Concept

Confusion matrix

Related publications (29)

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

Amsterdam2024

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

Kamiar Aminian, Anisoara Ionescu, Abolfazl Soltani, Francesca Salis

Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...

BMC2023

The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Enrico Amico, Antonella Romano

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to ...

ELSEVIER SCI LTD2022

Estimating The Degree of Sleepiness by Integrating Articulatory Feature Knowledge In Raw Waveform Based CNNs

Julian David Fritsch, Subrahmanya Pavankumar Dubagunta

Speech-based degree of sleepiness estimation is an emerging research problem. In the literature, this problem has been mainly addressed through modeling of low level of descriptors. This paper investigates an end-to-end approach, where given raw waveform a ...

Idiap2019

Chemical machine learning with kernels: The impact of loss functions

Volkan Cevher, Quoc Tran Dinh, Sandip De, Junhong Lin

Machine learning promises to accelerate materials discovery by allowing computational efficient property predictions from a small number of reference calculations. As a result, the literature has spent a considerable effort in designing representations tha ...

2019

Chemical machine learning with kernels: The key impact of loss functions

Volkan Cevher, Sandip De, Junhong Lin, Van Quang Nguyen

Machine learning promises to accelerate materials discovery by allowing computational efficient property predictions from a small number of reference calculations. As a result, the literature spent a considerable effort in designing representations that ca ...

2018

The complexity of error metrics

Mathias Soeken

Approximate computing exploits the fact that many applications do not require the results to be exact but not to exceed a threshold in a given error metric. Algorithms in approximate computing require to compute the error of the approximation in order to m ...

ELSEVIER SCIENCE BV2018

A Non-linear Filter to Detect Atrial Activation from Intracardiac Electrograms

Jean-Marc Vesin, Sasan Yazdani, Andréa Buttu, Etienne Pruvot

Atrial activation (AA) detection during atrial fibrillation (AF) can be considered as a first step in estimating AF characteristics such as the AF cycle length. The detection of AA from intracardiac electrograms (EGM) remains challenging due to the constan ...

2017

, , , , ,

Permission systems are the main defense that mobile platforms, such as Android and iOS, offer to users to protect their private data from prying apps. However, due to the tension between usability and control, such systems have several limitations that oft ...

IEEE2017

Wearable barometric pressure sensor to improve postural transition recognition of mobility-impaired stroke patients

Kamiar Aminian, Anisoara Ionescu, Fabien Massé

Sit-to-stand and Stand-to-sit transfers (STS) provide relevant information regarding the functional limitation of mobility- impaired patients. The characterization of STS pattern using a single trunk fixed inertial sensor has been proposed as an objective ...

Institute of Electrical and Electronics Engineers2016

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.