Concept

Iris flower data set

Related publications (34)

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

Christian Leinenbach, Sergey Shevchik, Rafal Wróbel, Marc Leparoux

This study presents a self-supervised Bayesian Neural Network (BNN) framework using air-borne Acoustic Emission (AE) to identify different Laser Powder Bed Fusion (LPBF) process regimes such as Lack of Fusion, conduction mode, and keyhole without ground-tr ...

London2023

Bias at a Second Glance: A Deep Dive into Bias for German Educational Peer-Review Data Modeling

Vinitra Swamy, Thiemo Wambsganss

Natural Language Processing (NLP) has become increasingly utilized to provide adaptivity in educational applications. However, recent research has highlighted a variety of biases in pre-trained language models. While existing studies investigate bias in di ...

2022

Adaptive and Robust Partition Learning for Person Retrieval With Policy Gradient

Zhen Wei, Zhiye Wang, Peixia Li

Person retrieval aims at effectively matching the pedestrian images over an extensive database given a specified identity. As extracting effective features is crucial in a high-performance retrieval system, recent significant progress was achieved by part- ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Systematic sensor placement for structural anomaly detection in the absence of damaged states

Jan Sickmann Hesthaven, Caterina Bigoni, Zhenying Zhang

In structural health monitoring (SHM), risk assessment and decision strategies rely primarily on sensor responses. Simulated data can be generated to emulate the monitoring phenomena under different natural operational and environmental conditions in order ...

2020

DOMAIN ADAPTATION FOR GENERALIZATION OF FACE PRESENTATION ATTACK DETECTION IN MOBILE SETTINGS WITH MINIMAL INFORMATION

Sébastien Marcel, Amir Mohammadi

With face-recognition (FR) increasingly replacing fingerprint sensors for user-authentication on mobile devices, presentation attacks (PA) have emerged as the single most significant hurdle for manufacturers of FR systems. Current machine-learning based pr ...

IEEE2020

Lane Detection and Lane Changing Phenomena Identification with Data from a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

In the era of big data, new transportation-related concepts and methodologies need to be proposed for understanding how congestion propagates. pNEUMA, a unique dataset that was acquired during a first-of-its-kind experiment with a swarm of drones over a de ...

2020

Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

Modeling and predicting student learning in computer-based environments often relies solely on sequences of accuracy data. Previous research suggests that it does not only matter what we learn, but also how we learn. The detection and analysis of learning ...

2020

Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis

Cathrin Brisken, Kathryn Hess Bellwald, Jacques Rougemont

Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex data sets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small data sets. ...

2019

SemiHD: Semi-Supervised Learning Using Hyperdimensional Computing

Samuel Bosch, Mohsen Imani

In the Internet of Things (IoT), the large volume of data generated by sensors poses significant computational challenges in resource-constrained environments. Most existing machine learning algorithms are unable to train a proper model using a significant ...

IEEE2019

, , , ,

We present two wide-field catalogues of photometrically selected emission line galaxies (ELGs) at z approximate to 0.8 covering about 2800 deg(2)over the south galactic cap. The catalogues were obtained using a Fisher discriminant technique described in a ...

Oxford Univ Press2017

Graph Chatbot

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.