| |
Records |
Links |
|
Author |
Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades |
|
| |
Title |
Exploring the impact of inter-query variability on the performance of retrieval systems |
Type |
Conference Article |
| |
Year |
2014 |
Publication |
11th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
|
| |
Volume |
8814 |
Issue |
|
Pages |
413–420 |
|
| |
Keywords |
|
|
| |
Abstract |
This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes. |
|
| |
Address |
Algarve; Portugal; October 2014 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0302-9743 |
ISBN |
978-3-319-11757-7 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICIAR |
|
| |
Notes |
IAM; DAG; 600.060; 600.061; 600.077; 600.075 |
Approved |
no |
|
| |
Call Number  |
Admin @ si @ BGB2014 |
Serial |
2559 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Sonia Baeza; R.Domingo; M.Salcedo; G.Moragas; J.Deportos; I.Garcia Olive; Carles Sanchez; Debora Gil; Antoni Rosell |
|
| |
Title |
Artificial Intelligence to Optimize Pulmonary Embolism Diagnosis During Covid-19 Pandemic by Perfusion SPECT/CT, a Pilot Study |
Type |
Journal Article |
| |
Year |
2021 |
Publication |
American Journal of Respiratory and Critical Care Medicine |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
IAM; 600.145 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BDS2021 |
Serial |
3591 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate |
|
| |
Title |
Is there a pattern of Chromosome territoriality along mice spermatogenesis? |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
3rd Spanish MeioNet Meeting Abstract Book |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
55-56 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Miraflores de la Sierra; Madrid; June 2017 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
MEIONET |
|
| |
Notes |
IAM; 600.096; 600.145 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
2958 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Jose Elias Yauri; Aura Hernandez-Sabate; Pau Folch; Debora Gil |
|
| |
Title |
Mental Workload Detection Based on EEG Analysis |
Type |
Conference Article |
| |
Year |
2021 |
Publication |
Artificial Intelligent Research and Development. Proceedings 23rd International Conference of the Catalan Association for Artificial Intelligence. |
Abbreviated Journal |
|
|
| |
Volume |
339 |
Issue |
|
Pages |
268-277 |
|
| |
Keywords |
Cognitive states; Mental workload; EEG analysis; Neural Networks. |
|
| |
Abstract |
The study of mental workload becomes essential for human work efficiency, health conditions and to avoid accidents, since workload compromises both performance and awareness. Although workload has been widely studied using several physiological measures, minimising the sensor network as much as possible remains both a challenge and a requirement.
Electroencephalogram (EEG) signals have shown a high correlation to specific cognitive and mental states like workload. However, there is not enough evidence in the literature to validate how well models generalize in case of new subjects performing tasks of a workload similar to the ones included during model’s training.
In this paper we propose a binary neural network to classify EEG features across different mental workloads. Two workloads, low and medium, are induced using two variants of the N-Back Test. The proposed model was validated in a dataset collected from 16 subjects and shown a high level of generalization capability: model reported an average recall of 81.81% in a leave-one-out subject evaluation. |
|
| |
Address |
Virtual; October 20-22 2021 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CCIA |
|
| |
Notes |
IAM; 600.139; 600.118; 600.145 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
3723 |
|
| Permanent link to this record |
