Object Classification through Deconvolutional Neural Networks Student: Carlos Rubiano Mentor: Oliver Nina

Helped High School Students Helped them with Caffe Setup Caffe Showed them how to create a network and then train it Gave them assistance when needed

Aerial View Classes Cars Non-Cars Size: 24x24 Trained on Caffe Results: 88%

On UT-Interaction Dataset, doing majority voting, classified sequences with 100% accuracy Chalearn Dataset got 54.55%

Working on python predictions file Refining it Want to combine various networks In ensemble fashion using different trained features Working on custom model by adding dropout to max pooling layers, similar to maxout but faster Adding RNN for temporal segmentation