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detection process » selection process (Expander búsqueda), election process (Expander búsqueda), protection process (Expander búsqueda)
based detection » case detection (Expander búsqueda), rapid detection (Expander búsqueda), acid detection (Expander búsqueda)
detection process » selection process (Expander búsqueda), election process (Expander búsqueda), protection process (Expander búsqueda)
based detection » case detection (Expander búsqueda), rapid detection (Expander búsqueda), acid detection (Expander búsqueda)
1
artículo
Publicado 2020
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This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to serve as fiducials. For the detection of those marks, the use of two methods was evaluated: One based on the application of thresholds to the color components, and the other based on the use of a fuzzy rule machine. The experimentation shows that both approaches provide similar results. Some morphological operations are then applied in order to detect the scalpel region. The algorithm was successfully tested in several cases, and some examples of the results are presented and analyzed. © 2020 IEEE.
2
artículo
Publicado 2024
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This work proposes an electronic equipment which determines the marbling grade in beef rib eye according to the American grading scale using digital image processing and machine learning, achieving an 88.89 % coincidence level with grading done by beef specialists. Existing solutions which use image processing usually require calibration methods due to working in non-controlled environments. Furthermore, they only acquire the fat distribution from the longissimus dorsi muscle with an approximate accuracy of 80 %, without referring the distribution to any quality standard. In this work, meat samples are placed in a food grade stainless-steel enclosure with a touch screen and a digital RGB camera. The device acquires an image of the rib eye, which is then analyzed using techniques such as adaptive histogram analysis based on the HSV color model, histogram peaks detection for grayscale thre...
3
artículo
Publicado 2021
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For social robots, knowledge regarding human emotional states is an essential part of adapting their behavior or associating emotions to other entities. Robots gather the information from which emotion detection is processed via different media, such as text, speech, images, or videos. The multimedia content is then properly processed to recognize emotions/sentiments, for example, by analyzing faces and postures in images/videos based on machine learning techniques or by converting speech into text to perform emotion detection with natural language processing (NLP) techniques. Keeping this information in semantic repositories offers a wide range of possibilities for implementing smart applications. We propose a framework to allow social robots to detect emotions and to store this information in a semantic repository, based on EMONTO (an EMotion ONTOlogy), and in the first figure or table...
4
artículo
Publicado 2015
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Cervical cancer is one of the main causes of death by disease worldwide. In Peru, it holds the first place in frequency and represents 8% of deaths caused by sickness. To detect the disease in the early stages, one of the most used screening tests is the cervix Papanicolaou test. Currently, digital images are increasingly being used to improve Pap test efficiency. This work develops an algorithm based on adaptive thresholds, which will be used in Pap smear assisted quality control software. The first stage of the method is a pre-processing step, in which noise and background removal is done. Next, a block is segmented for each one of the points selected as not background, and a local threshold per block is calculated to search for cell nuclei. If a nucleus is detected, an artifact rejection follows, where only cell nuclei and inflammatory cells are left for the doctors to interpret. The ...
5
tesis de maestría
Publicado 2017
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Tuberculosis is a leading killing disease worldwide with more than 9 million people a ected per year. Current diagnostic methods exhibit several disadvantages; one of the most promising alternatives to overcome this is the development of nanostructured diagnostic systems which are able to detect molecules associated with certain diseases. Graphene since its discovery has been the focus for the development of these sensing elements due to its excellent electronic properties. In this work, a graphene-based eld e ect transistor (FET) has been developed for tuberculosis DNA detection, in order to set the basis for a diagnostic method that overcomes current limitations. The sensing elements composed of graphene monolayers were manufactured in the stages of annealing of the substrate, addition of the linker and functionalization with the addition of a probe DNA for tuberculosis detection. Addi...
6
tesis de maestría
Publicado 2017
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Tuberculosis is a leading killing disease worldwide with more than 9 million people a ected per year. Current diagnostic methods exhibit several disadvantages; one of the most promising alternatives to overcome this is the development of nanostructured diagnostic systems which are able to detect molecules associated with certain diseases. Graphene since its discovery has been the focus for the development of these sensing elements due to its excellent electronic properties. In this work, a graphene-based eld e ect transistor (FET) has been developed for tuberculosis DNA detection, in order to set the basis for a diagnostic method that overcomes current limitations. The sensing elements composed of graphene monolayers were manufactured in the stages of annealing of the substrate, addition of the linker and functionalization with the addition of a probe DNA for tuberculosis detection. Addi...
7
objeto de conferencia
Publicado 2017
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The present study proposes a method of automatic detection of tuberculosis (TB) bacilli from digital images of Ziehl Neelsen sputum smear baciloscopy. The method is based on an algorithm that aims to automate the interpretation of optical microscopic images of sputum smears. According to the World Health Organization (WHO), a specialist can not analyze and process more than 20 samples per day (in order to not affect the analysis sensitivity and commit errors in diagnosis). Therefore, an automated tool as the proposed here, is an important contribution to the current efforts to fight tuberculosis. The algorithm is based on geometric eccentricity of ellipses and improvement of RGB component tones. Correspondence functions adjusted to sample preparation conditions were applied in order to improve the RGB primary component tones of the image. This allows to obtain an adequate segmentation of...
8
artículo
Attention deficit hyperactivity disorder (ADHD) represents a medical condition characterized by the presence of inattention, hyperactivity, and impulsivity, which affects the academic development of students globally. In Peru, it affects a proportion of the pediatric population ranging from 2% to 12%, with a prevalence of 12.1% in South Lima, particularly in public schools. This research presents an online application with machine learning to improve the detection of ADHD in elementary school children. Several machine learning algorithms were reviewed and Random Forest was selected as the best-performing model with an accuracy of 96.08%. The model uses 27 selected variables, optimizing data collection and training. The child answers the questionnaire within the app and psychologists can access the app to visualize the results, aiding in the early detection of ADHD. The experiment involve...
9
artículo
Objective: To determine gender based violence prevalence in reproductive health services users and to motivate heath protessionals to detect these cases using an easy questionnaire. DESIGN: Survey type transversal descriptive study. Material and Methods: Two hundred and ninety-eight reproductive health services users at three Lima hospitals, between May and July 2002. Study searched for history of psychological, physical and sexual violence as well as sexual abuse during childhood. Time of violence and the relation between aggressor and the victim were identified. Data was processed with EpiInfo at the Campinas-Brasil University and Inppares. Results: Sixty-one per cent of the women interviewed accepted being victims of some type of violence, including emotional violence 54%, physical violence 32,2%, sexual violence 21, 1 % and childhood sexual violence 19, 1 %. Main aggressors were de c...
10
artículo
Objective: To determine gender based violence prevalence in reproductive health services users and to motivate heath protessionals to detect these cases using an easy questionnaire. DESIGN: Survey type transversal descriptive study. Material and Methods: Two hundred and ninety-eight reproductive health services users at three Lima hospitals, between May and July 2002. Study searched for history of psychological, physical and sexual violence as well as sexual abuse during childhood. Time of violence and the relation between aggressor and the victim were identified. Data was processed with EpiInfo at the Campinas-Brasil University and Inppares. Results: Sixty-one per cent of the women interviewed accepted being victims of some type of violence, including emotional violence 54%, physical violence 32,2%, sexual violence 21, 1 % and childhood sexual violence 19, 1 %. Main aggressors were de c...
11
objeto de conferencia
The diagnostic process of respiratory diseases requires experience and skills to assess the different pathologies that patients may develop. Unfortunately, the lack of qualified radiologists is a global problem that limits respiratory diseases diagnosis. Therefore, it will be useful to have a tool that minimizes errors and workload, improves efficiency, and speeds up the diagnostic process in order to provide a better healthcare service to the community. This research proposes a methodology to detect pathologies by using deep learning architectures. The present proposal is divided into three types of experiments. The first one evaluates the performance of feature descriptors such as SIFT, SURF, and ORB in medical images with machine learning models as an introduction to the last experiment. The second one evaluates the performance of deep learning architectures such as ResNet50, Alexnet,...
12
artículo
Publicado 2020
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ABSTRACT Diabetic retinopathy is a leading cause of vision loss in developed countries. Regular diabetic retinal eye screenings are needed to detect early signs of retinopathy, so that appropriate treatments can be rendered to prevent blindness. Digital imaging is becoming available as a means of screening for diabetic retinopathy. However, with the large number of patients undergoing screenings, medical professionals require a tremendous amount of time and effort in order to analyse and diagnose the fundus photo-graphs, the treatment is done on a digital image, to obtain results as complex as recognizing patterns or as simple as enhancing con-tours, may involve filtering, transformations of gray levels, based on histogram processing, describing, between others. The design of a teaching tool to facilitate image processing, allowing access to each of the steps involved in the system, ensu...
13
artículo
Publicado 2021
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Digital Image processing has been a research area of interest in the last decades, standing out for its applications in the analysis of diagnostic images and astronomical images. In this paper, we perform an overview of edge detection methods through finite-difference to present edge detection as a problem-based learning strategy for numerical differentiation, in order to improve the students’ skills in modeling and algorithmic thinking in numerical analysis courses. In addition, we present image restoration through finite-difference as a problem involving partial differential equations and software tools.
14
artículo
Publicado 2019
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Edge detection is a digital image processing tool. It determines points in a digital image where light intensity suddenly changes. This process applies to a digital image which assumes some degree of uncertainty in the location and intensity of the pixel in the real image. In this work, we propose an edge detection model which consists in capturing this uncertainty in terms of interval images. Then we apply interval-valued fuzzy morphology to calculate the interval-valued erosion and dilation. Finally, we compute the convex combinations of the upper and lower bounds of the interval-valued erosion and dilation image, to obtain a morphological erosion and dilation respectively, and thus an edge image.
15
artículo
Publicado 2019
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Edge detection is a digital image processing tool. It determines points in a digital image where light intensity suddenly changes. This process applies to a digital image which assumes some degree of uncertainty in the location and intensity of the pixel in the real image. In this work, we propose an edge detection model which consists in capturing this uncertainty in terms of interval images. Then we apply interval-valued fuzzy morphology to calculate the interval-valued erosion and dilation. Finally, we compute the convex combinations of the upper and lower bounds of the interval-valued erosion and dilation image, to obtain a morphological erosion and dilation respectively, and thus an edge image.
16
artículo
Publicado 1999
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OBJETIVES: To evaluate the sensitivity and specifity of a nitrocellulose membrane-based immunoassay for dengue IgM, with respect to capture enzyme immunoassay, for the diagnosis of dengue virus infection. METHODS: 101 serum samples were processed and divided into 2 groups: 53 from dengue serotype 1 (DEN1) infected patients, and 48 from healthy subjects. Both groups were tested with a nitrocellulose membrane-based IgM capture enzyme immunoassay (NMB-EIA) and also with an ELISA as referential pattern. RESULTS: NMB-EIA testing detected IgM anti-DEN1 in 94,34% of samples from infected patients, and in 14,58% of control samples, whereas ELISA fails to report false positive or false negative results. CONCLUSION: NMB-EIA appears to be a good alternative for dengue infection diagnosis.
17
artículo
Publicado 2022
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This work proposes a computational algorithm which monitors voice/audio signals demodulated from a FM receptor and detects whether they are intelligible or not. Data analytics applications which require the continuous storage of radio broadcasted audio signals into a database can benefit from this algorithm. In many instances, the broadcasted signals arrive at the receptor with heavy distortion and noise content, limiting the data analysis due to poor data quality. Moreover, radio spectrum supervisory agencies can also take advantage of this work, since broadcasted signals can be efficiently and continuously monitored to detect whether a broadcaster has stopped transmitting for an extended period. First, the algorithm processes the demodulated signals block by block, extracting its MFCC coefficients, spectral centroid, the arithmetic and geometric means of the frequency magnitude spectru...
18
artículo
Publicado 2025
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Dental cavities represent a significant global health challenge, particularly in low-and middle-income countries, where early detection and diagnosis can substantially improve clinical outcomes. This study presents the development of a mobile application that utilizes YOLOv7 to detect early carious lesions on intraoral images, intending to provide dental professionals with a tool for timely diagnosis and intervention. The research was carried out in three key phases: analysis of YOLOv7, system development, and validation. The application was trained in a real clinical environment in Peru in collaboration with two independent dentists and their patients in two private clinics. Intraoral images were collected and processed from 40 participants, ensuring complete adherence to the ethical and privacy standards required for clinical studies. The experimental results demonstrated that the appl...
19
artículo
Publicado 2020
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Botnets are some of the most recurrent cyber-threats, which take advantage of the wide heterogeneity of endpoint devices at the Edge of the emerging communication environments for enabling the malicious enforcement of fraud and other adversarial tactics, including malware, data leaks or denial of service. There have been significant research advances in the development of accurate botnet detection methods underpinned on supervised analysis but assessing the accuracy and performance of such detection methods requires a clear evaluation model in the pursuit of enforcing proper defensive strategies. In order to contribute to the mitigation of botnets, this paper introduces a novel evaluation scheme grounded on supervised machine learning algorithms that enable the detection and discrimination of different botnets families on real operational environments. The proposal relies on observing, u...
20
tesis de grado
Publicado 2020
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Botnets are some of the most recurrent cyber-threats, which take advantage of the wide heterogeneity of endpoint devices at the Edge of the emerging communication environments for enabling the malicious enforcement of fraud and other adversarial tactics, including malware, data leaks or denial of service. There have been significant research advances in the development of accurate botnet detection methods underpinned on supervised analysis but assessing the accuracy and performance of such detection methods requires a clear evaluation model in the pursuit of enforcing proper defensive strategies. In order to contribute to the mitigation of botnets, this paper introduces a novel evaluation scheme grounded on supervised machine learning algorithms that enable the detection and discrimination of different botnets families on real operational environments. The proposal relies on observing, u...
