Ricardo Guerrero | DeepAI

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Featured Co-authors

Daniel Rueckert
199 publications
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85 publications
Georgios Tzimiropoulos
64 publications
Vladimir Pavlovic
52 publications
Bernhard Kainz
46 publications
Adrian Bulat
39 publications
Wenjia Bai
37 publications
Konstantinos Kamnitsas
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Brais Martinez
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∙ 12/02/2022

D2DF2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation

Weakly-supervised object detection (WSOD) models attempt to leverage ima...

16 Yuting Wang, et al. ∙

∙ 11/02/2022

A digital business ecosystem maturity model for personal service firms

Personal services can be found in sectors such as education, retail, hos...

0 Ricardo Guerrero, et al. ∙

∙ 10/10/2022

FS-DETR: Few-Shot DEtection TRansformer with prompting and without re-training

This paper is on Few-Shot Object Detection (FSOD), where given a few tem...

14 Adrian Bulat, et al. ∙

∙ 04/10/2022

SOS! Self-supervised Learning Over Sets Of Handled Objects In Egocentric Action Recognition

Learning an egocentric action recognition model from video data is chall...

14 Victor Escorcia, et al. ∙

∙ 10/22/2021

Multi-attribute Pizza Generator: Cross-domain Attribute Control with Conditional StyleGAN

Multi-attribute conditional image generation is a challenging problem in...

6 Fangda Han, et al. ∙

∙ 02/04/2021

CHEF: Cross-modal Hierarchical Embeddings for Food Domain Retrieval

Despite the abundance of multi-modal data, such as image-text pairs, the...

7 Hai X. Pham, et al. ∙

∙ 12/04/2020

MPG: A Multi-ingredient Pizza Image Generator with Conditional StyleGANs

Multilabel conditional image generation is a challenging problem in comp...

11 Fangda Han, et al. ∙

∙ 12/02/2020

Cross-modal Retrieval and Synthesis (X-MRS): Closing the modality gap in shared subspace

Computational food analysis (CFA), a broad set of methods that attempt t...

0 Ricardo Guerrero, et al. ∙

∙ 12/01/2020

Learning Disentangled Latent Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach

We deal with the problem of learning the underlying disentangled latent ...

0 Minyoung Kim, et al. ∙

∙ 10/17/2020

Picture-to-Amount (PITA): Predicting Relative Ingredient Amounts from Food Images

Increased awareness of the impact of food consumption on health and life...

1 Jiatong Li, et al. ∙

∙ 02/25/2020

CookGAN: Meal Image Synthesis from Ingredients

In this work we propose a new computational framework, based on generati...

35 Fangda Han, et al. ∙

∙ 09/26/2019

Deep Cooking: Predicting Relative Food Ingredient Amounts from Images

In this paper, we study the novel problem of not only predicting ingredi...

34 Jiatong Li, et al. ∙

∙ 05/09/2019

The Art of Food: Meal Image Synthesis from Ingredients

In this work we propose a new computational framework, based on generati...

1 Fangda Han, et al. ∙

∙ 04/19/2019

Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes

We introduce a novel personalized Gaussian Process Experts (pGPE) model ...

8 Ognjen Rudovic, et al. ∙

∙ 10/25/2018

GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

One of the biggest issues facing the use of machine learning in medical ...

4 Christopher Bowles, et al. ∙

∙ 06/08/2018

Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents

We propose a fully automatic method to find standardized view planes in ...

10 Amir Alansary, et al. ∙

∙ 06/05/2018

Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease

Graphs are widely used as a natural framework that captures interactions...

0 Sarah Parisot, et al. ∙

∙ 02/22/2018

Personalized Gaussian Processes for Forecasting of Alzheimer's Disease Assessment Scale-Cognition Sub-Scale (ADAS-Cog13)

In this paper, we introduce the use of a personalized Gaussian Process m...

0 Yuria Utsumi, et al. ∙

∙ 12/01/2017

Personalized Gaussian Processes for Future Prediction of Alzheimer's Disease Progression

In this paper, we introduce the use of a personalized Gaussian Process m...

0 Kelly Peterson, et al. ∙

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