9 citations · 33 across the 14 of their papers we have counts for
14 papers
FAU-Net: An Attention U-Net Extension with Feature Pyramid Attention for Prostate Cancer Segmentation
Pablo Cesar Quihui-Rubio, Daniel Flores-Araiza, Miguel Gonzalez-Mendoza +2
This contribution presents a deep learning method for the segmentation of prostate zones in MRI images based on U-Net using additive and feature pyramid attention modules, which ca…
Assessing the performance of deep learning-based models for prostate cancer segmentation using uncertainty scores
Pablo Cesar Quihui-Rubio, Daniel Flores-Araiza, Gilberto Ochoa-Ruiz +2
This study focuses on comparing deep learning methods for the segmentation and quantification of uncertainty in prostate segmentation from MRI images. The aim is to improve the wor…
Isolated Sign Language Recognition based on Tree Structure Skeleton Images
David Laines, Gissella Bejarano, Miguel Gonzalez-Mendoza +1
Sign Language Recognition (SLR) systems aim to be embedded in video stream platforms to recognize the sign performed in front of a camera. SLR research has taken advantage of recen…
Deep Prototypical-Parts Ease Morphological Kidney Stone Identification and are Competitively Robust to Photometric Perturbations
Daniel Flores-Araiza, Francisco Lopez-Tiro, Jonathan El-Beze +4
Identifying the type of kidney stones can allow urologists to determine their cause of formation, improving the prescription of appropriate treatments to diminish future relapses.…
Improved Kidney Stone Recognition Through Attention and Multi-View Feature Fusion Strategies
Elias Villalvazo-Avila, Francisco Lopez-Tiro, Jonathan El-Beze +4
This contribution presents a deep learning method for the extraction and fusion of information relating to kidney stone fragments acquired from different viewpoints of the endoscop…
Comparison of automatic prostate zones segmentation models in MRI images using U-net-like architectures
Pablo Cesar Quihui-Rubio, Gilberto Ochoa-Ruiz, Miguel Gonzalez-Mendoza +2
Prostate cancer is the second-most frequently diagnosed cancer and the sixth leading cause of cancer death in males worldwide. The main problem that specialists face during the dia…
Computer Vision-based Characterization of Large-scale Jet Flames using a Synthetic Infrared Image Generation Approach
Carmina Pérez-Guerrero, Jorge Francisco Ciprián-Sánchez, Adriana Palacios +5
Among the different kinds of fire accidents that can occur during industrial activities that involve hazardous materials, jet fires are one of the lesser-known types. This is becau…
Impact of loss function in Deep Learning methods for accurate retinal vessel segmentation
Daniela Herrera, Gilberto Ochoa-Ruiz, Miguel Gonzalez-Mendoza +1
The retinal vessel network studied through fundus images contributes to the diagnosis of multiple diseases not only found in the eye. The segmentation of this system may help the s…
Experimental Large-Scale Jet Flames' Geometrical Features Extraction for Risk Management Using Infrared Images and Deep Learning Segmentation Methods
Carmina Pérez-Guerrero, Adriana Palacios, Gilberto Ochoa-Ruiz +4
Jet fires are relatively small and have the least severe effects among the diverse fire accidents that can occur in industrial plants; however, they are usually involved in a proce…
On the in vivo recognition of kidney stones using machine learning
Francisco Lopez-Tiro, Vincent Estrade, Jacques Hubert +4
Determining the type of kidney stones allows urologists to prescribe a treatment to avoid recurrence of renal lithiasis. An automated in-vivo image-based classification method woul…
TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video
Mario Alberto Duran-Vega, Miguel Gonzalez-Mendoza, Leonardo Chang +1
Timely handgun detection is a crucial problem to improve public safety; nevertheless, the effectiveness of many surveillance systems still depends of finite human attention. Much o…
Comparing Machine Learning based Segmentation Models on Jet Fire Radiation Zones
Carmina Pérez-Guerrero, Adriana Palacios, Gilberto Ochoa-Ruiz +3
Risk assessment is relevant in any workplace, however there is a degree of unpredictability when dealing with flammable or hazardous materials so that detection of fire accidents b…
A Bop and Beyond: A Second Order Optimizer for Binarized Neural Networks
Cuauhtemoc Daniel Suarez-Ramirez, Miguel Gonzalez-Mendoza, Leonardo Chang-Fernandez +2
The optimization of Binary Neural Networks (BNNs) relies on approximating the real-valued weights with their binarized representations. Current techniques for weight-updating use t…
FIRe-GAN: A novel Deep Learning-based infrared-visible fusion method for wildfire imagery
J. F. Ciprián-Sánchez, G. Ochoa-Ruiz, M. Gonzalez-Mendoza +1
Early wildfire detection is of paramount importance to avoid as much damage as possible to the environment, properties, and lives. Deep Learning (DL) models that can leverage both…