Thesis Proposal

For us, looking for young talents who are passionate about the latest technologies is essential. We also put a big effort in consolidating the cooperation and the harmony within the team
Those who will join us will meet a small family where everyone helps each other, learn and enjoys many informal moments with colleagues

For us it is important to keep high the motivation of the newcomers through the continuous development of new technologies and their application on real problems. The development of a master thesis is for us an important period to evaluate the capabilities and the talents of the people that we will recruit just after graduation. For the master’s candidates this is a great opportunity to work on state-of-the art technologies, applied to real world problems.

Partners

Addfor_politecnico_torino
Addfor_universita_torino
addfor_politecnico_milano
addfor_univerita_bologna
addfor_universita_trento

Thesis still available

Algorithms for Multiple Object Tracking

[Available]

The aim of this thesis is to define objective methods for measuring the performance of multiple object tracking algorithms in real datasets.

[read more]

Scene Classification in Video Streams

[Available]

ResNet is a Deep Learning Network considered a reference for Image Classification. It is used in cases where a high classification accuracy is required. RL in conjunction with Deep Learning has obtained outstanding results in Atari video games, the Go board-game and a more complex environment like StarCraft II.

[read more]

Testing Algorithms for image & Video understanding

[Available]

In the last few years, many algorithms with remarkable effectiveness for Object Detection have been published but still some comparative metrics haven’t been defined.

[read more]

Build a Chatbot for Interviews on IBM Watson

[Available]

IBM Watson™ is a SaaS engine for the development of Cognitive Computing applications.

[read more]

Comparison of Reinforcement Learning Frameworks

[Available]

Reinforcement Learning (RL) is a class of machine learning algorithms in which an agent interacts by trial-and-error in an environment.

[read more]

Safe Reinforcement Learning

[Available]

Reinforcement Learning (RL) [1] is a class of machine learning algorithms in which an agent interacts by trial-and-error in an environment.

[read more]

Unsupervised/semi-supervised video classification

[Available]

When there are hundreds or thousands of cameras producing video streams all day long it is very useful to have an algorithm that analyses such streams instead of a human.

[read more]

Deep Genomics: harnessing the power of Deep Neural Networks in the analysis of biomolecular data

[Available]

The human genome project [1], an international scientific research project with the goal of determining the sequence of nucleotide base pairs that make up human DNA, lasted roughly 15 years and cost $5 billion (adjusted for inflation).

[read more]

Algorithm Optimization on Embedded & Server GPU

[Available]

NVIDIA TensorRT5.1™ is an Inference Optimizer and runtime that allows low latency and high throughput for Deep-Learning applications.

[read more]

Model Based Reinforcement Learning

[Available]

Reinforcement Learning (RL) [1] is a class of machine learning algorithms in which an agent interacts by trial-and-error in an environment.

[read more]

Thesis completed – no more available

Synthetic object Dataset Augmentation

[Expired]

A recent publication “On Pre-Trained Image Features and Synthetic Images for Deep Learning“ uses real images as background for synthetically generated objects in order to create a dataset for Deep Learning algorithms.

[read more]

Capsule Networks as alternative to DCNN

[Expired]

Geoffrey Hinton released last month a document titled “Dynamic Routing Between Capsules“ and the entire Deep Learning community was shaken by this article.

[read more]

Latest Thesis [ITA]

Latest Thesis [ENG]