Tag Archives: Decision Trees

Supervised graduate students

I have supervised several graduate students (Laëtitia Letoupin, Antonin Molières, Alexis Malécot, Ho Tien Lam) for the development of a Video Indexing tool in C++/Qt while doing my PhD in Bordeaux.

Since joining the MICC, I have supervised multiple italian students on different projects:

  • Alessio Benevieri, Railway Wagon Id Automatic recognition
  • Federico Bartoli, Master thesis “Fast pedestrian detection via geometric and Soft Cascade approximation” [1]

  • Claudio Tortorici, Master thesis “Relaxed Decision Trees over multiple Taxonomies for Visual Recognition”

  • Giovanni Giunto, Master thesis “Towards Spatial Codebook-free Methods for Image Classification”

  • Andrea Ciolini, Master thesis “Object Detection on Low Power Devices” [2]

[1] [pdf] F. Bartoli, G. Lisanti, S. Karaman, A. D. Bagdanov, and A. Del Bimbo, “Unsupervised scene adaptation for faster multi-scale pedestrian detection,” in 22nd International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 2014.
[Bibtex]
@InProceedings{bartoliicpr2014,
author = {Bartoli, Federico and Lisanti, Giuseppe and Karaman, Svebor and Bagdanov, Andrew D. and Del Bimbo, Alberto},
title = {Unsupervised scene adaptation for faster multi-scale pedestrian detection},
note = {Oral presentation},
booktitle = {22nd International Conference on Pattern Recognition (ICPR)},
address = {Stockholm, Sweden},
year = {2014}
}
[2] [pdf] A. Ciolini, L. Seidenari, S. Karaman, and A. Del Bimbo, “Efficient Hough Forest Object Detection for Low-power Devices,” in IEEE First International Workshop on Wearable and Ego-vision Systems for Augmented Experience (WEsAX), 2015.
[Bibtex]
@inproceedings{ciolini2015,
author = {Ciolini, Andrea and Seidenari, Lorenzo and Karaman, Svebor and Del Bimbo, Alberto},
title = {Efficient Hough Forest Object Detection for Low-power Devices},
booktitle = {IEEE First International Workshop on Wearable and Ego-vision Systems for Augmented Experience (WEsAX)},
year = {2015}
}