Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning

The burgeoning navigation services using digital maps provide great convenience to drivers. However, there are sometimes anomalies in the lane rendering map images, which might mislead human drivers and result in unsafe driving. To accurately and effectively detect the anomalies, this paper transforms lane rendering image anomaly detection into...

Building and roof type classification on 3D city models

In a rapidly evolving digital landscape, 3D city models have become more accurate and complex. Despite their widespread availability of open-source 3D city model datasets, these invaluable resources remain underutilized. Our primary goal centers on the classification of building and roof types. For our client, Spotr, our work directly impacts on...

The paradox of the artificial intelligence system development process: the use case of corporate wellness programs using smart wearables

Artificial intelligence (AI) systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI...

An efficient deep learning approach for ground point filtering in aerial laser scanning point clouds

Ground surface extraction is one of the classic tasks in airborne laser scanning (ALS) point cloud processing that is used for three-dimensional (3D) city modelling, infrastructure health monitoring, and disaster management. Many methods have been developed over the last three decades. Recently, Deep Learning (DL) has become the most dominant...

SCIPoC: Semantic Classification of Indoor Point Cloud: A study into the possibilities of classifying indoor point cloud using a Deep Learning approach

With the constantly evolving range of applications for technology the quality and amount of data constantly increases as well. In this growing data environment, there is a constant search to provide more value to all data that is available for as little effort as possible. Our research tries to add such additional value by diving into the...

Continuous Human Activity Classification from FMCW Radar with Bi-LSTM Networks

Recognition of human movements with radar for ambient activity monitoring is a developed area of research that yet presents outstanding challenges to address. In real environments, activities and movements are performed with seamless motion, with continuous transitions between activities of different duration and a large range of dynamic...

Hierarchical radar data analysis for activity and personnel recognition

Radar-based classification of human activities and gait have attracted significant attention with a large number of approaches proposed in terms of features and classification algorithms. A common approach in activity classification attempts to find the algorithm (features plus classifier) that can deal with multiple activities analysed in...

Human activity classification with radar signal processing and machine learning

As the number of older adults increases worldwide, new paradigms for indoor activity monitoring are required to keep people living at home independently longer. Radar-based human activity recognition has been identified as a sensing modality of choice because it is privacy-preserving and does not require end-users compliance or manipulation. In...

Driving risk classification methodology for intelligent drive in real traffic event

To solve the problem that existing driving data cannot correlate to the large number of vehicles in terms of driving risks, is the functionality of intelligent driving algorithm should be improved. This paper deeply explores driving data to build a link between massive driving data and a large number of sample vehicles for driving risk...

Influence of driver characteristics on emissions and fuel consumption

Fuel consumption and atmospheric pollution emissions of vehicles depend on driving conditions, the characteristics of the driver and the car. The influence of driving style on the environmental aspects of a car journey has been investigated. Driver characteristics were determined by a Driver Behaviour Questionnaire and observed acceleration...

Non-Vegetated Playa Morphodynamics Using Multi-Temporal Landsat Imagery in a Semi-Arid Endorheic Basin: Salar de Uyuni, Bolivia

Playas in endorheic basins are of environmental value and highly scientific because of their natural habitats of a wide variety of species and indicators for climatic changes and tectonic activities within continents. Remote sensing, due to its capability of acquiring repetitive data with synoptic coverage, provides a unique tool to monitor and...

An Exploratory Study on Authorship Verification Models for Forensic Purpose

Authorship verification is one subfield of authorship analysis. However, the majority of the research in the field of authorship analysis is on the authorship identification problem. The authorship verification problem has received less attention than the authorship identification problem. Thus, there is a demand for a study on the authorship...