Tópicos Sugeridos dentro de su búsqueda.
Tópicos Sugeridos dentro de su búsqueda.
Buscar alternativas:
classification using » classification _ (Expander búsqueda)
a classification » _ classification (Expander búsqueda), abc classification (Expander búsqueda), image classification (Expander búsqueda)
classification using » classification _ (Expander búsqueda)
a classification » _ classification (Expander búsqueda), abc classification (Expander búsqueda), image classification (Expander búsqueda)
1
artículo
Publicado 2021
Enlace
Enlace
We want to thank the Image Processing Research Laboratory. (INTI-Lab) and the Universidad de Ciencias y Humanidades. (UCH) for their support in this research, the National Fund for. Scientific, Technological and Technological Innovation (FONDECYT), according to the research: ?SAMAYCOV: ?Desarrollo de un dispositivo electr?nico port?til a bajo costo para evaluar riesgo de neumon?a basado en sonido pulmonar anormal en pacientes con sospecha de COVID-19 en zonas vulnerables?. CONVENIO 054-2020-FONDECYT?; for the financing of this research and the Electronics Laboratory of the UCH for assigning us their facilities and being able to carry out the respective tests.
2
artículo
Publicado 2023
Enlace
Enlace
The present project consists of developing a Natural Language Processing model to classify news using a set of data or DataSets already evaluated. The main objective is to create a system that can automatically identify and assign news to one of the predefined categories: business, entertainment, politics, sports or technology. This involves data preprocessing, feature extraction, training a machinelearning model and then evaluating its performance using metrics such as "accuracy", "recall 2" F1 - score". This will allow to determine how well the model can predict the correct category for a new or unlabeled news item. If the performance of the model is satisfactory, it can be used to classify unlabeled news in real time. In summary, it seeks to provide an efficient and accurate solution for organizing and labeling the informative content of a news item with the help of Artificial Intelli...
3
artículo
Publicado 2024
Enlace
Enlace
This project focuses on developing an NLP-based text analysis tool to evaluate Android app user feedback, specifically collected from F-Droid. The lack of an automated solution to analyze and understand these opinions, classifying them into specific topics, motivates research. The goal is to provide developers, users, and data analysts with a detailed view of user preferences and perceptions. Using data sets in English between 2014 and 2017, the proposal is implemented in Python with the Pandas library. The BERT model is used for classification, with a specific focus on the comparison of different models. The graphical interface is built in Visual Studio, allowing users to enter comments and obtain topic rankings, along with word cloud visualizations.
4
artículo
Publicado 2005
Enlace
Enlace
This study has the aim to find a pattern in delayed payments from the information obtained at the moment of requesting credit in a specific creditable product: At the same time, we show a very useful new statistical technique for this area, that is the classification tree (CART) that is applied in situations where we have independent predictor variables of classification or criterion that define the group to which every individual belongs. The paper also tries to find a set of decision rules that allow an explanation of the actual classification and the use of these rules to classify any new individual.
5
artículo
Publicado 2022
Enlace
Enlace
This article addresses some manifestations of narrative in science with the broader intention of contributing to the understanding of its use in factual domains. First, taking as a starting point some previous approaches to the problem of “narrativity”, a theoretical-analytical model is proposed that specifies ten conditions of narrativity. Then, the aim is to determine the areas of scientific discursive production that are more permeable to narrative textuality based on a measurement of the degrees of narrativity of different textual genres. Thus, the differences between texts that report on established knowledge and those that provide new knowledge are explored; a distinction is made between the institutional communication of science and its dissemination; the persuasive and illustrative uses of narrative are addressed; and the field of historical sciences is delimited as a privile...
6
artículo
Publicado 2005
Enlace
Enlace
This study has the aim to find a pattern in delayed payments from the information obtained at the moment of requesting credit in a specific creditable product: At the same time, we show a very useful new statistical technique for this area, that is the classification tree (CART) that is applied in situations where we have independent predictor variables of classification or criterion that define the group to which every individual belongs. The paper also tries to find a set of decision rules that allow an explanation of the actual classification and the use of these rules to classify any new individual.
7
artículo
Publicado 2023
Enlace
Enlace
Today there are many signs of depression, as well as many suicide attempts caused by this emotional disorder, and this is reflected mostly on social networks, mainly on Twitter. For this reason, it is important for specialists and organizations seeking to safeguard people's lives to use software tools to address this problem. For this, in this work a web tool called "UBDevs-Depression-Classifier" is proposed, that allows you to automatically obtain and classify tweets for a specific topic. A greater emphasis was placed on tweets related to COVID-19in the years 2020-2021 the world experienced a pandemic that increased cases of depression in many places. This research proposal focuses on the use of a model based on NLP (Natural Language Processing) for the classification of Tweets in order to find those that incite depression or imply that users are in a bad mood, all this in order t...
8
artículo
This study investigates the application of the Xception architecture for accurate classification of skin lesions, focusing on the early detection of melanoma and other malignant skin conditions. Utilizing deep learning techniques, the research aims to enhance the precision and efficiency of skin lesions diagnosis. The study utilizes the TensorFlow framework and the HAM10000 dataset, comprising a vast collection of benign and malignant skin lesion images, for training and evaluating the Xception model. Preprocessing steps, including data splitting, augmentation, and image resizing, are applied to the dataset. The Xception architecture, a deep convolutional neural network, serves as the foundational model, supplemented with customized classification layers for specialized features and predictions. The model’s performance is evaluated using diverse metrics. The experimental outcomes revea...
9
artículo
Publicado 2025
Enlace
Enlace
The application of Artificial Intelligence (AI) is revolutionizing radio production, offering significant advantages over traditional methods. AI, much like digitalization did, challenges existing production structures and routines, forcing the industry to adapt to technological and market changes. This work identifies three types of AI: analytic, which detect patterns and foresee future situations; assistive, which execute mechanical tasks in an automated manner; and generative, which simulate creative processes and produce content. To contextualize the different functions, six phases have been established in the radio production cycle (Ideation, Research, Production, Distribution, Interaction, and Archiving), and in each phase, specific AI functions that contribute to the process have been identified. An inductive methodology based on the observation and analysis of 96 specific AI appl...
10
artículo
Few floristic inventories and even less syntaxonomical vegetation descriptions of tropical mountain forests exist. The author presents a syntaxonomical treatment of the vegetation of Reserva Biológica of San Francisco at the northern limit of Podocarpus National Park, Ecuador, together with notes on the corresponding soil types. The Lower Montane Forest (1800-2150 m), grouped in the new order Alzateetalia verticillatae, has a very diverse tree layer 20-35 m tall, and are a typical mosaic-climax. It grows on Terric Haplosaprists and Aquic Dystrupepts, developed from old landslide material and extends up to elevations of 2300 m at the bottom of wind-protected riverine valleys. At altitudes from 2100-2650 m (–2750 m), the forest structure and floristic composition change completely. The vegetation types belonging to this Upper Montane Forest form the newly described Purdiaeaetalia nutant...
11
artículo
Few floristic inventories and even less syntaxonomical vegetation descriptions of tropical mountain forests exist. The author presents a syntaxonomical treatment of the vegetation of Reserva Biológica of San Francisco at the northern limit of Podocarpus National Park, Ecuador, together with notes on the corresponding soil types. The Lower Montane Forest (1800-2150 m), grouped in the new order Alzateetalia verticillatae, has a very diverse tree layer 20-35 m tall, and are a typical mosaic-climax. It grows on Terric Haplosaprists and Aquic Dystrupepts, developed from old landslide material and extends up to elevations of 2300 m at the bottom of wind-protected riverine valleys. At altitudes from 2100-2650 m (–2750 m), the forest structure and floristic composition change completely. The vegetation types belonging to this Upper Montane Forest form the newly described Purdiaeaetalia nutant...
12
artículo
This study aims to use machine learning classifiers to predict the kingdom to which an organism belongs by the frequency of use of DNA codons. The study used 13,028 data from GenBank organisms distributed in eleven kingdoms and reduced them to six kingdoms (archaea, bacteria, invertebrates, plants, viruses, and vertebrates) with 9,027 regrouped data. The process required cleaning irrelevant attributes, using measurement metrics of accuracy, precision, sensitivity, and score classifiers, and the adjustment of hyperparameters of the models. The classification algorithms were voting, bagging, boosting, and stacking, using KNN, AD, MLP, SVC, and RF. Random forest was used in selecting the attributes. The stacking ensemble, with its models, better predicts the classification of organisms in the present study.
13
artículo
This study aims to use machine learning classifiers to predict the kingdom to which an organism belongs by the frequency of use of DNA codons. The study used 13,028 data from GenBank organisms distributed in eleven kingdoms and reduced them to six kingdoms (archaea, bacteria, invertebrates, plants, viruses, and vertebrates) with 9,027 regrouped data. The process required cleaning irrelevant attributes, using measurement metrics of accuracy, precision, sensitivity, and score classifiers, and the adjustment of hyperparameters of the models. The classification algorithms were voting, bagging, boosting, and stacking, using KNN, AD, MLP, SVC, and RF. Random forest was used in selecting the attributes. The stacking ensemble, with its models, better predicts the classification of organisms in the present study.
14
tesis de grado
Publicado 2024
Enlace
Enlace
Las tecnologías emergentes posibilitan reenfocar las estrategias de comunicación e interacción con los clientes y usuarios con innovaciones importantes, tales como el uso de vídeos de 360 y la realidad virtual inmersiva (VR) en la promoción turística y hotelera. El objetivo de este trabajo es aprovechar estas tecnologías para optimizar la creación de experiencias en 360, a partir de una automatización de procesos enfocada en la clasificación de imágenes que compondrán dicha experiencia. En nuestra propuesta diseñamos una red neuronal convolucional (CNN), cuyas funciones esenciales son el proceso de extracción de características y el proceso de clasificación y salida de imágenes, debido a que serán utilizados para la composición de tours virtuales. La etapa de extracción de características, está compuesta por varias capas ocultas, como la capa de convolución, la fun...
15
artículo
Publicado 2022
Enlace
Enlace
“The most devastating disease to humanity is commonly known as elephantiasis. Infection usually acquired in childhood but visible indication like pain, disfiguring occur later in life. Severely affected people will have a permanent disability. Not only had it generated physical challenges it also cost for social, psychological, and economical losses. The impact of the disease is so painful and devastating among young men and women as they live with the lifelong disfiguring condition. As the parasite attacks directly to the lymphatic system of the body whose primary function is to drain all the harmful components and impurities from tissues and cells also make a strong immune system of the body to fight against infection and diseases. Since the parasite attack damages the lymphatic vessels and capillaries. Hence the effect is on the flow of lymph resulting in lymphoedema. 90% of the cas...
16
artículo
Publicado 2022
Enlace
Enlace
“The most devastating disease to humanity is commonly known as elephantiasis. Infection usually acquired in childhood but visible indication like pain, disfiguring occur later in life. Severely affected people will have a permanent disability. Not only had it generated physical challenges it also cost for social, psychological, and economical losses. The impact of the disease is so painful and devastating among young men and women as they live with the lifelong disfiguring condition. As the parasite attacks directly to the lymphatic system of the body whose primary function is to drain all the harmful components and impurities from tissues and cells also make a strong immune system of the body to fight against infection and diseases. Since the parasite attack damages the lymphatic vessels and capillaries. Hence the effect is on the flow of lymph resulting in lymphoedema. 90% of the cas...
17
tesis de maestría
Publicado 2020
Enlace
Enlace
Descargue el texto completo en el repositorio institucional de la Universidade Estadual de Campinas: https://hdl.handle.net/20.500.12733/1641108
18
tesis de grado
Publicado 2025
Enlace
Enlace
Inventory management has a valuable role because it identifies the loss of raw materials and maintains the economic sustainability of companies in the market. This research aims to measure inventory control and provide analysis through appropriate methodologies, such as the ABC classification system and the weighted moving average, improving warehouse management and the sales level of the company Tectum. For this purpose, the preliminary diagnosis was made employing a survey, considering The permanence at work, economic situation, classification of products according to importance, frequency of registration of inputs and outputs, knowledge of inventory management and control, and its application; which gave as a primary result that, despite not knowing the storage of products thoroughly, if they know their benefits, so they keep a record where they are classifying the products by importa...
19
artículo
Publicado 2023
Enlace
Enlace
Portable electronic systems allow the analysis and monitoring of continuous time signals, such as human activity, integrating deep learning techniques with cloud computing, causing network traffic and high energy consumption. In addition, the use of algorithms based on neural networks are a very widespread solution in these applications, but they have a high computational cost, not suitable for edge devices. In this context, solutions are created that bring data analysis closer to the edge of the network, so in this paper models adapted to an edge device for the recognition of human activity are evaluated, considering characteristics such as inference time, memory, and precision. Two categories of models based on deep and convolutional neural networks are developed by implementing them in C language and comparing with the TensorFlow Lite platform. The results show that the implementation...
20
artículo
Publicado 2023
Enlace
Enlace
Identifying and classifying text extracted from social networks, following the traditional method, is very complex. In recent years, computer science has advanced exponentially, helping significantly to identify and classify text extracted from social networks, specifically Twitter. This work aims to identify, classify and analyze tweets related to real natural disasters through tweets with the hashtag #NaturalDisasters, using Machine learning (ML) algorithms, such as Bernoulli Naive Bayes (BNB), Multinomial Naive Bayes (MNB), Logistic Regression (LR), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF). First, tweets related to natural disasters were identified, creating a dataset of 122k geolocated tweets for training. Secondly, the data-cleaning process was carried out by applying stemming and lemmatization techniques. Third, exploratory data analysis (EDA) was performed...
