Category: Solutions

In this post I’ll talk in detail about the forward path implementation of the famous AlexNet. This Convolutional Neural Network (CNN) by Krizhevsky and Hinton has won the ILSVR 2012 competition with a remarkable margin. If you are starting to work with CNNs or Deep Learning in general, this post will give you a head start. You can find a straight forward implementation of the CNN’s forward path on our Github site. Feel free to download it and classify arbitrary images.

Continue reading “AlexNet Forward Path Implementation”

This document is the primary studies on the real.iZ VS-1000 3D Vision System for fruit detection. Please go to manuals and odos imaging for more information and always regard the manuals as your prioritized reference.

The contents are listed as follows:

1. structure and operating principles
2. features
3. indoor experiment
4. outdoor experiments
5. range photos processing
6. portable solutions
7. future challenges
8. help seeking

Continue reading “Primary Studies on the real.iZ VS-1000 3D Vision System”

This document briefly explains how to use the parser of the Caffe code base in order to read and parse the specifications of neural networks. Caffe’s text file format for specifying models uses Google Protocol Buffer format. The code that actually reads a model can be found in src/caffe/util/io.cpp: Continue reading “Data Parser in Caffe”