Deep learning with tensorflow: A review
… Fortunately, TensorFlow greatly eases and accelerates the research and application of
neural network models. We review several core concepts of TensorFlow such as graph …
neural network models. We review several core concepts of TensorFlow such as graph …
An experience report on machine learning reproducibility: Guidance for practitioners and TensorFlow model garden contributors
V Banna, A Chinnakotla, Z Yan, A Vegesana…�- arXiv preprint arXiv�…, 2021 - arxiv.org
… selection to model engineering, as well as testing and releasing in TensorFlow Model Garden,
… Although some of our technical advice is specific to TensorFlow, our engineering process …
… Although some of our technical advice is specific to TensorFlow, our engineering process …
TensorFlow with user friendly Graphical Framework for object detection API
… which can be recognised by TensorFlow for generating TensorFlow readable input files, …
communicating with TensorFlow. TensorFlow also provides very useful multi-model evaluation …
communicating with TensorFlow. TensorFlow also provides very useful multi-model evaluation …
Modelhub. ai: Dissemination platform for deep learning models
Recent advances in artificial intelligence research have led to a profusion of studies that
apply deep learning to problems in image analysis and natural language processing among …
apply deep learning to problems in image analysis and natural language processing among …
An empirical study on tensorflow program bugs
… a model, the test execution may be expensive. The complete training process of a TensorFlow
model … of the model. On the other hand, the training phase consists of many iterations, and …
model … of the model. On the other hand, the training phase consists of many iterations, and …
EvalDNN: A toolbox for evaluating deep neural network models
… the robustness of TensorFlow models. Besides, Foolbox [13] is designed to generate
adversarial examples for DNN models and thus can be used to evaluate the models’ robustness. …
adversarial examples for DNN models and thus can be used to evaluate the models’ robustness. …
Benchmarking deep learning infrastructures by means of tensorflow and containers
Ever growing interest and usage of deep learning rises a question on the performance of
various infrastructures suitable for training of neural networks. We present here our approach …
various infrastructures suitable for training of neural networks. We present here our approach …
[BOOK][B] Intelligent Mobile Projects with TensorFlow: Build 10+ Artificial Intelligence Apps Using TensorFlow Mobile and Lite for IOS, Android, and Raspberry Pi
J Tang - 2018 - books.google.com
… TensorFlow model, a retrained TensorFlow model for TensorFlow Lite, and a custom TensorFlow
Lite model … We'll also show you how to use TensorFlow Lite in Android. After that, we'll …
Lite model … We'll also show you how to use TensorFlow Lite in Android. After that, we'll …
Static automatic batching in TensorFlow
A Agarwal�- International Conference on Machine Learning, 2019 - proceedings.mlr.press
… To address this we extend TensorFlow with pfor, a parallel-for loop optimized using static
loop vectorization. With pfor, users can express computation using nested loops and …
loop vectorization. With pfor, users can express computation using nested loops and …
[BOOK][B] Machine Learning with TensorFlow 1. x: Second generation machine learning with Google's brainchild-TensorFlow 1. x
Q Hua, SU Azeem, S Ahmed - 2017 - books.google.com
… model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-…
up to take on any challenges of implementing TensorFlow 1. x in your machine learning …
up to take on any challenges of implementing TensorFlow 1. x in your machine learning …