8 Result(s)
within
Sebastián Salazar-Colores
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Article
Image dehazing using morphological opening, dilation and Gaussian filtering
Image pre-processing is a critical stage in computer vision systems, with greater relevance when the input images are captured in outdoor environments because the pictures could contain low contrast and modifi...
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Chapter and Conference Paper
A Fast and Robust Deep Learning Approach for Hand Object Gras** Confirmation
One of the most important skills for service robots is object manipulation, which is still a challenging task. Since object manipulation is a hard task, it is relevant to know if an object was successfully gra...
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Article
Open AccessEfficient single image dehazing by modifying the dark channel prior
Outdoor images can be degraded due to the particles in the air that absorb and scatter light. The produced degradation generates contrast attenuation, blurring, and distortion in pixels, resulting in low visib...
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Chapter and Conference Paper
A Quaternion Deterministic Monogenic CNN Layer for Contrast Invariance
Deep learning (DL) is attracting considerable interest as it currently achieves remarkable performance in many branches of science and technology. However, current DL cannot guarantee capabilities of the mamma...
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Chapter and Conference Paper
Adversarial Attack Versus a Bio-Inspired Defensive Method for Image Classification
Adversarial attacks are designed to disrupt the information supplied to Artificial Intelligence (AI) models causing a failure in their intended purpose. Despite late state-of-art performance on computer vision...
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Chapter and Conference Paper
A Novel Method Based on Gunnar Farneback Method, Mathematical Morphology, and Artificial Vision for Flow Analysis in Electrochemical Reactors
Parallel flat plate electrochemical reactors are versatile devices that are used in a wide range of applications, including hydrogen production, organic compound synthesis, chlorine generation, wastewater trea...
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Chapter and Conference Paper
Classification of COVID-19 Mortality Risk: A Neural Network-Based Approach Using Mexican Healthcare Sector Data
This study focuses on the use of neural networks and clinical data collected by the Mexican Ministry of Health to classify the risk of death from COVID-19. A multi-layer perceptron neural network model was de...
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Chapter
Dsmk-DcSeg-Lap, a Generative Adversarial Network Guided by Dark-Chanel and Segmentation to Smoke Removal in Laparoscopic Images
In this chapter, a computational approach is proposed to address the challenge of degraded visibility caused by smoke during laparoscopic surgery. The visualization of organs and tissues is hindered by the pre...
