Jónathan Heras

Universidad de La Rioja (Spain) | UNIRIOJA · Mathematics and Computation

In waste recycling plants, measuring the waste volume and weight at the beginning of the treatment process is key for a better management of resources. This task can be conducted by using orthophoto images, but it is necessary to remove from those images the objects, such as containers or trucks, that are not involved in the measurement process. Th...

Deep learning models are the state-of-the-art approach to deal with semantic segmentation tasks. However, training deep models require a considerable amount of images that might be difficult to obtain. This issue can be faced by means of data augmentation techniques that generate new images by applying geometric or colour transformations, or more r...

Nowadays, public institutions usually provide videos that contain important information in their webpages. However, people suffering from hearing impairment have difficulties accessing content provided by that mean, and the manual transcription of those videos is a time-consuming task. This problem can be faced by means of Automatic Speech Recognit...

Stomata are pores in the epidermal tissue of leaf plants formed by specialised cells called guard cells, which regulate the stomatal opening. Stomata facilitate gas exchange, being pivotal in the regulation of processes such as pho-tosynthesis and transpiration. The analysis of the number and behaviour of stomata is a task carried out by studying m...

Drought is one of the biggest problems for crop production and also affects the survival and persistence of soil rhizobia. The reduced presence of rhizobia limits the establishment of symbiosis and endangers the productivity of legumes, the main source of plant protein worldwide. Thus, the preservation of soil microbial diversity is essential becau...

The accumulation of tau aggregates is associated with neurodegenerative diseases collectively known as tauopathies. Tau aggregates (fibrils) isolated from different tauopathies such as Alzheimer's Disease, corticobasal degeneration and progressive supranuclear palsy have distinct Cryo-EM structures with respect to their packed fibril cores. To unde...

Diabetic Retinopathy (DR) is an ocular complication of diabetes that leads to a significant loss of vision. Screening retinal fundus images allows ophthalmologists to early detect and diagnose this disease; however, the manual interpretation of images is a time-consuming task. Deep image classification models deal with this drawback and provide an...

The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible. While AI models for glaucoma screening from CFPs have shown promising results in laboratory settings, their performan...

In this paper we describe the mathematical foundations of a new approach to semi-supervised Machine Learning. Using techniques of Symbolic Computation and Computer Algebra, we apply the concept of persistent homology to obtain a new semi-supervised learning method.

Forms are a widespread type of template-based document used in a great variety of fields including, among others, administration, medicine, finance, or insurance. The automatic extraction of the information included in these documents is greatly demanded due to the increasing volume of forms that are generated in a daily basis. However, this is not...

This paper introduces the Human Action Multi-Modal Monitoring in Manufacturing (HA4M) dataset, a collection of multi-modal data relative to actions performed by different subjects building an Epicyclic Gear Train (EGT). In particular, 41 subjects executed several trials of the assembly task, which consists of 12 actions. Data were collected in a la...

Background and objective: Age-related macular degeneration (AMD) is an eye disease that happens when ageing causes damage to the macula, and it is the leading cause of blindness in developed countries. Screening retinal fundus images allows ophthalmologists to early detect, diagnose and treat this disease; however, the manual interpretation of ima...

Myocarditis is among the most important cardiovascular diseases (CVDs), endangering the health of many individuals by damaging the myocardium. Microbes and viruses, such as HIV, play a vital role in myocarditis disease (MCD) incidence. Lack of MCD diagnosis in the early stages is associated with irreversible complications. Cardiac magnetic resonanc...

The distribution of any non-conservative variable in the deep open ocean results from the circulation and mixing of water masses (WMs) of contrasting origin and from the initial preformed composition, modified during ongoing simultaneous biological and/or geochemical processes. Estimating the contribution of the WMs composing a sample is useful to...

Semantic segmentation models based on deep learning techniques have been successfully applied in several contexts. However, non-expert users might find challenging the use of those techniques due to several reasons, including the necessity of trying different algorithms implemented in heterogeneous libraries, the configuration of hyperparameters, t...

Automatic yield monitoring and in-field robotic harvesting by low-cost cameras require object detection and segmentation solutions to tackle the poor quality of natural images and the lack of exactly-labeled datasets of consistent sizes. This work proposed the application of deep learning for semantic segmentation of natural images acquired by a lo...

The development of mobile and on the edge applications that embed deep convolutional neural models has the potential to revolutionise biomedicine. However, most deep learning models require computational resources that are not available in smartphones or edge devices; an issue that can be faced by means of compact models. The problem with such mode...

Nowadays, Machine Learning and Deep Learning methods have become the state-of-the-art approach to solve data classification tasks. In order to use those methods, it is necessary to acquire and label a considerable amount of data; however, this is not straightforward in some fields, since data annotation is time consuming and might require expert kn...

Digitizing historical music books can be challenging since staves are usually mixed with typewritten text explaining some characteristics of them. In this work, we propose a new methodology to undertake such a digitization task. After scanning the pages of the book, the different blocks of text and staves can be detected and organized into music pi...

Epidermal bladder cells (EBC) are specialized structures of halophyte plants that accumulate salt and other metabolites, and are thought to be involved in salinity tolerance, as well as in UV-B protection, drought and other stresses tolerance. However, the role of the EBC size, density or volume remains to be confirmed since few studies have addres...

Myocarditis is a cardiovascular disease caused by infectious agents, especially viruses. Compared to other cardiovascular diseases, myocarditis is very rare, occurring mainly due to chest pain or heart failure. Cardiac magnetic resonance (CMR) imaging is a popular technique for diagnosis of myocarditis. Factors such as low contrast, different noise...

Background and objectives. Domain shift is a generalisation problem of machine learning models that occurs when the data distribution of the training set is different to the data distribution encountered by the model when it is deployed. This is common in the context of biomedical image segmentation due to the variance of experimental conditions, e...

Forms are a widespread type of template-based document used in a great variety of fields including, among others, administration, medicine, finance, or insurance. The automatic extraction of the information included in these documents is greatly demanded due to the increasing volume of forms that are generated in a daily basis. However, this is not...

Schizophrenia (SZ) is a mental disorder whereby due to the secretion of specific chemicals in the brain, the function of some brain regions is out of balance, leading to the lack of coordination between thoughts, actions, and emotions. This study provides various intelligent deep learning (DL)-based methods for automated SZ diagnosis via electroenc...

Due to the increasing volume of forms that are generated in a daily basis, the automatic extraction of the information included in these template-based documents is greatly demanded. However, this is not a straightforward task due to the great diversity of templates with different location of form entities, and the quality of the scanned documents....

Deep learning algorithms for object detection on images have been successfully applied in several fields; however, non-expert users might find difficult to adopt these techniques due to several reasons. First of all, using detection models requires some knowledge about the library employed to built them; and, in general, it is not usually possible...

An epiretinal membrane (ERM) is an eye disease that can lead to visual distortion and, in some cases, to loss of vision. Screening retinal fundus images allows ophthalmologists to early detect and diagnose this disease; however, the manual interpretation of images is a time-consuming task. In spite of the existence of several computer vision tools...

Schizophrenia (SZ) is a mental disorder whereby due to the secretion of specific chemicals in the brain, the function of some brain regions is out of balance, leading to the lack of coordination between thoughts, actions, and emotions. This study provides various intelligent Deep Learning (DL)-based methods for automated SZ diagnosis via EEG signal...

Simplicial-map neural networks are a recent neural network architecture induced by simplicial maps defined between simplicial complexes. It has been proved that simplicial-map neural networks are universal approximators and that they can be refined to be robust to adversarial attacks. In this paper, the refinement toward robustness is optimized by...

Background and objectives Infectious diseases produced by antimicrobial resistant microorganisms are a major threat to human, and animal health worldwide. This problem is increased by the virulence and spread of these bacteria. Surface motility has been regarded as a pathogenicity element because it is essential for many biological functions, but a...

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor problems for people with a detrimental effect on the functioning of the nervous system. In order to diagnose MS, multiple screening methods have been proposed so far; among them, magnetic resonance imaging (MRI) has received considerable attention among physi...

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor problems for people with a detrimental effect on the functioning of the nervous system. In order to diagnose MS, multiple screening methods have been proposed so far; among them, magnetic resonance imaging (MRI) has received considerable attention among physi...

The outbreak of the corona virus disease (COVID-19) has changed the lives of most people on Earth. Given the high prevalence of this disease, its correct diagnosis in order to quarantine patients is of the utmost importance in steps of fighting this pandemic. Among the various modalities used for diagnosis, medical imaging, especially computed tomo...

Object detection models based on deep learning techniques have been successfully applied in several contexts; however, non-expert users might find challenging the use of these techniques due to several reasons, including the necessity of trying different algorithms implemented in heterogeneous libraries, the configuration of hyperparameters, the la...

Broadly speaking, an adversarial example against a classification model occurs when a small perturbation on an input data point produces a change on the output label assigned by the model. Such adversarial examples represent a weakness for the safety of neural network applications, and many different solutions have been proposed for minimizing thei...

Background and objectives Deep learning techniques are the state-of-the-art approach to solve image classification problems in biomedicine; however, they require the acquisition and annotation of a considerable volume of images. In addition, using deep learning libraries and tuning the hyperparameters of the networks trained with them might be chal...

Background and objectives Spheroids are the most widely used 3D models for studying the effects of different micro-environmental characteristics on tumour behaviour, and for testing different preclinical and clinical treatments. In order to speed up the study of spheroids, imaging methods that automatically segment and measure spheroids are instrum...

Stomata are pores in the epidermal tissue of leaf plants formed by specialised cells called guard cells, which regulate the stomatal opening. Stomata facilitate gas exchange, being pivotal in the regulation of processes such as photosynthesis and transpiration. The analysis of the number and behaviour of stomata is a task carried out by studying mi...

A correct localisation of tables in a document is instrumental for determining their structure and extracting their contents; therefore, table detection is a key step in table understanding. Nowadays, the most successful methods for table detection in document images employ deep learning algorithms; and, particularly, a technique known as fine-tuni...

The automatic assessment of the aesthetic value of an image is a task with many applications but really complex and challenging, due to the subjective component of the aesthetics for humans. The computational systems that carry out this task are usually composed of a set of ad hoc metrics proposed by the researchers and a machine learning system. W...

Nowadays, the use of transfer learning, a deep learning technique, is growing to solve imaging problems in several contexts such as biomedicine where the amount of images is limited. However, applying transfer learning might be challenging for users without experience due to the complexity of the deep learning frameworks. To facilitate the task of...

Image classification is a computer vision task that has several applications in diverse fields like security, biology or medicine; and, currently, deep learning techniques have become the state-of-the-art to create image classification models. This growing use of deep learning techniques is due to the large amount of data, the fast increase of the...

Stomata are pores in the epidermal tissue of plants formed by specialized cells called occlusive cells or guard cells. Analyzing the number and behavior of stomata is a task carried out by studying microscopic images, and that can serve, among other things, to better manage crops in agriculture. However, quantifying the number of stomata in an imag...

Deep learning techniques are currently the state of the art approach to deal with image classification problems. Nevertheless, non-expert users might find challenging the use of these techniques due to several reasons, including the lack of enough images, the necessity of trying different models and conducting a thorough comparison of the results o...

A correct localisation of tables in a document is instrumental for determining their structure and extracting their contents; therefore, table detection is a key step in table understanding. Nowadays, the most successful methods for table detection in document images employ deep learning algorithms; and, particularly, a technique known as fine-tuni...

Fungi have diverse biotechnological applications in, among others, agriculture, bioenergy generation, or remediation of polluted soil and water. In this context, culture media based on colour change in response to degradation of dyes are particularly relevant, but measuring dye decolourisation of fungal strains mainly relies on a visual and semiqua...

We propose algorithms based on monomial resolution theory for simplicial homology computation. We explore some alternatives that can either be used as a preprocessing step for homology computation or as alternatives to the usual linear algebra approach. We show the results of some computer experiments to demonstrate the performance of a C++ impleme...

Background Deep learning techniques have been successfully applied to bioimaging problems; however, these methods are highly data demanding. An approach to deal with the lack of data and avoid overfitting is the application of data augmentation, a technique that generates new training samples from the original dataset by applying different kinds of...

Background and objective: Deep learning techniques have been successfully applied to tackle several image classification problems in bioimaging. However, the models created from deep learning frameworks cannot be easily accessed from bioimaging tools such as ImageJ or Icy; this means that life scientists are not able to take advantage of the resul...

This study analyzes the impact of adding a review exercises module to an online tool used in a software engineering degree program. The objective of the module is to promote students’ self-learning effort to improve their performance. We also intend to determine if this new feature has any effect on the amount of code copies detected in lab session...

In this work, we explore the differences between proctored and unproctored Internet administration for a Basque language low-stakes test considering demographic factors such as age, gender, and knowledge level in the subject. To this aim, we have developed an ad hoc application that allows us to establish a set of filters and techniques that succes...

In today’s globalized world, it seems important that students can telecollaborate in a team by making effective use of information and communication technologies. This collaboration format can positively influence their academic performance, enhance engineering student interest in the subject, and improve skills such as communication and teamwork....

In today’s globalized world, it seems important that students can telecollaborate in a team by making effective use of information and communication technologies. This collaboration format can positively influence their academic performance, enhance engineering student interest in the subject, and improve skills such as communication and teamwork....

Due to the broad use of deep learning methods in Bioimaging, it seems convenient to create a framework that facilitates the task of analysing different models and selecting the best one to solve each particular problem. In this work-in-progress, we are developing a Python framework to deal with such a task in the case of bioimage classification. Na...

Nowadays, deep learning techniques are playing an important role in different areas due to the fast increase in both computer processing capacity and availability of large amount of data. Their applications are diverse in the field of bioimage analysis, e.g. for classifying and segmenting microscopy images, for automating the localization of protei...

Object detection is a computer vision field that has applications in several contexts ranging from biomedicine and agriculture to security. In the last years, several deep learning techniques have greatly improved object detection models. Among those techniques, we can highlight the YOLO approach, that allows the construction of accurate models tha...

Background: Fungi have diverse biotechnological applications in, among others, agriculture, bioenergy generation, or remediation of polluted soil and water. In this context, culture media based on color change in response to degradation of dyes are particularly relevant; but measuring dye decolorisation of fungal strains mainly relies on a visual...

Object detection is an area of computer vision with applications in several contexts such as biomedicine and security; and it is currently growing thanks to the availability of datasets of images, and the use of deep learning techniques. In order to apply object detection algorithms is instrumental to know the quality of the regions detected by the...

Several approaches exist to data-mining big corpora of formal proofs. Some of these approaches are based on statistical machine learning, and some – on theory exploration. However, most are developed for either untyped or simply-typed theorem provers. In this paper, we present a method that combines statistical data mining and theory exploration in...

Several approaches exist to data-mining big corpora of formal proofs. Some of these approaches are based on statistical machine learning, and some -- on theory exploration. However, most are developed for either untyped or simply-typed theorem provers. In this paper, we present a method that combines statistical data mining and theory exploration i...

Background and objective: The effective processing of biomedical images usually requires the interoperability of diverse software tools that have different aims but are complementary. The goal of this work is to develop a bridge to connect two of those tools: ImageJ, a program for image analysis in life sciences, and OpenCV, a computer vision and...

The quantification of synapses is instrumental to measure the evolution of synaptic densities of neurons under the effect of some physiological conditions, neuronal diseases or even drug treatments. However, the manual quantification of synapses is a tedious, error-prone, time-consuming and subjective task; therefore, reliable tools that might auto...

Background and objectives: Disk diffusion testing, known as antibiogram, is widely applied in microbiology to determine the antimicrobial susceptibility of microorganisms. The measurement of the diameter of the zone of growth inhibition of microorganisms around the antimicrobial disks in the antibiogram is frequently performed manually by speciali...

Background and objective: The manual transformation of DNA fingerprints of dominant markers into the input of tools for population genetics analysis is a time-consuming and error-prone task; especially when the researcher deals with a large number of samples. In addition, when the researcher needs to use several tools for population genetics analy...

The classification of organisms is a daily-basis task in biology as well as other contexts. This process is usually carried out by comparing a set of descriptors associated with each object. However, general-purpose statistical packages offer a limited number of methods to perform such a comparison, and specific tools are required for each concrete...

In the last few years, self- and peer-assessment have been increasingly employed not only as an evaluation method, but also as a learning procedure. The consistency and difference between self- and peer-assessments as compared to instructor-assessments have been previously studied, and a friendship bias was discovered. In this study, we introduce e...

Different learning methods such as project-based learning, spiral learning and peer assessment have been implemented in science disciplines with different outcomes. This paper presents a proposal for a project management course in the context of a computer science degree. Our proposal combines three well-known methods: project-based learning, spira...

Resumen Nuestro equipo de investigación se compone de seis profesores de La Rioja que colaboramos estrechamente con tres profesores del País Vasco. Inicialmente nuestras experiencias innovadoras se centraron en asignaturas de bases de datos. Destacamos un experimento donde los estudiantes realizaron un trabajo junto a un alumno de otra universidad...