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My name is Fabio Augusto Faria, I am Brazilian, born in São Roque, Sao Paulo state. I lived with my father and two brothers until early 2003, when I moved to Presidente Prudente city aiming to study Computer Science at the Sao Paulo State University (UNESP). In that period, I developed a passion for the academic life and became determined to pursue an academic career after receiving my Bachelor's degree. Upon graduation, end of Fall 2007 (5-year program), I moved to Campinas city for the Master's degree program of the Institute of Computing (IC), University of Campinas (UNICAMP). I finished my Masters in March/2010 under supervision of Prof. Dr. Ricardo da Silva Torres. I received a Doctorate degree in Computer Science at the same university in March/2014 under supervision of Prof. Dr. Torres and co-supervision of Prof. Dr. Anderson Rocha. From March/2014 to March/2015, I was post-doc research at Institute of Computing - University of Campinas  under supervision of Prof. Dr. Torres. From April/2012 to April/2013 I lived in Tampa/Florida where I was a visiting scholar at University of South Florida (USF) under supervision of Prof. Dr. Sudeep Sarkar. From July/2019 to September/2020, I was a visiting researcher at the Australian Institute of Machine Learning (AIML) - The University of Adelaide/Australia under supervision of Prof. Dr. Gustavo Carneiro. Currently, I am an Assistant Professor of the Institute of Science and Technology at the Federal University of Sao Paulo (UNIFESP).  My research interests include machine learning, image processing, information fusion, and data mining. When it is possible, I try to support Slow Science.

Stomata

Stomata

Plant stomata are essential structures (pores) that control the exchange of gases between plant leaves and the atmosphere, and also they influence plant adaptation to climate through photosynthesis and transpiration stream. Many works in literature aim for a better understanding of these structures and their role in the evolution process and the behavior of plants. Although stomata studies in dicots species have advanced considerably in the past years, even there is not much knowledge about the

Projeto Extensão

Projeto Extensão

Este projeto foi criado pelos alunos e professores do ICT-UNIFESP em parceria com o IFMS-Aquidauana e tem como objetivo mostrar para sociedade o comportamento dos municípios ao longo do período de vacinação da população brasileira.

Generative Adversarial Nets

Generative Adversarial Nets

This paper focuses on one of the most fascinatingand successful, but challenging generative models in the liter-ature: the Generative Adversarial Networks (GAN). Recently,GAN has attracted much attention by the scientific commu-nity and the entertainment industry due to its effectiveness ingenerating complex and high-dimension data, which makes ita superior model for producing new samples, compared withother types of generative models.

Evolutionary Framework

Evolutionary Framework

Convolutional Neural Networks (CNN) have been being widely employed to solve the challenging remote sensing task of aerial scene classification. Nevertheless, it is not straightforward to find single CNN models that can solve all aerial scene classification tasks, allowing the development of a better alternative, which is to fuse CNN-based classifiers into an ensemble. However, an appropriate choice of the classifiers that will belong to the ensemble is a critical factor, as it is unfeasible..

ForestEyes Project

ForestEyes Project

cientific projects involving volunteers for analyzing, collecting data, and using their computational resources, known as Citizen Science (CS), have become popular due to advances in information and communication technology (ICT). Many CS projects have been proposed to involve citizens in different knowledge domain such as astronomy, chemistry, mathematics, and physics. This work presents a CS project called ForestEyes, which proposes to track deforestation in rainforests.

Meta-Feature Engineering

Meta-Feature Engineering

The aerial scene classification task is a challenging problem to remote sensing area with important applicability to civil and military affairs. A technique that has achieved excellent results in this task is the convolutional neural network (CNN). CNNs are powerful semantic-level feature extraction techniques successfully applied to many application domains...

Cocaine Dependence Recognition

Cocaine Dependence Recognition

Cocaine dependence devastates millions of human lives. Despite of a variety of treatments, there is a very high rate of individual relapse to drug use. In the last decade, functional magnetic resonance imaging (fMRI) proved to be a powerful tool to diagnose and understand different pathologies. This work provides advances in the identification of cocaine dependence and in the relapse prediction based on fMRI classification. We improve the traditional methodology...

Identification of fruit flies

Identification of fruit flies

Fruit flies are pests of major economic importance in agriculture. Among these pests it is possible to high- light some species of genus Anastrepha, which attack a wide range of fruits, and are widely distributed in the American tropics and subtropics. Researchers seek to identify fruit flies in order to implement management and control programs as well as quarantine restrictions. However, fruit fly identification is manually performed by scarce specialists through analysis of morphological...

Artificial Intelligence + Health Data

Artificial Intelligence + Health Data

A thirteen-researcher group from digital health and artificial intelligence areas to produce a book, wich aims to be a guide for readers. A clear sense of how health data should be analyzed using tools based on intelligent algorithms.

Reccurence Plot for PlantRecognition

Reccurence Plot for PlantRecognition

In this article, we propose the use of a new representation of time series to improve plants recognition rates. This representation, called recurrence plot (RP), is a technique for nonlinear data analysis, which represents repeated events on time series into a two-dimensional representation (an image). Therefore, image descriptors can be used to characterize visual properties from this RP images so that these features can be used as input of a classifier.

E-Phenology Project

E-Phenology Project

Environmental changes are becoming an important issue in the world. An example that represents these problems arise in the context of phenology studies. Phenology, the study of natural recurring phenomena and its relation to climate, is a traditional science of observe the cycles of plants and animals and relate mainly to local meteorological data, as well as to biotic interactions and phylogeny. Recently, phenology has gain importance as the simplest and most reliable indicator of the...

Digital forensics

Digital forensics

In a society where social networks became powerful communication tools and are more ubiquitous than ever, it is now paramount to design and deploy methods that guarantee the authenticity of the broadcast information. Images, for instance, considered one of the most powerful communication media, appear as the most shared documents at these social networks, mainly because current mobile devices allow anyone to capture thousands of images anywhere at anytime.

 

06/25/2021 - Pre-launch our book about AI applied to health data. [link]

06/02/2021 - A new journal paper has been accepted to FGCS 2021. [link]

05/11/2020 - Tutorial SIBGRAPI 2020. [link]

08/22/2020 - Best paper in the ERAMIA-SP 2020.

06/22/2020 - A new conference paper has been accepted to ICPR 2020. [link]

06/22/2020 - A new journal paper has been accepted to GRSL 2020. [link]

11/08/2018 - The honorable Mention Award in the WUW-SIBGRAPI 2018. [link]

NEWS & UPDATES

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