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ORCIDRicardo Guerrero
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- affiliation: Imperial College London, UK
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2020 – today
- 2023
[j10]Ricardo Guerrero, Christoph Lattemann, Pia Gebbing:
Helping Personal Service Firms to Cope with Digital Transformation: Evaluation of a Digitalization Maturity Model. Pac. Asia J. Assoc. Inf. Syst. 15(2): 1 (2023)- [c28]Adrian Bulat, Ricardo Guerrero, Brais Martínez, Georgios Tzimiropoulos:
FS-DETR: Few-Shot DEtection TRansformer with prompting and without re-training. ICCV 2023: 11759-11768 - [c27]Yuting Wang, Ricardo Guerrero, Vladimir Pavlovic:
D2F2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation. WACV 2023: 22-31 - 2022
- [c26]Minyoung Kim, Ricardo Guerrero, Hai Xuan Pham, Vladimir Pavlovic:
Variational Continual Proxy-Anchor for Deep Metric Learning. AISTATS 2022: 4552-4573 - [c25]Victor Escorcia, Ricardo Guerrero, Xiatian Zhu, Brais Martínez:
SOS! Self-supervised Learning over Sets of Handled Objects in Egocentric Action Recognition. ECCV (13) 2022: 604-620 - [i20]Victor Escorcia, Ricardo Guerrero, Xiatian Zhu, Brais Martínez:
SOS! Self-supervised Learning Over Sets Of Handled Objects In Egocentric Action Recognition. CoRR abs/2204.04796 (2022) - [i19]Adrian Bulat, Ricardo Guerrero, Brais Martínez, Georgios Tzimiropoulos:
FS-DETR: Few-Shot DEtection TRansformer with prompting and without re-training. CoRR abs/2210.04845 (2022) - [i18]Yuting Wang, Ricardo Guerrero, Vladimir Pavlovic:
D2DF2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation. CoRR abs/2212.01376 (2022) - 2021
- [c24]Hai Xuan Pham, Ricardo Guerrero, Vladimir Pavlovic
, Jiatong Li:
CHEF: Cross-modal Hierarchical Embeddings for Food Domain Retrieval. AAAI 2021: 2423-2430 - [c23]Fangda Han, Guoyao Hao, Ricardo Guerrero, Vladimir Pavlovic:
Multi-attribute Pizza Generator: Cross-domain Attribute Control with Conditional StyleGAN. BMVC 2021: 318 - [c22]Minyoung Kim, Ricardo Guerrero, Vladimir Pavlovic:
Learning Disentangled Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach. ACM Multimedia 2021: 2862-2870 - [c21]Ricardo Guerrero, Hai Xuan Pham, Vladimir Pavlovic:
Cross-modal Retrieval and Synthesis (X-MRS): Closing the Modality Gap in Shared Subspace Learning. ACM Multimedia 2021: 3192-3201 - [c20]Ricardo Guerrero, Michael Spranger, Shuqiang Jiang, Chong-Wah Ngo:
AIxFood'21: 3rd Workshop on AIxFood. ACM Multimedia 2021: 5688-5689 - [e1]Ricardo Guerrero, Michael Spranger, Shuqiang Jiang, Chong-Wah Ngo:
AI & Food'21: Proceedings of the 3rd Workshop on AIxFood, Virtual Event, China, 20 October 2021. ACM 2021, ISBN 978-1-4503-8673-9 [contents] - [i17]Hai Xuan Pham, Ricardo Guerrero, Jiatong Li, Vladimir Pavlovic:
CHEF: Cross-modal Hierarchical Embeddings for Food Domain Retrieval. CoRR abs/2102.02547 (2021) - [i16]Fangda Han, Guoyao Hao, Ricardo Guerrero, Vladimir Pavlovic:
Multi-attribute Pizza Generator: Cross-domain Attribute Control with Conditional StyleGAN. CoRR abs/2110.11830 (2021) - 2020
- [j9]Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, Hongwei Li, Ricardo Guerrero, Rozanna Meijboom, Stewart Wiseman, Adam Waldman, Jianguo Zhang, Daniel Rueckert, Joanna M. Wardlaw, Taku Komura:
Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images. Comput. Medical Imaging Graph. 79: 101685 (2020) - [c19]Jiatong Li, Fangda Han, Ricardo Guerrero, Vladimir Pavlovic:
Picture-to-Amount (PITA): Predicting Relative Ingredient Amounts from Food Images. ICPR 2020: 10343-10350 - [c18]Fangda Han, Ricardo Guerrero, Vladimir Pavlovic:
CookGAN: Meal Image Synthesis from Ingredients. WACV 2020: 1439-1447 - [i15]Fangda Han, Ricardo Guerrero, Vladimir Pavlovic:
CookGAN: Meal Image Synthesis from Ingredients. CoRR abs/2002.11493 (2020) - [i14]Jiatong Li, Fangda Han, Ricardo Guerrero, Vladimir Pavlovic:
Picture-to-Amount (PITA): Predicting Relative Ingredient Amounts from Food Images. CoRR abs/2010.08727 (2020) - [i13]Minyoung Kim, Ricardo Guerrero, Vladimir Pavlovic:
Learning Disentangled Latent Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach. CoRR abs/2012.00682 (2020) - [i12]Ricardo Guerrero, Hai Xuan Pham, Vladimir Pavlovic:
Cross-modal Retrieval and Synthesis (X-MRS): Closing the modality gap in shared subspace. CoRR abs/2012.01345 (2020) - [i11]Fangda Han, Guoyao Hao, Ricardo Guerrero, Vladimir Pavlovic:
MPG: A Multi-ingredient Pizza Image Generator with Conditional StyleGANs. CoRR abs/2012.02821 (2020)
2010 – 2019
- 2019
- [c17]Ognjen (Oggi) Rudovic, Yuria Utsumi, Ricardo Guerrero, Kelly Peterson, Daniel Rueckert, Rosalind W. Picard:
Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes. MLHC 2019: 181-196 - [c16]Jiatong Li, Ricardo Guerrero, Vladimir Pavlovic:
Deep Cooking: Predicting Relative Food Ingredient Amounts from Images. MADiMa @ ACM Multimedia 2019: 2-6 - [i10]Ognjen Rudovic, Yuria Utsumi, Ricardo Guerrero, Kelly Peterson, Daniel Rueckert, Rosalind W. Picard:
Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes. CoRR abs/1904.09370 (2019) - [i9]Fangda Han, Ricardo Guerrero, Vladimir Pavlovic:
The Art of Food: Meal Image Synthesis from Ingredients. CoRR abs/1905.13149 (2019) - [i8]Jiatong Li, Ricardo Guerrero, Vladimir Pavlovic:
Deep Cooking: Predicting Relative Food Ingredient Amounts from Images. CoRR abs/1910.00100 (2019) - 2018
- [j8]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease. Medical Image Anal. 48: 117-130 (2018) - [j7]Chen Qin, Ricardo Guerrero, Christopher Bowles, Liang Chen, David Alexander Dickie, Maria del C. Valdés Hernández, Joanna M. Wardlaw, Daniel Rueckert:
A large margin algorithm for automated segmentation of white matter hyperintensity. Pattern Recognit. 77: 150-159 (2018) - [c15]Yuria Utsumi, Ognjen (Oggi) Rudovic, Kelly Peterson, Ricardo Guerrero, Rosalind W. Picard:
Personalized Gaussian Processes for Forecasting of Alzheimer's Disease Assessment Scale-Cognition Sub-Scale (ADAS-Cog13). EMBC 2018: 4007-4011 - [c14]Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. MICCAI (1) 2018: 277-285 - [i7]Yuria Utsumi, Kelly Peterson, Ognjen Rudovic, Ricardo Guerrero, Rosalind W. Picard:
Personalized Gaussian Processes for Forecasting of Alzheimer's Disease Assessment Scale-Cognition Sub-Scale (ADAS-Cog13). CoRR abs/1802.08561 (2018) - [i6]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease. CoRR abs/1806.01738 (2018) - [i5]Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. CoRR abs/1806.03228 (2018) - [i4]Christopher Bowles, Liang Chen, Ricardo Guerrero, Paul Bentley, Roger N. Gunn, Alexander Hammers, David Alexander Dickie, Maria del C. Valdés Hernández, Joanna M. Wardlaw, Daniel Rueckert:
GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks. CoRR abs/1810.10863 (2018) - 2017
- [j6]Ricardo Guerrero, Christian Ledig, Alexander Schmidt-Richberg, Daniel Rueckert:
Group-constrained manifold learning: Application to AD risk assessment. Pattern Recognit. 63: 570-582 (2017) - [j5]Tong Tong, Qinquan Gao, Ricardo Guerrero, Christian Ledig, Liang Chen, Daniel Rueckert:
A Novel Grading Biomarker for the Prediction of Conversion From Mild Cognitive Impairment to Alzheimer's Disease. IEEE Trans. Biomed. Eng. 64(1): 155-165 (2017) - [j4]Ozan Oktay, Wenjia Bai, Ricardo Guerrero, Martin Rajchl, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Mattias P. Heinrich, Ben Glocker, Daniel Rueckert:
Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images. IEEE Trans. Medical Imaging 36(1): 332-342 (2017) - [c13]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-Based Disease Prediction. MICCAI (3) 2017: 177-185 - [i3]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-based Disease Prediction. CoRR abs/1703.03020 (2017) - [i2]Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias P. Heinrich, Wenjia Bai, Jose Caballero, Ricardo Guerrero, Stuart A. Cook, Antonio de Marvao, Timothy Dawes, Declan P. O'Regan, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation. CoRR abs/1705.08302 (2017) - [i1]Kelly Peterson, Ognjen Rudovic, Ricardo Guerrero, Rosalind W. Picard:
Personalized Gaussian Processes for Future Prediction of Alzheimer's Disease Progression. CoRR abs/1712.00181 (2017) - 2016
- [j3]Ricardo Guerrero, Alexander Schmidt-Richberg, Christian Ledig, Tong Tong, Robin Wolz, Daniel Rueckert:
Instantiated mixed effects modeling of Alzheimer's disease markers. NeuroImage 142: 113-125 (2016) - [c12]Christopher Bowles, Chen Qin, Christian Ledig, Ricardo Guerrero, Roger N. Gunn, Alexander Hammers, Eleni Sakka, David Alexander Dickie, Maria del C. Valdés Hernández, Natalie A. Royle, Joanna M. Wardlaw, Hanneke Rhodius-Meester, Betty M. Tijms, Afina W. Lemstra, Wiesje M. van der Flier, Frederik Barkhof, Philip Scheltens, Daniel Rueckert:
Pseudo-healthy Image Synthesis for White Matter Lesion Segmentation. SASHIMI@MICCAI 2016: 87-96 - [c11]Chen Qin, Ricardo Guerrero Moreno, Christopher Bowles, Christian Ledig, Philip Scheltens, Frederik Barkhof, Hanneke Rhodius-Meester, Betty M. Tijms, Afina W. Lemstra, Wiesje M. van der Flier, Ben Glocker, Daniel Rueckert:
A Semi-supervised Large Margin Algorithm for White Matter Hyperintensity Segmentation. MLMI@MICCAI 2016: 104-112 - [c10]Ozan Oktay, Wenjia Bai, Matthew C. H. Lee, Ricardo Guerrero, Konstantinos Kamnitsas, Jose Caballero, Antonio de Marvao, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
Multi-input Cardiac Image Super-Resolution Using Convolutional Neural Networks. MICCAI (3) 2016: 246-254 - 2015
- [c9]Alexander Schmidt-Richberg, Ricardo Guerrero, Christian Ledig, Helena Molina-Abril, Alejandro F. Frangi, Daniel Rueckert:
Multi-stage Biomarker Models for Progression Estimation in Alzheimer's Disease. IPMI 2015: 387-398 - [c8]Ricardo Guerrero, Christian Ledig, Alexander Schmidt-Richberg, Daniel Rueckert:
Group-Constrained Laplacian Eigenmaps: Longitudinal AD Biomarker Learning. MLMI 2015: 178-185 - 2014
- [j2]Tong Tong, Robin Wolz, Qinquan Gao, Ricardo Guerrero, Joseph V. Hajnal, Daniel Rueckert:
Multiple instance learning for classification of dementia in brain MRI. Medical Image Anal. 18(5): 808-818 (2014) - [j1]Ricardo Guerrero, Robin Wolz, A. W. Rao, Daniel Rueckert:
Manifold population modeling as a neuro-imaging biomarker: Application to ADNI and ADNI-GO. NeuroImage 94: 275-286 (2014) - [c7]Ricardo Guerrero, Christian Ledig, Daniel Rueckert:
Manifold Alignment and Transfer Learning for Classification of Alzheimer's Disease. MLMI 2014: 77-84 - 2013
- [b1]Ricardo Guerrero Moreno:
Landmark localization, feature matching and biomarker discovery from magnetic resonance images. Imperial College London, UK, 2013 - [c6]Ricardo Guerrero, Daniel Rueckert:
Data-specific feature point descriptor matching using dictionary learning and graphical models. Medical Imaging: Image Processing 2013: 866921 - 2012
- [c5]Ricardo Guerrero, Luis Pizarro, Robin Wolz, Daniel Rueckert:
Landmark localisation in brain MR images using feature point descriptors based on 3D local self-similarities. ISBI 2012: 1535-1538 - [c4]Kai-Pin Tung, Wenzhe Shi, Luis Pizarro, Hiroto Tsujioka, Haiyan Wang, Ricardo Guerrero, Ranil De Silva, Philip Eddie Edwards, Daniel Rueckert:
Automatic detection of coronary stent struts in intravascular OCT imaging. Medical Imaging: Computer-Aided Diagnosis 2012: 83150K - [c3]Ricardo Guerrero, Claire R. Donoghue, Luis Pizarro, Daniel Rueckert:
Learning Correspondences in Knee MR Images from the Osteoarthritis Initiative. MLMI 2012: 218-225 - [c2]Stefan Pszczólkowski, Luis Pizarro, Ricardo Guerrero, Daniel Rueckert:
Nonrigid free-form registration using landmark-based statistical deformation models. Medical Imaging: Image Processing 2012: 831418 - 2011
- [c1]Ricardo Guerrero, Robin Wolz, Daniel Rueckert:
Laplacian Eigenmaps Manifold Learning for Landmark Localization in Brain MR Images. MICCAI (2) 2011: 566-573
Coauthor Index
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