Autonomous landing of Micro Air Vehicles through bio-inspired monocular vision

Positive Class Localization Map: A framework for weakly supervised object localization

To possess a computer algorithm that can perform the popular task of object localization with only weak supervision is valuable for numerous reasons. Often enough a certain localization task (e.g. bird localization) simply does not have properly annotated training data available. In this thesis a novel approach called Positive Class Localization...

Deriving a global identification tool of sandy beaches using satellite images

The objective of this research is to explore the feasibility of detecting sandy beaches at a high spatial level, using satellite images. A pixel-based classification scheme of the four classes selected (sand, mud, vegetation and gravel) is conducted, using Landsat 8 Top-of-Atmosphere images (years 2014 and 2015) and Google Earth Engine. Moreover...

Semi-supervised rail defect detection from imbalanced image data

Rail defect detection by video cameras has recently gained much attention in both<br/>academia and industry. Rail image data has two properties. It is highly imbalanced towards the non-defective class and it has a large number of unlabeled data samples available for semisupervised learning techniques. In this paper we investigate if positive...

Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification

Improvement guarantees for semi-supervised classifiers can currently only be given under restrictive conditions on the data. We propose a general way to perform semi-supervised parameter estimation for likelihood-based classifiers for which, on the full training set, the estimates are never worse than the supervised solution in terms of the log...

Probabilistic defect-based risk assessment approach for rail failures in railway infrastructure

This paper develops a defect-based risk analysis methodology for estimating rail failure risk. The methodology relies on an evolution model addressing the severity level of rail surface defect, called squat. The risk of rail failure is assessed by analyzing squat failure probability using a probabilistic analysis of the squat cracks. For this...

Persistent self-supervised learning principle: Study and demonstration on flying robots

We introduce, study and demonstrate Persistent Self-Supervised Learning (PSSL), a machine learning method for usage onboard robotic platforms. The PSSL model leverages a standard supervised learning method to simplify the learning problem, but acquires training data in an unsupervised and autonomous manner. Using two platforms, a small...

Supervised Learning for Measuring Hip Joint Distance in Digital X-ray Images

Osteoarthritis is a degenerative joint disease which is hard to diagnose objectively and may vary based on the surgeon. This disease is usually diagnosed by measuring several characteristic features of Hip X-rays mainly the joint distance between the femoral head and acetabular cup. Hip joint distance reduction is a clear symptom of...

Anomaly detection for internet banking using supervised learning on high dimensional data

Nowadays, a high number of transactions are performed via internet banking. Rabobank processes more than 10 million transactions per day. Most of these transactions are (part of) normal behaviour. On the other hand, some transactions are considered to be out of the ordinary. These anomalous events occur relatively infrequently (less than 10 per...

Active Grasp Synthesis for Grasping Unknown Objects

Manipulation is a key feature for robots which are designed to work in daily environments like homes, offices and streets. These robots do not often have manipulators that are specialized for specific tasks, but grippers that can grasp the target object. This makes grasping a crucial ability that enables many manipulation tasks. Robotic grasping...

The Road to Success: Effects of Top Management Supervision on NPD Processes and Outcomes

In this project the author studies the effect of top management supervision on two NPD structural elements, namely customer orientation and portfolio management processes, and on NPD success factors: new product innovativeness, NPD speed and costs. Additionally, the effect of the two aforementioned structural elements on the noted NPD success...

Efficiently identifying deterministic real-time automata from labeled data

We develop a novel learning algorithm RTI for identifying a deterministic real-time automaton (DRTA) from labeled time-stamped event sequences. The RTI algorithm is based on the current state of the art in deterministic finite-state automaton (DFA) identification, called evidence-driven state-merging (EDSM). In addition to having a DFA structure...

Constrained parameter estimation for semi-supervised learning: The case of the nearest mean classifier

A rather simple semi-supervised version of the equally simple nearest mean classifier is presented. However simple, the proposed approach is of practical interest as the nearest mean classifier remains a relevant tool in biomedical applications or other areas dealing with relatively high-dimensional feature spaces or small sample sizes. More...

Reliability and effectiveness of clickthrough data for automatic image annotation

Automatic image annotation using supervised learning is performed by concept classifiers trained on labelled example images. This work proposes the use of clickthrough data collected from search logs as a source for the automatic generation of concept training data, thus avoiding the expensive manual annotation effort. We investigate and...

Reducing Free Riding in Peer-to-Peer Systems with Supervised Teaming

Peer-to-peer technology has produced thriving communities in which peers contribute bandwidth to each other. However, when free riding occurs, these communities will not be able to sustain themselves without incentives to enforce this contribution. This thesis presents Supervised Teaming, a peer-to-peer transfer protocol that gives uploading...