paper-with-me

Papers

A Tour of TensorFlow

2016-10-01 · Peter Goldsborough

Deep learning is a branch of artificial intelligence employing deep neural network architectures that has significantly advanced the state-of-the-art in computer vision, speech recognition, natural language processing and other domains. In November 2015, Google released $\textit{TensorFlow}$, an open source deep learning software library for defining, training and deploying machine learning models. In this paper, we review TensorFlow and put it in context of modern deep learning concepts and software. We discuss its basic computational paradigms and distributed execution model, its programming interface as well as accompanying visualization toolkits. We then compare TensorFlow to alternative libraries such as Theano, Torch or Caffe on a qualitative as well as quantitative basis and finally comment on observed use-cases of TensorFlow in academia and industry.

📄 PDF Abstract BibTeX arXiv:1610.01178

Code (0)

등록된 구현이 없습니다.

Tasks

Deep Learningspeech-recognitionSpeech Recognition

Similar Papers 제목 키워드 기반

End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery

2020-07-22 · ECCV 2020 8 · Ali Hatamizadeh, Debleena Sengupta, Demetri Terzopoulos

The automated segmentation of buildings in remote sensing imagery is a challenging task that requires the accurate delineation of multiple building instances over typically large image areas. Manual methods are often lab…

Image SegmentationSegmentationSemantic Segmentation

End-to-End Deep Convolutional Active Contours for Image Segmentation

2019-09-29 · Ali Hatamizadeh, Debleena Sengupta, Demetri Terzopoulos

The Active Contour Model (ACM) is a standard image analysis technique whose numerous variants have attracted an enormous amount of research attention across multiple fields. Incorrectly, however, the ACM's differential-e…

Image SegmentationInstance SegmentationSegmentationSemantic Segmentation

TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning

2019-02-27 · Akshay Agrawal, Akshay Naresh Modi, Alexandre Passos, Allen Lavoie 외

TensorFlow Eager is a multi-stage, Python-embedded domain-specific language for hardware-accelerated machine learning, suitable for both interactive research and production. TensorFlow, which TensorFlow Eager extends, re…

BIG-bench Machine Learning

TensorFlow.js: Machine Learning for the Web and Beyond

2019-01-16 · Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan 외

TensorFlow.js is a library for building and executing machine learning algorithms in JavaScript. TensorFlow.js models run in a web browser and in the Node.js environment. The library is part of the TensorFlow ecosystem, …

BIG-bench Machine Learning

Towards ML Engineering: A Brief History Of TensorFlow Extended (TFX)

2020-09-28 · Konstantinos, Katsiapis, Abhijit Karmarkar, Ahmet Altay 외

Software Engineering, as a discipline, has matured over the past 5+ decades. The modern world heavily depends on it, so the increased maturity of Software Engineering was an eventuality. Practices like testing and reliab…