Another open-source Deep Learning framework on our list is Keras. This nifty tool can run on top of TensorFlow, Theano, Microsoft Cognitive Toolkit, and PlaidML. The USP of Keras is its speed – it comes with built-in support for data parallelism, and hence, it can process massive volumes...
To overcome these challenges, we propose the integration of medical imaging with deep learning to develop an automated detection system for FISH images. This system features an algorithm capable of quickly detecting fluorescent spots and capturing their coordinates, which is crucial for evaluating ...
DeepCreamPy 9.7k Decensoring Hentai with Deep Neural Networks stylegan 9.7k StyleGAN - Official TensorFlow Implementation Dive-into-DL-PyTorch 9.6k 本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。 stanford-tensorflow-tutorials 9.6k This repository contains code exa...
scikit-learn36.6kscikit-learn: machine learning in Python TensorFlow-Examples33.4kTensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) pytorch30.8kTensors and Dynamic neural networks in Python with strong GPU acceleration caffe28.8kCaffe: a fast open framework for deep learning. ...
(Though to be fair, they are bullish on Swift for TensorFlow.) In the most recent version of the course, you’ll discover how to achieve state-of-the-art results on tasks such as classification, segmentation, and predictions in text and vision domains, along with learning all about GANs ...
Zygote.jl 和 TPU, 以及 Swift for TensorFlow 等系统通过集成到非 Python 宿主语言中的方式提供了程序转换接口. Swift 和 Julia 中这种原生宿主语言集成的主要缺点是: 它们需要用户推出 Python 生态系统. Python 在数字/科学计算(尤其是深度学习)领域具有相当大的发展势头和广泛的库, 许多用户更愿意留在 Python 生...
《Faster deep learning with GPUs and Theano》 介绍:基于Theano/GPU的高效深度学习. 《Introduction to R Programming》 介绍:来自微软的. 《Golang:Web Server For Performing Sentiment Analysis》 介绍:(Go)情感分析API服务Sentiment Server. 《A Beginner’s Guide to Restricted Boltzmann Machines》 ...
Convolutional Neural Networks with Swift for Tensorflow: Image Recognition and Dataset Categorization; Apress: New York, NY, USA, 2021; pp. 109–123. [Google Scholar] Theckedath, D.; Sedamkar, R.R. Detecting affect states using VGG16, ResNet50 and SE-ResNet50 networks. SN Comput. Sci....
ResNet 34. In Convolutional Neural Networks with Swift for Tensorflow: Image Recognition and Dataset Categorization; Apress: Berkeley, CA, USA, 2021; pp. 51–61. ISBN 978–1–4842–6168–2. [Google Scholar] [CrossRef] Parvat, A.; Chavan, J.; Kadam, S.; Dev, S.; Pathak, V. A ...
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