From thermal comfort to heat mitigation action: A reproducible QGIS plugin for calculating the physiological equivalent temperature in Dutch cities for informed strategies for mitigating heat stress in public spaces, in a Rotterdam case study

In the summer of 2023, heatwaves became quite prominent in the south of Europe. Due to the extreme heat, the health of those citizens was affected. The Netherlands Meteorological Institute predicts an increase in heatwaves in the future for the Netherlands as well. The main research question is how to propose a strategy for a liveable...

Architectural Pipeline - Pipeline Architecture: An experiment into the role of topological graphs in the early stages of architectural design in the era of machine learning

The realm of architectural design and conceptualization, despite witnessing advancements in design complexity facilitated by technological tools and fabrication techniques, appears to have experienced limited transformative change over time in the way we begin our design process. But is there an alternative way to look at architecture ? Perhaps...

Domain shift-aware Ensemble-based Visual Place Recognition

VPR describes a task where an agent (e.g., a robot) attempts to recognize its current location by comparing the incoming visual data from its sensor(s) (query images), usually a camera, to geotagged reference images. Both query and reference images are described using a feature extractor, and the query descriptor is matched to its closest...

SliceNet: Street-to-Satellite Image Metric Localization using Local Feature Matching

This work addresses visual localization for intelligent vehicles. The task of cross-view matching-based localization is to estimate the geo-location of a vehicle-mounted camera by matching the captured street view image with an overhead-view satellite map containing the vehicle's local surroundings. This local satellite view image can be...

Towards a Safer and More Reliable Selective Classifier: With Human Knowledge and Value Incorporated

While the performance of traditional confidence-based rejectors is heavily dependent on the calibration of the pretrained model, this study proposes the concept of feature-based rejectors and the whole pipeline where such rejector can be used in. Multiple design and development decisions along the implementation are discussed in the paper -...

Evaluation of Video Summarization Using Fully Convolutional Sequence Networks on Action Localization Datasets

In the problem of video summarization, the goal is to select a subset of the input frames conveying the most important information of the input video. The collection of data proves to be a challenging task. In part because there exists a disagreement among human annotators on what segments of a video should be considered important for a summary....

Evaluating the Supervised Video Summarization Model VASNet on an Action Localization Dataset

There is growing research on automated video summarization following the rise of video content. However, the subjectivity of the task itself is still an issue to address. This subjectivity stems from the fact that there can be different summaries for the same video depending on which parts one considers important. Supervised models especially...

Evaluation of Video Summarization using DSNet and Action Localization Datasets

In this paper, the DSNet framework used for automatic video summarization gets reviewed when using action localization datasets. The problem facing video summarizations using deep learning techniques is that datasets can be subjective depending on preferences of human annotators, making for noise in the labeling. This paper will look at a anchor...

Evaluation of the SUM-GAN-AAE method for Video Summarization

Video summarization is a task which many researchers have tried to automate with deep learning methods. One of these methods is the SUM-GAN-AAE algorithm developed by Apostolidis et al. which is an unsupervised machine learning method evaluated in this study. The research aims at testing the algorithm's performance on the Breakfast dataset,...