
Farid García-LamontAutonomous University of Mexico State · Computer Engineering Department
Farid García-Lamont
Computer Science PhD
About
62
Publications
27,310
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2,418
Citations
Introduction
Pattern Recognition
Robotics
Artificial Intelligence Applications
Image processing
Additional affiliations
February 2005 - December 2016
Universidad Politécnica de Pachuca (UPP)
Position
- Profesor de Tiempo Completo tipo A
March 2011 - June 2012
Universidad Autónoma del Estado de Hidalgo (UAEH)
Position
- Profesor de Tiempo Completo tipo C
Publications
Publications (62)
La revista Tecnura es una publicación institucional de la Facultad Tecnológica de la Universidad Francisco José de Caldas, de carácter científico-tecnológico. Las áreas de interés están enfocadas a todos los campos de la ingeniería, como la electrónica, telecomunicaciones, electricidad, sistemas, industrial, mecánica, catastral, civil, ambiental, e...
In this paper we propose the classification of radiological patterns with the presence of tuberculosis in X-ray images, it was observed that two to six patterns (consolidation, fibrosis, opacity, opacity, pleural, nodules and cavitations) are present in the radiographs of the patients. It is important to mention that species specialists consider th...
Computer vision, for decades, has been involved in solving problems in everyday life, under the implementation of different computational methods, that have evolved over time. Feature extraction, along with other computer techniques, is considered a way to develop computer vision systems; currently, plays an important role, considered a complex tas...
The precise segmentation of white blood cells (WBCs) within blood smear images is a significant challenge with implications for both medical research and image processing. Of particular importance is the often neglected task of accurately segmenting WBC nuclei, an aspect that currently lacks dedicated methodologies. This paper introduces a straight...
Se utilizan técnicas de reconocimiento de patrones para identificar hojas sanas y cuatro enfermedades de la planta del café Coffeea arabica. Las enfermedades son la roya del café, el minador de la hoja, phoma quema y Cercospora coffeicola. Para lograrlo, se ocuparon diferentes técnicas de segmentación, entre ellas Otsu, PCA y método de frontera glo...
This paper presents a proposal for parameter extraction of a resistive load inverter circuit, with a Thin Film Transistor (TFT), using Artificial Neural Networks, Random Forest, Decision Trees and Support Vector Regression. Although analytical and optimization methods are usually used for this purpose, they have disadvantages such as the need for e...
This work presents a method based on supervised learning for the extraction of parameters in Indium Gallium Zinc Oxide Thin-Film Transistors with aluminium contacts, as an alternative regarding analytical and optimisation methods. The method consists of generating a set of I–V curves of the device of interest using Spice software. These curves are...
El objetivo del trabajo fue desarrollar un sistema basado en reglas que apoye la determinación de la salud estructural de edificios de varios niveles. Se utilizan técnicas de descripción de hardware mediante lógica programable empleando integración de entidades y diseño jerárquico con programación VHDL. El sistema se embebe en una FPGA que, mediant...
A test of independence is commonly used to determine differences (or associations) between samples in a nominal level measurement. Fisher’s exact test and Chi-square test are two of the most widely applied tests of independence used in the data analyses in different areas such as information technologies, biostatistics, psychology and health scienc...
Vessel segmentation is an important task to extract helpful information from retinal images that can help make a retinopathy diagnosis. A good segmentation perfectly represents the structure and obtains patterns that diagnose retinal diseases. Most of the current methods require many parameters, and the final quality of vessel segmentation depends...
In recent years, modern technology has been increasing, and this has grown a derivate in big challenges related to the network and application infrastructures. New devices have been providing more high functionalities to users than ever before; however, these devices depend on a high functionality of network in order to ensure a correct functioning...
Context:
The automobile industry has included active and passive safety. Active safety incorporates elements to avoid crashes and collisions. Some elements are ABS brakes and stabilization bars, among others. On the other hand, passive safety avoids or minimizes damage to the occupants in the event of an accident. Some passive safety features inclu...
Leukocyte (white blood cell, WBC) count is an essential factor that physicians use to diagnose infections and provide adequate treatment. Currently, WBC count is determined manually or semi-automatically, which often leads to miscounting. In this paper, we propose an automated method that uses a bioinspired segmentation mimicking the human percepti...
In this study, we present a nucleus segmentation proposal of white blood cells (WBCs) using chromatic features. It is human inspired on perception of color: a person locates the nucleus of the WBCs by the chromatic contrast between the nucleus and the other elements of the blood smear. To implement that, we segment the nucleus by selecting the pixe...
Looking for the improvement of the classification, we propose a hybrid algorithm to identify the corn plant and the weed. With the aim of improving the fertilization and herbicide application processes. An efficient process can avoid wasted fertilizers and decrease subsoil contamination. The purpose is to identify the corn plant to specify the fert...
In this work, the classification of current diseases in population that can be detected from X-ray radiographs is proposed; the diseases are COVID-19 that threaten life and health, also tuberculosis, which continues to be a global health problem, and viral and bacterial cases of pneumonia that present initial symptoms similar to COVID-19 and Tuberc...
In this paper, we present a new method for emotion recognition from facial expressions. The proposed algorithm concentrates on only two specific areas (eyes and mouth), reducing features and descriptors and focusing only on these areas. The algorithm extracts characteristics from these two regions of the face and, in a subsequent process, eliminate...
In recent years, the development of algorithms that assist in communicate with deaf people is an important challenge. The development of automatic systems to translate sign language is a current research topic. However, this involves several processes that range from video capture, pre-processing to identification or classification of the signal. T...
La presente invención describe un método y un sistema que lo comprende, para reconocer diferentes clases de frutas empleando visión artificial. Es aplicable en dispositivos para agilizar la venta de tales frutas en tiendas y supermercados. Las características visuales que se extraen de las frutas son la forma, la textura y la cromaticidad del color...
The last years in Mexico were reported thousands of missing people. Almost every day were found peoples dead in some place. The authorities open a folder investigation, but most times is not possible an identification effective of the person. In other hand, the familiars report the missing of any member to Public Ministry (PM) or to National Search...
The classification of leaves has gained popularity through the years, and a great variety of algorithms has been created to target these tasks, among those is the Deep Learning approach, which simplicity of learning from raw imputed data makes this task easy to target. However, not all methods are into the complex leaves classification task. In thi...
The extraction of characteristics, currently, plays an important role, likewise, it is considered a complex task, allowing to obtain essential descriptors of the processed images, differentiating particular characteristics between different classes, even when they share similarity with each other, guaranteeing the delivery of information not redund...
In recent years, an enormous amount of research has been carried out on support vector machines (SVMs) and their application in several fields of science. SVMs are one of the most powerful and robust classification and regression algorithms in multiple fields of application. The SVM has been playing a significant role in pattern recognition which i...
In this paper we introduce a method for color image segmentation by computing automatically the number of clusters the data, pixels, are divided into using fuzzy c-means. In several works the number of clusters is defined by the user. In other ones the number of clusters is computed by obtaining the number of dominant colors, which is determined wi...
Although the RGB space is accepted to represent colors, it is not adequate for color processing. In related works the colors are usually mapped to other color spaces more suitable for color processing, but it may imply an important computational load because of the non-linear operations involved to map the colors between spaces; nevertheless, it is...
Skin cancer is detected in skin lesions. The most common skin cancer is melanoma. Skin cancer is increasing in several parts of the world. Due to the above, it is important to work on the classification of melanomas, in order to support the possible detection of malignant melanomas that cause skin cancer. We use Convolutional Neural Networks (CNN)...
El libro se compone de nueve capítulos organizados es cuatro secciones. En la sección
se abordan los conceptos sobre la complejidad algorítmica y la metodología para calcularla; asimismo, se describen algunos programas implementados en lenguaje C con los que se ejemplifica la solución de problemas mediante algoritmos de distinta complejidad, los cu...
Most of the works addressing segmentation of color images use clustering-based methods; the drawback with such methods is that they require a priori knowledge of the amount of clusters, so the number of clusters is set depending on the nature of the scene so as not to lose color features of the scene. Other works that employ different unsupervised...
The histogram equalization (HE) is a technique developed for image contrast enhancement of grayscale images. For RGB (Red, Green, Blue) color images, the HE is usually applied in the color channels separately; due to correlation between the color channels, the chromaticity of colors is modified. In order to overcome this problem, the colors of the...
The automatic identification of plant leaves is a very important current topic of research in vision systems. Several researchers have tried to solve the problem of identification from plant leaves proposing various techniques. The proposed techniques in the literature have obtained excellent results on data sets where the leaves have dissimilar fe...
Image segmentation is an important stage for object recognition. Many methods have been proposed in the last few years for grayscale and color images. In this paper, we present a deep review of the state of the art on color image segmentation methods; through this paper, we explain the techniques based on edge detection, thresholding, histogram-thr...
Automatic plant identification has been an important issue in the last years. Most of the state-of-the-art methods for this purpose use leaf features to predict the species. Despite there are many methods to extract different leaf features, just few of them are focused on discriminating between simple and compound leaves. In this work, we introduce...
In most of classic plant identification methods a dichotomous or multi-access key is used to compare characteristics of leaves. Some questions about if the analyzed leaves are lobed, unlobed, simple or compound need to be answered to identify plants successfully. However, very little attention has been paid to make an automatic distinction of leave...
The development of vision systems for identifying plants by leaves is an important challenge which has numerous applications ranging from food, medicine, industry and environment. Recently, several techniques have been proposed in the literature in order to identify plants in various fields of application. However, current techniques are restricted...
Over the last years, Support Vector Machines (SVMs) have become a successful approach in classification problems. However, the performance of SVMs is affected harshly by skewed data sets. An SVM learns a biased model that affects the performance of the classifier. Furthermore, SVMs are typically unsuccessful on data sets where the imbalanced ratio...
The development of vision systems capable to extracting discriminative features that enhance the generalization power of a classifier is still a very challenging problem. In this paper, is presented a methodology to improve the classification performance of Mexican Sign Language (MSL). The proposed method explores some frames in video sequences for...
The performance of classification methods is notably damaged with imbalanced data sets. Although some studies to analyze this behavior have realized before, most of the conclusions obtained from experiments correspond to synthetic data sets. In this paper, we study the relationship between the performance of five classification methods and neighbor...
Fuzzy C-means (FCM) is one of the most often techniques employed for color image segmentation; the drawback with this technique is the number of clusters the data, pixels’ colors, is grouped must be defined a priori. In this paper we present an approach to compute the number of clusters automatically. A competitive neural network (CNN) and a self-o...
Usually, the segmentation of color images is performed using cluster-based methods and the RGB space to represent the colors. The drawback with these methods is the a priori knowledge of the number of groups, or colors, in the image; besides, the RGB space is sensitive to the intensity of the colors. Humans can identify different sections within a...
In this paper we present an approach for fruit recognition using artificial vision, towards to employ it as an application for supermarkets. The fruit's visual features extracted are shape, texture and ‑we focus on‑ the extraction of the color chromaticity. From the few related works on fruit recognition, the color extraction is performed in the RG...
Support Vector Machines (SVM) have shown excellent generalization power in classification problems. However, on skewed data-sets, SVM learns a biased model that affects the classifier performance, which is severely damaged when the unbalanced ratio is very large. In this paper, a new external balancing method for applying SVM on skewed data sets is...
Classification methods usually exhibit a poor performance when they are applied on imbalanced data sets. In order to overcome this problem, some algorithms have been proposed in the last decade. Most of them generate synthetic instances in order to balance data sets, regardless the classification algorithm. These methods work reasonably well in mos...
In this paper we present a comparison between three color characterizations methods applied for fruit recognition, two of them are selected from two related works and the third is the authors’ proposal; in the three works, color is represented in the RGB space. The related works characterize the colors considering their intensity data; but employin...
This paper focuses on the representation of magnetic resonances of different parts of the human body, such as knees, spinal column, arms, elbows, etc., using ontologies. First, it maps the resonance images in a multimedia database. Then, automatically, using the SIFT pattern recognition algorithm, descriptors of the images stored in the database ar...
Over the past few years, has been shown that generalization power of Support Vector Machines (SVM) falls dramatically on imbalanced data-sets. In this paper, we propose a new method to improve accuracy of SVM on imbalanced data-sets. To get this outcome, firstly, we used undersampling and SVM to obtain the initial SVs and a sketch of the hyperplane...
In this paper we describe a machine vision approach to recognize the denomination classes of the Mexican paper currency by extracting their color features. A banknote’s color is characterized by summing all the color vectors of the image’s pixels to obtain a resultant vector, the banknote’s denomination is classified by knowing the orientation of t...
The method involves controlling speed and browsing path of a vehicle on land with different textures and irregularities by a computer. The path is defined and the speed control is updated so that the vehicle moves with maximum speed and security.
Vertical partitioning has been widely employed in relational databases to improve query response time. Nevertheless, most of the vertical partitioning approaches are static, based on the way applications access the database attributes. A vertical fragmentation scheme (VPS) is created according to a previously known set of queries. If this set under...
In pattern recognition and data mining a data set is named skewed or imbalanced if it contains a large number of objects of certain type and a very small number of objects of the opposite type. The imbalance in data sets represents a challenging problem for most classification methods, this is because the generalization power achieved for classic c...
In recent years, vertical partitioning techniques have been employed in multimedia databases to achieve efficient retrieval of multimedia objects. These techniques are static because the input to the partitioning process, which includes queries accessing database and their frequency as well as the database schema, is obtained from an earlier analys...
In this paper we present a new algorithm to speed up the training time of Support Vector Machines (SVM). SVM has some important properties like solid mathematical background and a better generalization capability than other machines like for example neural networks. On the other hand, the major drawback of SVM occurs in its training phase, which is...
This paper addresses the velocity control of wheeled vehicles regarding the terrain features, beyond detection and avoidance
of the obstacles as most current works do. Terrain appearance average is used to enable the wheeled vehicle to adapt velocity
such that, as speedy as possible, it safely navigates. The vehicle velocity adaptation imitates the...
In this paper is shown that the Appearance-Based modeling is the best pattern recognition method for supporting the velocity
updating of wheeled-robots navigation. Although Appearance-Based recognition algorithms have lower accuracy than the ones
for detailed pattern recognition, they successfully classify terrain textures by regarding the average...
For navigation on outdoor surfaces, usually having different kind of roughness and soft irregularities, this paper proposal is that a wheeled robot combines the gradient method for path planning, alongside it adjusts velocity based on a multi-layer fuzzy neural network; the network integrates information about the roughness and the soft slopes of t...