AI on low-cost hardware: Microcontroller subgroup

The creation of effective computational models that function within the power limitations of edge de- vices is an important research problem in the field of Artificial Intelligence (AI). While cutting-edge deep learning algorithms show promising results, they frequently need computing resources that are many orders of magnitude more than the...

AI on Low-Cost Hardware: Software Subgroup

Artificial Intelligence has become a dominant part of our lives, however, complex artificial intelligence models tend to use a lot of energy, computationally complex operations, and a lot of memory resources. Therefore, it excluded a whole class of hardware in its applicability. Namely, relatively resource-constrained low-cost hardware. This...

Improvements in Monte Carlo Tree Search for Inductive Program Synthesis

A recent development in program synthesis is using Monte Carlo Tree Search to traverse the search tree of possible programs in order to efficiently find a program that will successfully transform the given input to the desired output. Previous research has shown promising results as Monte Carlo Tree Search is able to escape local optima that...

Efficient Online Globalized Dual Heuristic Programming With an Associated Dual Network

Globalized dual heuristic programming (GDHP) is the most comprehensive adaptive critic design, which employs its critic to minimize the error with respect to both the cost-to-go and its derivatives simultaneously. Its implementation, however, confronts a dilemma of either introducing more computational load by explicitly calculating the...

Evaluating and Improving Large-Scale Machine Learning Frameworks

Given the increasing popularity of Machine Learning, and the ever increasing need to solve larger and more complex learning challenges, it is unsurprising that numerous distributed learning strategies have been brought forward in recent years, along with many large scale Machine Learning frameworks. It is however unclear how well these...

Repetition counting in videos using deep learning

This work tackles the problem of repetition counting in videos using modern deep learning techniques. For this task, the intention is to build an end-to-end trainable model that could estimate the number of repetitions without having to manually intervene with the feature selection process. The models that exist currently perform well on videos...

An Axial Array for Volumetric Intravascular Ultrasound Imaging

Intravascular ultrasound (IVUS) is a medical imaging modality aimed at imaging blood vessel walls from within the vessel. Current commercial IVUS catheters are designed to yield two-dimensional cross-sectional images perpendicular to the vessel wall. By pulling the catheter back through the artery (in the ‘axial direction’), and stacking the...

Comparison of fundamental, second harmonic, and superharmonic imaging: A simulation study

In medical ultrasound, fundamental imaging (FI) uses the reflected echoes from the same spectral band as that of the emitted pulse. The transmission frequency determines the trade-off between penetration depth and spatial resolution. Tissue harmonic imaging (THI) employs the second harmonic of the emitted frequency band to construct images....