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

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

Devis Tuia

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 ...

IEEE2021

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

Devis Tuia, Benjamin Alexander Kellenberger

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 ...

IEEE2021

Cross-Modal Learning of Housing Quality in Amsterdam

Devis Tuia

In our research we test data and models for the recognition of housing quality in the city of Amsterdam from ground-level and aerial imagery. For ground-level images we compare Google StreetView (GSV) to Flickr images. Our results show that GSV predicts th ...

ACM2021

3D Structure From 2D Microscopy Images Using Deep Learning

Suliana Manley, Christian Sieben

Understanding the structure of a protein complex is crucial in determining its function. However, retrieving accurate 3D structures from microscopy images is highly challenging, particularly as many imaging modalities are two-dimensional. Recent advances i ...

Frontiers Media Sa2021

Perceiving Humans: from Monocular 3D Localization to Social Distancing

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

Perceiving humans in the context of Intelligent Transportation Systems (ITS) often relies on multiple cameras or expensive LiDAR sensors. In this work, we present a new cost-effective vision-based method that perceives humans' locations in 3D and their bod ...

IEEE Institute of Electrical and Electronics Engineers2022

Promoting Connectivity of Network-Like Structures by Enforcing Region Separation

Pascal Fua, Mateusz Kozinski, Doruk Oner, Leonardo Citraro

We propose a novel, connectivity-oriented loss function for training deep convolutional networks to reconstruct network-like structures, like roads and irrigation canals, from aerial images. The main idea behind our loss is to express the connectivity of r ...

2022

Estimating Nonplanar Flow from 2D Motion-blurred Widefield Microscopy Images via Deep Learning

Michael Stefan Daniel Liebling, Adrian Shajkofci

Optical flow is a method aimed at predicting the movement velocity of any pixel in the image and is used in medicine and biology to estimate flow of particles in organs or organelles. However, a precise optical flow measurement requires images taken at hig ...

IEEE2021

Reward biases spontaneous neural reactivation during sleep

Dimitri Nestor Alice Van De Ville

Sleep favors the reactivation and consolidation of newly acquired memories. Yet, how our brain selects the noteworthy information to be reprocessed during sleep remains largely unknown. From an evolutionary perspective, individuals must retain information ...

Nature Research2021

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Dario Floreano, Fabrizio Schiano

We address the detection, tracking, and relative localization of the agents of a drone swarm from a human perspective using a headset equipped with a single camera and an Inertial Measurement Unit (IMU). We train and deploy a deep neural network detector o ...

2021

Automatic detection of potential mosquito breeding sites from aerial images acquired by unmanned aerial vehicles

Vitor Pessoa Colombo

The World Health Organization (WHO) has stated that effective vector control measures are critical to achieving and sustaining reduction of vector-borne infectious disease incidence. Unmanned aerial vehicles (UAVs), popularly known as drones, can be an imp ...

2021

LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals

Pascal Fua, Pavan P Ramdya, Helge Jochen Rhodin, Semih Günel, Victor Lobato Rios, Adám Gosztolai, Daniel Eduardo Morales Garza

LiftPose3D infers three-dimensional poses from two-dimensional data or from limited three-dimensional data. The approach is illustrated for videos of behaving Drosophila, mice, rats and macaques. ...

Nature Publishing Group2021

Additive manufacturing of a precious bulk metallic glass

Roland Logé, Jamasp Jhabvala, Antonia Neels, Navid Sohrabi, Güven Kurtuldu, Annapaola Parrilli

For the first time, a high-density amorphous and crack-free bulk metallic glass (BMG) based on a precious metal (PdCuNiP) was produced via additive manufacturing (AM). Laser powder-bed fusion (LPBF) was used for the fabrication of the samples, and led to a ...

2021