Publications associées à Low-latency speaker spotting with online diarization and detection

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

Nature Portfolio2024

Technology-Aware Logic Synthesis for Superconducting Electronics

Giovanni De Micheli, Dewmini Sudara Marakkalage, Siang-Yun Lee, Alessandro Tempia Calvino, Mingfei Yu, Rassul Bairamkulov

Superconducting electronics provide us with cryogenic digital circuits that can rival established technologies in performance and energy consumption. Today, the lack of tools for the design of large-scale integrated superconducting circuits is a major obst ...

2024

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Sabine Süsstrunk, Alessio Verardo, Yufan Ren, Peter Arpad Grönquist, Qingyi He

Video DeepFakes are fake media created with Deep Learning (DL) that manipulate a person’s expression or identity. Most current DeepFake detection methods analyze each frame independently, ignoring inconsistencies and unnatural movements between frames. Som ...

2024

Lotic-SIPCO2: Adaptation of an open-source CO2 sensor system and examination of associated emission uncertainties across a range of stream sizes and land uses

Andrew Lean Robison

River networks play a crucial role in the global carbon cycle, as relevant sources of carbon dioxide (CO2) to the atmosphere. Advancements in high-frequency monitoring in aquatic environments have enabled measurement of dissolved CO2 concentration at tempo ...

Association for the Sciences of Limnology and Oceanography (ASLO)2024

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Evann Pierre Guy Courdier

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

EPFL2024

In-Sensor Passive Speech Classification with Phononic Metamaterials

Luis Guillermo Villanueva Torrijo, Daniel Moreno Garcia

Mitigating the energy requirements of artificial intelligence requires novel physical substrates for computation. Phononic metamaterials have vanishingly low power dissipation and hence are a prime candidate for green, always-on computers. However, their u ...

Wiley-V C H Verlag Gmbh2024

TSLAM: a tag-based object-centered monocular navigation system for augmented manual woodworking

Yves Weinand, Julien Gamerro, Andrea Settimi, Hong-Bin Yang

TimberSLAM (TSLAM) is an object-centered, tag-based visual self-localization and mapping (SLAM) system for monocular RGB cameras. It was specifically developed to support a robust and augmented reality pipeline for close-range, noisy, and cluttered fabrica ...

2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Sparse Autoencoders for Speech Modeling and Recognition

Selen Hande Kabil

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

EPFL2023

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

Bo Du, Li Zhang, Zhigang Li, 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

Multiparty Homomorphic Encryption: from Theory to Practice

Christian Vincent Mouchet

Multiparty homomorphic encryption (MHE) enables a group of parties to encrypt data in a way that (i) enables the evaluation of functions directly over its ciphertexts and (ii) enforces a joint cryptographic access-control over the underlying data. By exten ...

EPFL2023

Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation

Zhigang Li, Haoqi Wang

We generalize the class vectors found in neural networks to linear subspaces (i.e., points in the Grassmann manifold) and show that the Grassmann Class Representation (GCR) enables simultaneous improvement in accuracy and feature transferability. In GCR, e ...

Ieee Computer Soc2023

Practical Implementations of Remote Power Side-Channel and Fault-Injection Attacks on Multitenant FPGAs

Francesco Regazzoni, Mirjana Stojilovic, Ognjen Glamocanin, Dina Gamaleldin Ahmed Shawky Mahmoud

Cloud computing environments increasingly provision FPGAs because of their fine-grained, highly parallel, and flexible hardware architecture. The availability of FPGAs in the cloud fueled research on the security risks associated with exposing FPGA fabric ...

Springer, Cham2023

Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

Julian David Fritsch

Atypical aspects in speech concern speech that deviates from what is commonly considered normal or healthy. In this thesis, we propose novel methods for detection and analysis of these aspects, e.g. to monitor the temporary state of a speaker, diseases tha ...

EPFL2023

Projector-based augmented stacking framework for irregularly shaped objects

Yves Weinand, Katrin Beyer, Julien Gamerro, Andrea Settimi, Qianqing Wang, Edward Carlo Giorgio Andò

Augmented reality in additive fabrication is predominantly applied to the manufacturing of structures from regularly shaped materials. Our work however embraces natural heterogeneity, by focusing on the assembly of irregularly shaped elements such as miner ...

2023

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

Advancing atomic force microscopy through open source instrumentation

Mustafa Kangül

Atomic force microscopy (AFM), a member of the scanning probe microscopy (SPM) family, holds a unique position as a nano-characterization instrument in the fields of physics, chemistry, and biology. Its ability to provide atomic resolution and operate in v ...

EPFL2023

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Saeed Saadatnejad

Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...

EPFL2023

Diversity of radial spin textures in chiral materials

Oleg Yazyev, Alberto Crepaldi, Daniel Gosalbez Martinez

We introduce a classification of the radial spin textures in momentum space that emerge at the high-symmetry points in crystals characterized by nonpolar chiral point groups (D2, D3, D4, D6, T, O). Based on the symmetry constraints imposed by these point g ...

Amer Physical Soc2023

Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan region

Danya Li

Crop maps are crucial for agricultural monitoring and food management and can additionally support domain-specific applications, such as setting cold supply chain infrastructure in developing countries. Machine learning (ML) models, combined with freely-av ...

Elsevier2023