Search
Now showing items 1-10 of 21
City Safety Event Classification using Machine Learning
(2019-11-21)
City safety technology aims to reduce vehicle collisions using activated warnings
and braking based on automated detection of environmental threats. However, automatic
detection of tentative collisions may differ from ...
Detecting security related code by using software architecture
(2018-03-20)
This thesis looks into automatic detection of security related code in order to eliminate
this problem. Since manual code detection is tiresome and introduces human
error we need a more efficient way of doing it. We ...
Predicting Pedestrian Counts per Street Segment in Urban Environments
(2020-07-08)
Cities are continuously growing all over the world and the complexity of designing
urban environments increases. Therefore, there is a need to build a better understanding
in how our cities work today. One of the essential ...
Application of Machine Learning Algorithms for Post Processing of Reference Sensors
(2021-04-01)
The Autonomous Drive (AD) systems and Advanced Driver Assistance Systems
(ADAS) in the current and future generations of vehicles include a large number
of sensors which are used to perceive the vehicle’s surroundings. ...
Machine Learning for Detecting Hate Speech in Low Resource Languages
(2020-07-08)
This work examines the role of both cross-lingual zero-shot learning and data augmentation
in detecting hate speech online for low resource set-ups. The proposed
solutions for situations where the amount of labeled data ...
Compressed Machine Learning on Time Series Data
(2020-07-08)
The extent of time related data across many fields has led to substantial interest
in the analysis of time series. This interest meets growing challenges to store and
process data. While the data is collected at an ...
Text analysis for email multi label classification
(2020-07-08)
This master’s thesis studies a multi label text classification task on a small data
set of bilingual, English and Swedish, short texts (emails). Specifically, the size of
the data set is 5800 emails and those emails are ...
Learning Geometry Compatibility with 3D Convolutional Neural Networks
(2019-10-04)
Modern video games offer substantial amounts of customization options. Manually testing the visual compatibility of all options is time-consuming and error-prone. Together with Ghost Games, we present a method of learning ...
Resource Optimal Neural Networks for Safety-critical Real-time Systems
(2020-07-10)
Deep neural networks consume an excessive amount of hardware resources, making
them difficult to deploy to real-time systems. Previous work in the field of network
compression lack the explicit hardware feedback necessary ...
Deep Learning for Deep Water: Robust classification of ship wakes with expert in the loop
(2020-10-06)
This work examines the applicability of the deep learning models to pattern recognition
in acoustic ocean data. The features of the dataset include noise, data scarcity
and the lack of labeled samples. A deep learning ...