Juan Gabriel Colonna

Juan Gabriel Colonna
Federal University of Amazonas | UFAM · Institute of Computing (IComp)

Ph.D. Computer Science

About

40
Publications
8,779
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
267
Citations
Additional affiliations
February 2013 - September 2017
Federal University of Amazonas
Position
  • PhD Student
Education
March 2013
Federal University of Amazonas
Field of study
  • Computer science
March 2010 - March 2012
Federal University of Amazonas
Field of study
  • Computer science
March 2002 - December 2009
Universidad Nacional de Río Cuarto
Field of study
  • Telecommunications engineering

Publications

Publications (40)
Preprint
Full-text available
Camera traps are a strategy for monitoring wildlife that collects a large number of pictures. The number of images collected from each species usually follows a long-tail distribution, i.e., a few classes have a large number of instances while a lot of species have just a small percentage. Although in most cases these rare species are the classes o...
Article
Full-text available
In this article, we introduce explainable methods to understand how Human Activity Recognition (HAR) mobile systems perform based on the chosen validation strategies. Our results introduce a new way to discover potential bias problems that overestimate the prediction accuracy of an algorithm because of the inappropriate choice of validation methodo...
Conference Paper
Full-text available
Plagiarism is a serious and growing problem in the academic environment, which interferes directly in the quality of teaching. This research is contextualized in the problem the detection of plagiarism in CS1 courses. In these courses, the codes developed by students tend to be simple and small, making it difficult for traditional methods based on...
Article
Full-text available
In general, the unit-demand envy-free pricing problem has proven to be APX-hard, but some special cases can be optimally solved in polynomial time. When substitution costs that form a metric space are included, the problem can be solved in O(n4) time, and when the number of consumers is equal to the number of items—all with a single copy so that ea...
Article
Full-text available
Animal biodiversity has been experiencing rapid decline due to various reasons such as habitat loss and degradation, invasive species, and environment pollution. Recent advances in acoustic sensors provide a novel way to monitor animals through investigating collected bioacoustic recordings. To accurately monitor animals, the precondition is the hi...
Conference Paper
Full-text available
Monitoring wildlife through camera traps produces a massive amount of images, whose a significant portion does not contain animals, being later discarded. Embedding deep learning models to identify animals and filter these images directly in those devices brings advantages such as savings in the storage and transmission of data, usually resource-co...
Preprint
Full-text available
Monitoring wildlife through camera traps produces a massive amount of images, whose a significant portion does not contain animals, being later discarded. Embedding deep learning models to identify animals and filter these images directly in those devices brings advantages such as savings in the storage and transmission of data, usually resource-co...
Preprint
Full-text available
Automatic analysis of bioacoustic signals is a fundamental tool to evaluate the vitality of our planet. Frogs and bees, for instance, may act like biological sensors providing information about environmental changes. This task is fundamental for ecological monitoring still includes many challenges such as nonuniform signal length processing, degrad...
Article
Full-text available
Content-based image retrieval (CBIR) aims to display, as a result of a search, images with the same visual contents as a query. This problem has attracted increasing attention in the area of computer vision. Learning-based hashing techniques are amongst the most studied search approaches for approximate nearest neighbors in large-scale image retrie...
Article
Full-text available
Automatic monitoring of biodiversity by acoustic sensors has become an indispensable tool to assess environmental stress at an early stage. Due to the difficulty in recognizing the Amazon’s high acoustic diversity and the large amounts of raw audio data recorded by the sensors, the labeling and manual inspection of this data is not feasible. Theref...
Preprint
Full-text available
Technology applied in education can provide great benefits and overcome challenges by facilitating access to learning objects anywhere and anytime. However, technology alone is not enough, since it requires suitable planning and learning methodologies. Using technology can be problematic, especially in determining whether learning has occurred or n...
Article
Full-text available
Smartphones have emerged as a revolutionary technology for monitoring everyday life, and they have played an important role in Human Activity Recognition (HAR) due to its ubiquity. The sensors embedded in these devices allows recognizing human behaviors using machine learning techniques. However, not all solutions are feasible for implementation in...
Preprint
Full-text available
Automatic monitoring of biodiversity by acoustic sensors has become an indispensable tool to assess environmental stress at an early stage. Due to the difficulty in recognizing the Amazon’s high acoustic diversity and the large amounts of raw audio data recorded by the sensors, the labeling and manual inspection of this data is not feasible. Theref...
Conference Paper
Full-text available
This work present a new approach to develop a vacuum cleaner. This use actor-critic algorithm. We execute tests with three other algoritms to compare. Even that, we develop a new simulator based on Gym to execute the tests.
Article
Full-text available
In bioacoustic recognition approaches, a “flat” classifier is usually trained to recognize several species of anurans, where the number of classes is equal to the number of species. Consequently, the complexity of the classification function increases proportionally with the number of species. To avoid this issue, we propose a “hierarchical” approa...
Article
In this work, we present a comprehensive study of Singular Spectrum Analysis (SSA) applied to bioacoustics signal enhancement. The SSA method decomposes the signal into oscillatory components with physical meaning, allowing us to analyze different sound frequencies. One of the major SSA's challenges is how to choose those oscillatory components tha...
Article
We present a comprehensive study of temporal Low-Level acoustic Descriptors (LLDs) to automatically segment anuran calls in audio streams. The acoustic segmentation, or syllable extraction, is a key task shared by most of the bioacoustical species recognition systems. Consequently, the syllable extraction has a direct impact on the classification r...
Conference Paper
Full-text available
In this article, we propose a framework to detect emotional states from facial expressions of the students in the context of digital learning platforms. We analyzed and discussed the use of correlation and entropy between student's emotional states and their performance during a multiple choice assessment. We conducted an experiment with 27 student...
Conference Paper
Bioacoustics signals classification is an important instrument used in environmental monitoring as it gives the means to efficiently acquire information from the areas, which most of the time are unfeasible to approach. To address these challenges, bioacoustics signals classification systems should meet some requirements, such as low computational...
Conference Paper
Full-text available
Neste trabalho, apresentamos um método para detecção de sons de motosserras, com o objetivo de auxiliar no combate de extração ilegal de ma-deira nas florestas tropicais. Em nossa abordagem utilizamos um método de classificação de uma classe para detectar apenas o som de interesse e rejei-tar todos os outros sons, sejam estes naturais ou artificiai...
Conference Paper
Full-text available
Neste trabalho apresentamos um método de detecção de motosserras através de som para auxiliar no combate a extração ilegal de madeira. Em nossa abordagem é utilizada a decomposição Wavelet (W) nas altas frequên-cias, o que divide de forma ótima a classe de sons naturais das demais classes e divide muito bem, apesar de ainda haver sobreposição, a cl...
Conference Paper
Full-text available
In bioacoustic recognition approaches, a ''flat'' classifier is usually trained to recognize several species of anuran, where the number of classes is equal to the number of species. Consequently, the complexity of the classification function increases proportionally to the amount of species. To avoid this issue we propose a "hierarchical'' approac...
Conference Paper
Full-text available
In this work, we introduce a more appropriate (or alternative) approach to evaluate the performance and the generalization capabilities of a framework for automatic anuran call recognition. We show that, by using the common k-folds Cross-Validation (k-CV) procedure to evaluate the expected error in a syllable-based recognition system the recognitio...
Poster
Full-text available
* Hypothesis: the phylogenetic taxonomy may describe acoustics similarities among species that belong to the same genus and family. * The model has to decide between a small number of classes when compared to a ’flat’ classifier. * We can inspect the confusion matrices at each decomposition level. * We can get some insights about the similarities o...
Conference Paper
Full-text available
Anurans (frogs or toads) are closely related to the ecosystem and they are commonly used by biologists as early indicators of ecological stress. Automatic classification of anurans, by processing their calls, helps biologists analyze the activity of anurans on larger scale. Wireless Sensor Networks (WSNs) can be used for gathering data automaticall...
Conference Paper
Full-text available
This paper describes an experimental evaluation of the main machine learning supervised techniques to be used for the human activities recognition in the context of technological education using data collected from smartphones sensors. The overall goal is to use the recognition of activities to identify students with attention deficit or hyperac-ti...
Article
A bioacustical animal recognition system is composed of two parts: (1) the segmenter, responsible for detecting syllables (animal vocalization) in the audio; and (2) the classifier, which determines the species/animal whose the syllables belong to. In this work, we first present a novel technique for automatic segmentation of anuran calls in real t...
Article
A bioacoustical animal recognition system is composed of two parts: (1) the segmenter, responsible for detecting syllables (animal vocalization) in the audio; and (2) the classifier, which determines the species/animal whose the syllables belong to. In this work, we first present a novel technique for automatic segmentation of anuran calls in real...
Conference Paper
Full-text available
Wildlife monitoring through Sensors Networks is a new tool used by biologists to acquire information about animals and their habitat. • Machine learning techniques are often used for automatic sound classification. • Before classification, each call needs to be segmented into smaller units called syllables (preprocessing step). • The correct segmen...
Conference Paper
In this work, we evaluate the performance of a distributed classification system in a Wireless Sensor Network for monitoring anurans. Our aim is to study how to take advantage of the collaborative nature of the sensor network to improve the recognition of anuran calls. To accomplish this, we evaluate four low-cost techniques (majority vote, weighte...
Thesis
Full-text available
Wildlife monitoring is often used by biologist to acquire information about animals and their habitat. In this context, animal sounds and vocalizations usually provide a specie fingerprint that is used for classifying the target species in a given site. For that matter, Wireless Sensor Networks (WSNs) represent an interesting option for automatical...
Conference Paper
Full-text available
Wildlife sounds provide relevant information for non-intrusive environmental monitoring when Wireless Sensor Networks (WSNs) are used. Thus, collecting such audio data, while maximizing the network lifetime, is a key challenge for WSNs. In this work, we propose a methodology that applies Compressive Sensing (CS) aiming at collecting as little data...
Conference Paper
Full-text available
Anurans (frogs or toads) are commonly used by bi-ologists as early indicators of ecological stress. The reason is that anurans are closely related to the ecosystem. Although several sources of data may be used for monitoring these animals, anuran calls lead to a non-intrusive data acquisition strategy. Moreover, wireless sensor networks (WSNs) may...
Conference Paper
Full-text available
Wireless Sensor Networks consist of a powerful technology for monitoring the physical world. Particularly, in-network data fusion techniques are very important to applications such as target classification and tracking to reduce the communication burden in these constrained networks. However, the efficiency of the solution can be affected by the da...
Conference Paper
Full-text available
In this work, we developed an automatic system for classifying anura (frogs and toads) based on their vocalizations. Each bioacustic signal has been segmented on the first stage into smaller units called "syllables", followed by a preprocessing step, composed by a pre-emphasis filter and a Hamming window that prepares the signal for feature extract...

Network

Cited By