covers 10 projects on the implementation of all major AI areas on iOS, Android, and Raspberry Pi: computer vision, speech and language processing, and machine learning, including traditional, reinforcement, and deep reinforcement. |
| 588 | 0 |
▼a Print version record. |
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▼a Raspberry Pi
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▼a GAMES / Board
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▼a Electronic books. |
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▼i Print version:
▼a Tang, Xiaofei ""Jeff"".
▼t Intelligent Mobile Projects with TensorFlow : Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi.
▼d Birmingham : Packt Publishing, 짤2018 |
| 856 | 40 |
▼3 EBSCOhost
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