7 papers
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…
Efficient generative adversarial networks using linear additive-attention Transformers
Emilio Morales-Juarez, Gibran Fuentes-Pineda
Although the capacity of deep generative models for image generation, such as Diffusion Models (DMs) and Generative Adversarial Networks (GANs), has dramatically improved in recent…
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…
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…
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…
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…