Huseyin ABANOZ

Objective Transfer Learning technique is used when the dataset is not of sufficient size. It is common to fine tune a network which is pre-trained on large datasets like Imagenet for classification tasks. For further information, the reader is advised to refer to CS231N by Standford . A framework for general purpose transfer learning is proposed. This framework is developed for my MSc. thesis study and made publicly available to let researchers make use of it. Using this framework, the researcher will easily be able to fine-tune a network for a classification task. Audience This article can be useful for anyone seeking information about transfer learning implementation. Python knowledge is required to make use of the supplied code. Introductory information about Keras , a deep learning API, is necessary. Also in order to run the code, a proper deep learning system with a decent graphics card (GPU) with CUDA Compute Capability 3.0 or higher   is necessar...

Introduction Keras is a popular deep learning api. It can run on top of Tensorflow , CNTK and Theano frameworks. Keras provides an easy to use interface which makes deep learning practice straight forward. It is widely used thus resources are easily accessible. Objective This article aims to give an introductory information about using a Keras trained CNN model for inference. This article does not contain information about CNN training. Audience This article assumes introductory information about python and Convolutional Neural Networks. For those who lack information may first begin with information from following resources. For python use  Python For Beginners For Convolutional Neural Networks use  CS231n Convolutional Neural Networks for Visual Recognition Software Installation Keras is a high level API. It requires a back-end framework to be installed. In this article, Tensorflow is used. Keras can transparently select CPU or GPU for processing. If use ...

An Ubuntu Deep Learning System A.                     Install latest Nvidia drivers 1-       Run following  commands  to add latest drivers from PPA. sudo add-apt-repository ppa:graphics-drivers/ppa sudo apt update 2-       Then use Ubuntu  Software &Updates  Additional Drivers application to update your driver. For my GTX-1070 I chose driver with version 384.69. 3-       After installation Restart your PC. You may need to disable safe boot using bios menu. 4-       Run following command to ensure that drivers are installed correctly. lsmod | grep nvidia 5-       İf you have issue with the new driver remove it with following command. sudo apt-get purge nvidia* For more information see: https://askubuntu.com/questions/...