Cross-Modal Learning of Housing Quality in Amsterdam

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Our dataset consists of very high-resolution aerial images (50cm) and a digital elevation model (50cm) that covers approx. 2300 km2 of land above 2000m altitude in the southwestern part of Switzerland. Our land cover labels focus on alpine land cover that ...

Many species aggregate in dense colonies. Species-specific spatial patterns provide clues about how colonies are shaped by various (a)biotic factors, including predation, temperature regulation or disease transmission. Using aerial imagery, we examined the ...

In this paper we explore deep learning models to monitor longitudinal liveability changes in Dutch cities at the neighbourhood level. Our liveability reference data is defined by a country-wise yearly survey based on a set of indicators combined into a liv ...

Introduced to enable a wider use of Earth Observation images using natural language, Remote Sensing Visual Question Answering (RSVQA) remains a challenging task, in particular for questions related to counting. To address this specific challenge, we propos ...

Automated animal censuses with aerial imagery are a vital ingredient towards wildlife conservation. Recent models are generally based on deep learning and thus require vast amounts of training data. Due to their scarcity and minuscule size, annotating anim ...

Urban planners are increasingly interested in understanding what makes a neighbourhood pleasant and liveable. In this paper, we use the overhead perspective as a new way to describe and understand liveability of city neighborhoods. We predict building qual ...

The recent advances in state estimation, perception, and navigation algorithms have significantly contributed to the ubiquitous use of quadrotors for inspection, mapping, and aerial imaging. To further increase the versatility of quadrotors, recent works i ...

Mapping the location and size of solar installations in urban areas can be a valuable input for policymakers and for investing in distributed energy infrastructures. Machine Learning techniques, combined with satellite and aerial imagery, allow to overcome ...

We describe the development of a BVLOS (Beyond Visual Line-Of-Sight) model aircraft (UAV). The broad design requirements included (i) fuselage capable of accommodating an imaging package or other instrumentation, (ii) suitability for over-lake BVLOS author ...

We propose a novel approach to reconstructing curvilinear tree structures evolving over time, such as road networks in 2D aerial images or neural structures in 3D microscopy stacks acquired in vivo. To enforce temporal consistency, we simultaneously proces ...

t is well known that accurate aerial position and attitude control is beneficial for image orientation in airborne photogrammetry. The aerial control is traditionally obtained by Kalman filtering/smoothing inertial and GNSS observations prior to the bundle ...

Unmanned Aerial Vehicles are becoming increasingly popular for a broad variety of tasks ranging from aerial imagery to objects delivery. With the expansion of the areas, where drones can be efficiently used, the collision risk with other flying objects inc ...

This study deals with semantic segmentation of high-resolution (aerial) images where a semantic class label is assigned to each pixel via supervised classification as a basis for automatic map generation. Recently, deep convolutional neural networks (CNNs) ...

Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resol ...

This study highlights the benefits of precise aerial position and attitude control in the context of mapping with Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline ins ...

Finding the centerline and estimating the radius of linear structures is a critical first step in many applications, ranging from road delineation in 2D aerial images to modeling blood vessels, lung bronchi, and dendritic arbors in 3D biomedical image stac ...

In proximity lithography, interference and diffraction effects arise when printing small features because of the proximity gap. Different techniques are used in order to control and take advantage of theses effects. In this paper, the focus is set on the M ...

This study highlights the benefit of precise aerial position control in the context of mapping using frame-based imagery taken by small UAVs. We execute several flights with a custom Micro Aerial Vehicle (MAV) octocopter over a small calibration field equi ...

This study examines the effects of land-use policies and natural events on the evolution of two wooded pastures in the Jura Mountains in Switzerland between 1934 and 2000. The socioeconomic context and the local conditions were seen as major driving forces ...

While the role of hemodynamic variables on the development of intimal hyperplasia in arteriovenous fistulas for hemodialysis has been examined, less is known about the intramural biomechanical factors. In this study, arteriovenous fistulas were created by ...

Cross-Modal Learning of Housing Quality in Amsterdam

Chat with Graph Search

swissALPS: a Dataset for Imbalanced Land Cover Mapping in Alpine Regions

Stay close, but not too close: aerial image analysis reveals patterns of social distancing in seal colonies

Time Series Analysis of Urban Liveability

Multi-task prompt-RSVQA to explicitly count objects on aerial images

Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images

Liveability from Above: Understanding Quality of Life with Overhead Imagery and Deep Neural Networks

The Foldable Drone: A Morphing Quadrotor That Can Squeeze and Fly

Deep learning in the built environment: automatic detection of rooftop solar panels using Convolutional Neural Networks

Lake Imaging and Monitoring Aerial Drone

Reconstructing Evolving Tree Structures in Time Lapse Sequences by Enforcing Time-Consistency

Bundle adjustment with raw inertial observations

Vision-based detection of aircrafts and UAVs

Learning Aerial Image Segmentation from Online Maps

Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response

Applicability Of New Approaches Of Sensor Orientation To Micro Aerial Vehicles

Multiscale Centerline Detection

Coherence management in lithography printing systems

Mapping with MAV: Experimental Study on the Contribution of Absolute and Relative Aerial Position Control

A Contextual Analysis of Land-Use and Vegetation Changes in Two Wooded Pastures in the Swiss Jura Mountains

Biomechanical, morphological and zero-stress state characterization of jugular vein remodeling in arteriovenous fistulas for hemodialysis