Here are the requirements.
1. Implement using C++ framework "tinydnn" ([url removed, login to view])
2. Implement SqueezeNet. Supports 3 modes.
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
Building on top of Part 1, implement object detection similar to SqueezeDet.
1. Implement object detection using squeezeDet ([url removed, login to view])
2. Implement in C++ using tinyDNN
3. Demo on linux machine
4. Well documented code.
5. 1 hr code review.
19 freelanceria on tarjonnut keskimäärin %project_bid_stats_avg_sub_26% %project_currencyDetails_sign_sub_27% tähän työhön
Hello! I read your details. I have a full of experiences in C++ Programming. I've finished many projects like this. I can finish your project clearly and quickly. Hope your kind contact. Thanks!
Hi. My major is math(Neural Science,Computer Science) My skill is image process(cnn/knn/rcnn/c++/opencv) Please contact my portfolio in my profile. I can do it perfectly. thanks.
I am a senior software engineer and I am preparing a mater degree and my research point is in machine learning and computer vision so this project is matching my interests and skills