Tag: mobilenet

• Modern Convolution Neutral Network (20 Mar 2022)
  

  Convolutional Neural Networks (ConvNets or CNNs) are a class of neural networks algorithms that are mostly used in visual recognition tasks such as image classification, object detection, and image segmentation. The use of ConvNets in visual recognition is inarguably one of the biggest inventions of decade 2010s in deep learning community.

• Convolution Nerual Network Backbone (15 Apr 2019)
  

  Convolution Nerual Network (CNN) has been used in many visual tasks. You may find the networks for varying types of visual tasks share similar set of feature extraction layer, which is referred as backbone. Researchers typically use backbone which has been succesful in ImageNet competion and combine them with different loss functions to solve different type of visual tasks.

• Effcient Deep Neural Network (07 Apr 2019)
  

  In this post, we will introduce some neural networks which are suitable for running on mobile devices.

• Network Compression (03 Apr 2019)
  

  The trained network is typically too large to run efficiently on mobile device. For example, VGG16 used for image classification has more 130 Million parameter (about 600 MB on model size) and requires about 31 billion operations to classify an image, which is way to expensive to be done on mobile.