Training deep retrieval models with noisy datasets: Bag exponential loss

PATTERN RECOGNITION (p. 1-13) - 4/2021

https://doi.org/10.1016/j.patcog.2020.107811 View at source

• ISSN 0031-3203

• UC3M

Temporal segmentation and keyframe selection methods for user-generated video search-based annotation

EXPERT SYSTEMS WITH APPLICATIONS (p. 488-502) - 1/2015

https://doi.org/10.1016/j.eswa.2014.08.001 View at source

• EISSN 1873-6793
• ISSN 0957-4174

• UC3M

Probabilistic Topic Model for Context-Driven Visual Attention Understanding

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (p. 1653-1667) - 4/2019

https://doi.org/10.1109/tcsvt.2019.2909427 View at source

• EISSN 1558-2205
• ISSN 1051-8215

• UC3M

Perceptually-guided deep neural networks for ego-action prediction: Object grasping

PATTERN RECOGNITION (p. 223-235) - 4/2019

https://doi.org/10.1016/j.patcog.2018.11.013 View at source

• ISSN 0031-3203

• UC3M

Perceptual modeling in the problem of active object recognition in visual scenes

PATTERN RECOGNITION (p. 129-141) - 8/2016

https://doi.org/10.1016/j.patcog.2016.03.007 View at source

• ISSN 0031-3203

• UC3M

Neighborhood Matching for Image Retrieval

IEEE TRANSACTIONS ON MULTIMEDIA (p. 544-558) - 3/2017

https://doi.org/10.1109/tmm.2016.2616298 View at source

• EISSN 1941-0077
• ISSN 1520-9210

• UC3M

Goal-oriented top-down probabilistic visual attention model for recognition of manipulated objects in egocentric videos

SIGNAL PROCESSING-IMAGE COMMUNICATION (p. 418-431) - 11/2015

https://doi.org/10.1016/j.image.2015.05.006 View at source

• ISSN 0923-5965

• UC3M

Finding landmarks within settled areas using hierarchical density-based clustering and meta-data from publicly available images

EXPERT SYSTEMS WITH APPLICATIONS (p. 315-327) - 6/2019

https://doi.org/10.1016/j.eswa.2019.01.046 View at source

• EISSN 1873-6793
• ISSN 0957-4174

• UC3M

Exploiting visual saliency for assessing the impact of car commercials upon viewers

Multimedia Tools And Applications (p. 18903-18933) - 1/8/2018

10.1007/s11042-017-5339-9 View at source

• EISSN 1573-7721
• ISSN 1380-7501

• iMarina
• UC3M

Enriched dermoscopic-structure-based cad system for melanoma diagnosis

MULTIMEDIA TOOLS AND APPLICATIONS (p. 12171-12202) - 5/2018

10.1007/s11042-017-4879-3 View at source

• EISSN 1573-7721
• ISSN 1380-7501

• UC3M

Recognition of instrumental activities of daily living in egocentric video for activity monitoring of patients with dementia. In: Health monitoring and personalized feedback using multimedia data

Health monitoring and personalized feedback using multimedia data (p. 161-178) - 7/2015

Editor: SPRINGER

https://doi.org/10.1007/978-3-319-17963-6_9 View at source

• ISBN 978-3-319-17962-9

• UC3M

Fusion of Multiple Visual Cues for Object Recognition in Videos. In: Fusion in Computer Vision : Understanding Complex Visual Content

Fusion in Computer Vision : Understanding Complex Visual Content (p. 79-107) - 3/2014

Editor: SPRINGER

• ISBN 978-3-319-05695-1

• UC3M

UC3M High Level Feature Extraction at TRECVID 2008

TRECVID Workshop 2008 - 2008

• UC3M

Perceptually-guided Understanding of Egocentric Video Content: Recognition of Objects to Grasp

(p. 434-441) - 2018

10.1145/3206025.3206073 View at source

• ISBN 978-1-4503-5046-4

• UC3M

Object recognition with top-down visual attention modeling for behavioral studies

IEEE International Conference on Image Processing (ICIP 2015) (p. 4431-4435) - 2015

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/icip.2015.7351644 View at source

• ISBN 978-1-4799-8339-1

• UC3M

Modeling instrumental activities of daily living in egocentric vision as sequences of active objects and context for alzheimer disease research

1st ACM International Workshop on Multimedia Indexing and Information Retrieval for Healthcare (p. 11-14) - 2013

Editor: Association for Computing Machinery (ACM)

https://doi.org/10.1145/2505323.2505328 View at source

• ISBN 978-1-4503-2398-7

• UC3M

Mid-level feature set for specific event and anomaly detection in crowded scenes

20th IEEE International Conference on Image Processing (ICIP 2013). (p. 4001-4005) - 2013

Editor: IEEE - THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/icip.2013.6738824 View at source

• ISBN 978-1-4799-2341-0

• UC3M

Incorporating Spatio-Temporal Mid Level Features in a Region Segmentation Algorithm for Video Sequences

IEEE International Conference on Image Processing (ICIP'08) - 2008

• UC3M

Automatic learning of image representations combining content and metadata

2018 25th IEEE International Conference on Image Processing (ICIP) (p. 1972-1976) - 2018

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/icip.2018.8451566 View at source

• ISBN 978-1-4799-7061-2

• UC3M

A probabilistic topic approach for context-aware visual attention modeling

14th International Workshop on Content-Based Multimedia Indexing (CBMI 2016) (p. 1-6) - 2016

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/cbmi.2016.7500272 View at source

• ISBN 978-1-4673-8695-1

• UC3M

A Bayesian model for brain tumor classification using clinical-based features

IEEE International Conference on Image Processing (ICIP 2014) (p. 2779-2783) - 2014

Editor: IEEE - THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/icip.2014.7025562 View at source

• ISBN 978-1-4799-5751-4

• UC3M

Training Deep Retrieval Models with Noisy Datasets

Reading date: 26-03-2021

• UC3M

Hierarchical Representations for Spatio-Temporal Visual Attention Modeling and Understanding

Reading date: 15-02-2019

• UC3M

Generative models for image segmentation and representation

Reading date: 21-07-2011

Reading institution: CAMPUS DE LEGANES

• UC3M

Density-based clustering: algorithms and evaluation techniques

Reading date: 24-09-2021

• UC3M

CONTRIBUTIONS TO MELANOMA COMPUTER AIDED DIAGNOSIS SYSTEMS USING DERMOSCOPIC IMAGES

Reading date: 31-01-2020

• UC3M