SE-Inception v3架构的模型搭建(keras代码实现)

Mark 2018-09-28 16:47
2017年ImagNet冠军架构得主的精髓之处SENet架构(Squeeze And Excitation),关于细节处不再多说,只是该架构的基本结构图,和代码实现。并且代码实现此处是googleNet的Inception v3架构为基础加上SE的结构。

A Neural Algorithm of Artistic Style

dwSun 2018-02-07 17:07
In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image. Thus far the algor

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

jixiaohui 2018-01-10 14:52
We present a class of efficient models called MobileNets for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses depth-wise separable convolutions to

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

辉仔 2018-01-10 11:09
In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications. Comparatively, unsupervised learning with CNNs has received less attenti

Learning to Segment Every Thing

dwSun 2018-01-15 20:39
Existing methods for object instance segmentation require all training instances to be labeled with segmentation masks. This requirement makes it expensive to annotate new categories and has restricte

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks

辉仔 2018-01-10 10:21
We present an integrated framework for using Convolutional Networks for classification, localization and detection. We show how a multiscale and sliding window approach can be efficiently implemented

Rethinking Atrous Convolution for Semantic Image Segmentation

dwSun 2018-01-15 20:12
In this work, we revisit atrous convolution, a powerful tool to explicitly adjust filter's field-of-view as well as control the resolution of feature responses computed by Deep Convolutional Neural Ne

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation

dwSun 2018-02-06 17:25
In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of diffe

One weird trick for parallelizing convolutional neural networks

辉仔 2018-01-10 10:26
I present a new way to parallelize the training of convolutional neural networks across multiple GPUs. The method scales significantly better than all alternatives when applied to modern convolutional

Rethinking the Inception Architecture for Computer Vision

辉仔 2018-01-10 11:10
Convolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yieldin
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