Publications associées à Evaluation of binary classifiers

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Within the scope of the implementation of a nuclear data pipeline aiming at producing the best possible evaluated nuclear data files, a major point is the production of relevant sensitivity coefficients when including integral benchmark information. Thanks ...

Elsevier Science Sa2024

Model-Class Selection Using Clustering and Classification for Structural Identification and Prediction

Ian Smith, Sai Ganesh Sarvotham Pai, Masoud Sanayei

Structural identification using physics-based models and subsequent prediction have much potential to enhance civil infrastructure asset-management decision-making. Interpreting monitoring information in the presence of multiple uncertainty sources and sys ...

2021

Evaluating salient object detection in natural images with multiple objects having multi-level saliency

Sabine Süsstrunk, Gökhan Yildirim

Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...

2020

A Sub-μW/Channel, 16-Channel Seizure Detection and Signal Acquisition SoC Based on Multichannel Compressive Sensing

Alexandre Schmid, Reza Ranjandish

An accurate 16-channel seizure detection system-on-chip is presented, which is based on extracting features from the compressed recorded data using multichannel compressive sensing (MCS). MCS is used to reduce the transmission data rate of sparse biologica ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Using Robust Principal Component Analysis to Reduce EEG Intra-Trial Variability

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Ping-Keng Jao

Practical brain-computer interfaces need to overcome several challenges, including tolerance to signal variability within- and across sessions. We introduce Robust Principal Component Analysis (RPCA) as a potential approach to tackle intra-trial variabilit ...

2018

Learning Pattern Transformation Manifolds for Classification

Pascal Frossard, Elif Vural

Manifold models provide low-dimensional representations that are useful for analyzing and classifying data in a transformation-invariant way. In this paper we study the problem of jointly building multiple pattern transformation manifolds from a collection ...

2012

Segmentation of head and neck lymph node regions for radiotherapy planning, using active contour based atlas registration

Jean-Philippe Thiran, Meritxell Bach Cuadra, Valérie Duay, Subrahmanyam Venkata Ravi Mohana Sai Gorthi, Nawal Houhou

In this paper, we present the segmentation of the head and neck lymph node regions using a new active contour based atlas registration model. We propose to segment the lymph node regions without directly including them in the atlas registration process; in ...

2009

Sleep and Wake Classification With ECG and Respiratory Effort Signals

Dario Floreano, Claudio Mattiussi, Walter Karlen

We describe a method for the online classification of sleep/wake states based on cardiorespiratory signals produced by wearable sensors. The method was conceived in view of its applicability to a wearable sleepiness monitoring device. The method uses a Fas ...

2009

Identification of Aging Faces using A-stack Classification Model

Andrzej Drygajlo, Weifeng Li

The problem of time validity of biometric models has received only a marginal attention from researchers. In this paper, we investigate the aging influence on the classifier scores of genuine client. Our studies show that as age progresses the classifier s ...

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Principled Detection-by-Classification from Multiple Views

Pascal Fua, François Fleuret, Jérôme Berclaz

Machine-learning based classification techniques have been shown to be effective at detecting objects in complex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically rel ...

2008