Skip To Main Content
Jose Dolz on Muck Rack

Jose Dolz

As seen in: arXiv, MDPI, Dialnet - Universidad de La Rioja, Espacio Logopédico
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile
Back to Jose Dolz’s profile

Articles by Jose Dolz

Computer Science > Computer Vision and Pattern Recognition

|
By Stergios Christodoulidis, Maria Vakalopoulou, Jose Dolz
| arXiv
Deep neural networks remain vulnerable to adversarial perturbations, which can distort not only predictions but also confidence scores, undermining uncertainty calibration. While existing certification methods focus on preserving the predicted category, providing guarantees on how calibration behaves under adversarial attacks remains overlooked.
Open in Who Shared Issue with article?

AInstein: Assessing the Feasibility of AI-Generated Approaches to Research Problems

|
By Gaurav Sahu, Marco Pedersoli, Laurent Charlin, Jose Dolz
| arXiv
Open in Who Shared Issue with article?

Dibujo técnico: 100 ejercicios prácticos : visualización de piezas

|
By Jose Dolz, Javier Rodrigo, Domínguez Rodrigo, Martí Dolz
| Dialnet - Universidad de La Rioja
Ayuda Buscar en la ayuda Buscar en la ayuda
Open in Who Shared View Duplicates (412) Issue with article?

Deep Learning Algorithms for Bladder Cancer Segmentation on Multi-Parametric MRI

|
By Julien P. Nicolas, Dheeraj Gopireddy, Jose Dolz, Kazim Z. Gumus
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Open in Who Shared View Duplicates (275) Issue with article?

LP++: A Surprisingly Strong Linear Probe for Few-Shot CLIP

|
By Ismail Ben, Jose Dolz, Malik Boudiaf, Fereshteh Shakeri
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (386) Issue with article?

Estrés postural. Ejercicios y mejora de los hábitos. José J. Pedrosa, Juan C. Gaspar, José L. Dolz, Félix Barbolla, Riccardo Azzolini - espacioLogopedico

|
By Jose Dolz, José J. Pedrosa Verified, Juan C. Gaspar, Félix Barbolla
| Espacio Logopédico
¿Es el estrés postural una manifestación orgánica de los factores psicosociales que nos van moldeando como individuos? Nuestro organismo es la muestra más evidente y directa que percibimos cuando nos superan las cargas físicas y mentales. Con frecuencia, nos afectan presiones y fuerzas que alteran la representación que nos hacemos de las circunstancias. En la adaptación postural también convergen todas las variables de nuestra relación con el entorno.
Open in Who Shared Issue with article?

[2312.12730] A Closer Look at the Few-Shot Adaptation of Large Vision-Language Models

|
By Ismail Ben, Ismail Ben Ayed, Jose Dolz, Sina Hajimiri
| arXiv
[Submitted on 20 Dec 2023] Title:A Closer Look at the Few-Shot Adaptation of Large Vision-Language Models Download a PDF of the paper titled A Closer Look at the Few-Shot Adaptation of Large Vision-Language Models, by Julio Silva-Rodriguez and Sina Hajimiri and Ismail Ben Ayed and Jose Dolz Download PDF HTML (experimental) Abstract:Efficient transfer learning (ETL) is receiving increasing attention to adapt large pre-trained language-vision models on downstream tasks with a few labeled samples.
Open in Who Shared Issue with article?

Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation

|
By Cesar Martinez Verified, Enzo Ferrante, Jose Dolz
| arXiv
arXiv:2112.12218 (cs) [Submitted on 22 Dec 2021 (v1), last revised 2 Jun 2023 (this version, v3)] Download a PDF of the paper titled Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation, by Agostina Larrazabal and 3 other authors Download PDF Submission history From: Enzo Ferrante [ view email] [v1] Wed, 22 Dec 2021 20:34:20 UTC (5,932 KB) [v2] Tue, 30 May 2023 21:01:09 UTC (2,542 KB) [v3] Fri, 2 Jun 2023 14:47:01 UTC (2,542 KB)...
Open in Who Shared View Duplicates (679) Issue with article?

The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration

|
By Ismail Ben, Ismail Ben Ayed, Jose Dolz, Adrian Galdran
| arXiv
[Submitted on 30 Nov 2021 ( v1 ), last revised 5 Jul 2023 (this version, v4)] Title:The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration Download a PDF of the paper titled The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration, by Bingyuan Liu and 3 other authors Download PDF Abstract: In spite of the dominant performances of deep neural networks, recent works have shown that they are poorly calibrated, resulting in over-confident...
Open in Who Shared Issue with article?
Show More