Multiparty Homomorphic Encryption from Ring-Learning-with-Errors

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Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Li Zhang, Jiancheng Yang

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...

Springer International Publishing Ag2023

Cybersickness assessment framework(CSAF): An Open Source Repository for Standardized Cybersickness Experiments

Adriano Viegas Milani, Ronan Boulic, Nana Tian

Studies of cybersickness (CS) often require a significant invest- ment in creating the primary VR environment and other experiment- related features. In addition, minor differences in VR content in independent studies may lead to opposite results. This mot ...

IEEE2023

Challenges and approaches in bridging the biomimicry gap in biohybrid systems of fish and robots

Vaios Papaspyros

As the field of ethology advances, especially over the past two decades, the role of animal-robot interaction tools has increasingly become essential. This importance arises from the need for controlled, repetitive, repeatable, and long-duration experiment ...

EPFL2023

Friction and fracture: richness and complexity in dynamic rupture

Thibault Didier Roch

Understanding how things break and slide is of paramount importance to describe the dynamics of a broad range of physical systems. This includes day-to-day problems such as the breaking of a glass of wine or the sliding of skis on snow, but also engineerin ...

EPFL2023

High-precision optical magnetometry using Nitrogen Vacancies in CVD diamond

Hossein Babashah

Sensing weak magnetic fields is a topic of great importance in basic science and technology due to its wide range of applications. In this context, solid-state and nanoscale quantum sensors are poised to revolutionize the sensing platforms due to their ult ...

EPFL2023

TiC-SAT: Tightly-coupled Systolic Accelerator for Transformers

David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi, Joshua Alexander Harrison Klein

Transformer models have achieved impressive results in various AI scenarios, ranging from vision to natural language processing. However, their computational complexity and their vast number of parameters hinder their implementations on resource-constraine ...

2023

Motor-Unit Ordering of Blindly-Separated Surface-EMG Signals for Gesture Recognition

Pasquale Davide Schiavone

Hand gestures are one of the most natural and expressive way for humans to convey information, and thus hand gesture recognition has become a research hotspot in the human-machine interface (HMI) field. In particular, biological signals such as surface ele ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Computation Complexity Reduction Technique for Accurate Seizure Detection Implants

Alexandre Schmid, Keyvan Farhang Razi

An automatic seizure detection method from high-resolution intracranial-EEG (iEEG) signals is presented to minimize the computational complexity and realize real-time accurate seizure detection for biomedical implants. Complex signal processing on a large ...

IEEE2022

Cockroach: an open-source tool for point cloud processing in cad

Yves Weinand, Julien Gamerro, Andrea Settimi, Petras Vestartas

In the architecture, engineering and construction (AEC) sector, the use of point cloud data is not a novelty. Usually employed to retrieve data for inspecting construction sites or retrofitting pre-existing buildings, sensors like LiDAR cameras have been k ...

Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)2022

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

Maximilian Wieland Hofer

In this dissertation, I develop theory and evidence to argue that new technologies are central to how firms organize to create and capture value. I use computational methods such as reinforcement learning and probabilistic topic modeling to investigate thr ...

EPFL2022