activity
20182025
most citedContextualize, Show and Tell: A Neural Visual Storyteller

29 citations · 67 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2025

MetaChest: Generalized few-shot learning of pathologies from chest X-rays

Berenice Montalvo-Lezama, Gibran Fuentes-Pineda

The limited availability of annotated data presents a major challenge for applying deep learning methods to medical image analysis. Few-shot learning methods aim to recognize new c…

cs.CV2024★ 2 cited

Efficient generative adversarial networks using linear additive-attention Transformers

Emilio Morales-Juarez, Gibran Fuentes-Pineda

Although deep generative models such as Diffusion Models (DMs) and Generative Adversarial Networks (GANs) achieve remarkable image generation performance, they often rely on comput…

cs.CV2022

Improving Transfer Learning with a Dual Image and Video Transformer for Multi-label Movie Trailer Genre Classification

Ricardo Montalvo-Lezama, Berenice Montalvo-Lezama, Gibran Fuentes-Pineda

In this paper, we study the transferability of ImageNet spatial and Kinetics spatio-temporal representations to multi-label Movie Trailer Genre Classification (MTGC). In particular…

cs.LG2021★ 2 cited

Risk markers by sex for in-hospital mortality in patients with acute coronary syndrome: a machine learning approach

Blanca Vazquez, Gibran Fuentes-Pineda, Fabian Garcia +2

Background: Several studies have highlighted the importance of considering sex differences in the diagnosis and treatment of Acute Coronary Syndrome (ACS). However, the identificat…

eess.AS2020★ 14 cited

Lightweight Speaker Verification for Online Identification of New Speakers with Short Segments

Ivette Velez, Caleb Rascon, Gibran Fuentes-Pineda

Verifying if two audio segments belong to the same speaker has been recently put forward as a flexible way to carry out speaker identification, since it does not require to be re-t…

cs.LG2019★ 2 cited

A few filters are enough: Convolutional Neural Network for P300 Detection

Alicia Montserrat Alvarado-Gonzalez, Gibran Fuentes-Pineda, Jorge Cervantes-Ojeda

Over the past decade, convolutional neural networks (CNNs) have become the driving force of an ever-increasing set of applications, achieving state-of-the-art performance. Most of…

eess.AS2018★ 5 cited

One-Shot Speaker Identification for a Service Robot using a CNN-based Generic Verifier

Ivette Vélez, Caleb Rascon, Gibrán Fuentes-Pineda

In service robotics, there is an interest to identify the user by voice alone. However, in application scenarios where a service robot acts as a waiter or a store clerk, new users…

cs.CL2018★ 13 cited

Topic Discovery in Massive Text Corpora Based on Min-Hashing

Gibran Fuentes-Pineda, Ivan Vladimir Meza-Ruiz

The task of discovering topics in text corpora has been dominated by Latent Dirichlet Allocation and other Topic Models for over a decade. In order to apply these approaches to mas…

cs.CL2018★ 29 cited

Contextualize, Show and Tell: A Neural Visual Storyteller

Diana Gonzalez-Rico, Gibran Fuentes-Pineda

We present a neural model for generating short stories from image sequences, which extends the image description model by Vinyals et al. (Vinyals et al., 2015). This extension reli…