SqueezeNet and SqueezeDet using C++

Here are the requirements.

Part 1

1. Implement using C++ framework "tinydnn" ([login to view URL])

2. Implement SqueezeNet. Supports 3 modes.

a) Regular

b) Compressed 8 bits

c) Compressed 6 bits

3) User Cifar-10 as training and test set.

4) Well documented code

5) Demonstrate on a linux machine for image classification

6) 1 hr of code review to be included

Part 2

Building on top of Part 1, implement object detection similar to SqueezeDet.

1. Implement object detection using squeezeDet ([login to view URL])

2. Implement in C++ using tinyDNN

3. Demo on linux machine

4. Well documented code.

5. 1 hr code review.

Skills: Algorithm, C Programming, C++ Programming, Machine Learning, Software Architecture

See more: Model Based Design, microcontrollers, DSP, C++, C, VxWorks, VSS, VAPS, UML, U-Boot, Test, TCL, Systems engineering, Sys, java c++ php SQL machine learning big data , Big data using Spark n scala, Machine learning using spark... Tableau visualisation, php, c programming, software architecture, c++ programming, algorithm, machine learning, C java database user interface VC++, C, C++, Android, Python, machine learning, data analytics, linux, device drivers, business analysis, user stories, requirements, user specification requirements, machine learning project matlab, accounting system using mysql source code user guide, machine vision project using webcam, machine learning using neural network neural networks, data mining machine learning project, machine learning using neural networks, machine learning matlab project

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Project ID: #16355941

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