Miguel Cazorla

University of Alicante | UA · Computer Sciences and Artificial Intelligence

In the past years, several works on urban object detection from the point of view of a person have been made. These works are intended to provide an enhanced understanding of the environ- ment for blind and visually challenged people. The mentioned approaches mostly rely in deep learning and machine learning methods. Nonetheless, these approaches o...

The use of semantic representations to achieve place understanding has been widely studied using indoor information. This kind of data can then be used for navigation, localization, and place identification using mobile devices. Nevertheless, applying this approach to outdoor data involves certain non-trivial procedures, such as gathering the infor...

Developmental and epileptic encephalopathy 35 (DEE 35) is a severe neurological condition caused by biallelic variants in ITPA, encoding inosine triphosphate pyrophosphatase, an essential enzyme in purine metabolism. We delineate the genotypic and phenotypic spectrum of DEE 35, analysing possible predictors for adverse clinical outcome. We investig...

The Web is the main source of information for almost all human activities. Webpages are growing exponentially and becoming more sophisticated, presenting a serious challenge to search engines, recommender systems and Web directories. To organize this complex and vast content, webpage classification is the basic technique, usually based on textual a...

Convolutional Neural Networks (CNNs) have become the default paradigm for addressing classification problems, especially, but not only, in image recognition. This is mainly due to their high success rate. Although a number of approaches currently apply deep learning to the 3D shape recognition problem, they are either too slow for online use or too...

Building upon the recent progress in novel view synthesis, we propose its application to improve monocular depth estimation. In particular, we propose a novel training method split in three main steps. First, the prediction results of a monocular depth network are warped to an additional view point. Second, we apply an additional image synthesis ne...

This research focused on the development of a cyber-physical robotic platform to assist speech-language pathologists who are related to articulation disorders in education environments. The first goal was the design and development of the system. The second goal was the qualitative initial validation of the platform with robotics and mobile device...

The World Wide Web is not only one of the most important platforms of communication and information at present, but also an area of growing interest for scientific research. This motivates a lot of work and projects that require large amounts of data. However, there is no dataset that integrates the parameters and visual appearance of Web pages, be...

The most common approaches for classification rely on the inference of a specific class. However, every category could be naturally organized within a taxonomic tree, from the most general concept to the specific element, and that is how human knowledge works. This representation avoids the necessity of learning roughly the same features for a rang...

In this work, we introduce HaReS, a hand rehabilitation system. Our proposal integrates a series of exercises, jointly developed with a foundation for those with motor and cognitive injuries, that are aimed at improving the skills of patients and the adherence to the rehabilitation plan. Our system takes advantage of a low-cost hand-tracking device...

So far, in order to interact with a virtual agent that simulates hands or to teleoperate a robotic hand it is required any kind of device like joysticks, gamepads or VR controllers. These devices map a button press to a predefined action, usually with no fine control of the entity that is being teleoperated, which is unsuitable and unpleasant. In t...

Over one billion people in the world live with some form of disability. This is incessantly increasing due to aging population and chronic diseases. Among the emerging social needs, rehabilitation services are the most required. However, they are scarce and expensive what considerably limits access to them. In this paper, we propose EVA, an augment...

In recent years the advances in Artificial Intelligence (AI) have been seen to play an important role in human well-being, in particular enabling novel forms of human-computer interaction for people with a disability. In this paper, we propose a sEMG-controlled 3D game that leverages a deep learning-based architecture for real-time gesture recognit...

Predicting the condition of the road is an important task for autonomous vehicles to make driving decisions. Vehicles are expected to slow down or stop for potential road risks such as road cracks, bumps and potholes. Vision systems are widely used to provide such information given the rich colours and textures carried by images. This paper present...

With the emergence of low cost 3D sensors, the focus is moving towards the recognition and scene understanding of tridimensional data. This kind of representation is really challenging in terms of computation, and it needs the development of new strategies and algorithms to be handled and interpreted. In this work, we propose NurbsNet, a novel ap...

In this work we present a method for the detection of radiological findings, their location and differential diagnoses from chest x-rays. Unlike prior works that focus on the detection of few pathologies, we use a hierarchical taxonomy mapped to the Unified Medical Language System (UMLS) terminology to identify 189 radiological findings, 22 differe...

This paper describes BIMCV COVID-19+, a large dataset from the Valencian Region Medical ImageBank (BIMCV) containing chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of COVID-19+ patients along with their radiological findings and locations, pathologies, radiological reports (in Spanish), DICOM metadata, Polymerase chain reactio...

Assistive robots are a category of robots that share their. [...]

Deep learning-based methods have proven to be the best performers when it comes to object recognition cues both in images and tridimensional data. Nonetheless, when it comes to 3D object recognition, the authors tend to convert the 3D data to images and then perform their classification. However, despite its accuracy, this approach has some issues....

Pulmonary Embolism (PE) is a respiratory disease caused by blood clots lodged in the pulmonary arteries, blocking perfusion, limiting blood oxygenation, and inducing a higher load on the right ventricle. Pulmonary embolism is diagnosed using contrast enhanced Computed Tomography Pulmonary Angiography (CTPA), resulting in a 3 D image where the pulmo...

Rationale: Computer aided detection (CAD) algorithms for Pulmonary Embolism (PE) algorithms have been shown to increase radiologists' sensitivity with a small increase in specificity. However, CAD for PE has not been adopted into clinical practice, likely because of the high number of false positives current CAD software produces. Objective: To gen...

Over one billion people in the world suffer from some form of disability. Nevertheless, according to the World Health Organization, people with disabilities are particularly vulnerable to deficiencies in services, such as health care, rehabilitation, support, and assistance. In this sense, recent technological developments can mitigate these defici...

Biomarker estimation methods from medical images have traditionally followed a segment-and-measure strategy. Deep-learning regression networks have changed such a paradigm, enabling the direct estimation of biomarkers in databases where segmentation masks are not present. While such methods achieve high performance, they operate as a black-box. In...

The capacity of a robot to automatically adapt to new environments is crucial, especially in social robotics. Often, when these robots are deployed in home or office environments, they tend to fail because they lack the ability to adapt to new and continuously changing scenarios. In order to accomplish this task, robots must obtain new information...

In this paper, a story-telling social robot is proposed. The robot is able to modify the evolution of the story considering the emotions the audience is feeling. To do that, the robot uses the user’s emotion from his/her face. We have used a deep learning-based model to identify the emotion. This model was trained and tested on state of the art dat...

There are a range of small-size robots that cannot afford to mount a three-dimensional sensor due to energy, size or power limitations. However, the best localization and mapping algorithms and object recognition methods rely on a three-dimensional representation of the environment to provide enhanced capabilities. Thus, in this work we propose a m...

Currently, state-of-the-art methods for 3D object recognition rely in a deep learning-pipeline. Nonetheless, these methods require a large amount of data that is not easy to obtain. In addition to that, the majority of them exploit features of the datasets, like the fact of being CAD models to create rendered representation which will not work in r...

As it is well known, some versions of the Pepper robot provide poor depth perception due to the lenses it has in front of the tridimensional sensor. In this paper, we present a method to improving that faulty 3D perception. Our proposal is based on a combination of the actual depth readings of Pepper and a deep learning-based monocular depth estima...

There are great physical and cognitive benefits for older adults who are engaged in active aging, a process that should involve daily exercise. In our previous work on the PHysical Assistant RObot System (PHAROS), we developed a system that proposed and monitored physical activities. The system used a social robot to analyse, by means of computer v...

In several large retail stores, such as malls, sport or food stores, the customer often feels lost due to the difficulty in finding a product. Although these large stores usually have visual signs to guide customers toward specific products, sometimes these signs are also hard to find and are not updated. In this paper, we propose a system that joi...

In this paper, we propose a new dataset for outdoor depth estimation from single and stereo RGB images. The dataset was acquired from the point of view of a pedestrian. Currently, the most novel approaches take advantage of deep learning-based techniques, which have proven to outperform traditional state-of-the-art computer vision methods. Nonethel...

The population ageing phenomenon leads to an unceasing need of home-based healthcare systems to continuously monitor elderly’s cognitive and physical health. In this sense, physical activity may be beneficial in preserving cognition in elder life as well as in providing clinicians and therapists with the indicative of elderly’s health condition. Ne...

Rehabilitation is essential for disabled people to achieve the highest level of functional independence, reducing or preventing impairments. Nonetheless, this process can be long and expensive. This fact together with the ageing phenomenon has become a critical issue for both clinicians and patients. In this sense, technological solutions may be be...

In this paper, we present a novel deep learning-based architecture, which is under the scope of expert and intelligent systems, to perform accurate real-time tridimensional hand pose estimation using a single RGB frame as an input, so there is no need to use multiple cameras or points of view, or RGB-D devices. The proposed pipeline is composed of...

With the lightning speed of technological evolution, several methods have been proposed with the aim of controlling robots and using them to serve humanity. In this work, we present and evaluate a novel learning-based system to control Pepper, the humanoid robot. We leveraged an existing low-cost surface electromyography (sEMG) sensor, that is in t...

Semantic memory stores knowledge about the meanings of words and the relationships between these meanings. In recent years, Artificial Intelligence, in particular Deep Learning, has successfully resolved the identification of classes of elements in images, and even instances of a class, providing a basic form of semantic memory. Unfortunately, inco...

Ambient assisted living (AAL) environments are currently a key focus of interest as an option to assist and monitor disabled and elderly people. These systems can improve their quality of life and personal autonomy by detecting events such as entering potentially dangerous areas, potential fall events, or extended stays in the same place. Nonethele...

The generation of semantic environment representations is still an open problem in robotics. Most of the current proposals are based on metric representations, and incorporate semantic information in a supervised fashion. The purpose of the robot is key in the generation of these representations, which has traditionally reduced the inter-usability...

As estimated by the World Health Organization, there are millions of people who lives with some form of vision impairment. As a consequence, some of them present mobility problems in outdoor environments. With the aim of helping them, we propose in this work a system which is capable of delivering the position of potential obstacles in outdoor scen...

In the last years, the care of dependent people, either by disease, accident, disability, or age, is one of the current priority research topics in developed countries. Moreover, such care is intended to be at patients home, in order to minimize the cost of therapies. Patients rehabilitation will be fulfilled when their integration in society is ac...

Every year, a significant number of people lose a body part in an accident, through sickness or in high-risk manual jobs. Several studies and research works have tried to reduce the constraints and risks in their lives through the use of technology. This work proposes a learning-based approach that performs gesture recognition using a surface elect...

In social robotics, it is important that a mobile robot knows where it is because it provides a starting point for other activities such as moving from one room to another. As a contribution to solving this problem in the field of the semantic location of the mobile robot, we pro- pose to implement a methodology of recognition and scene learning in...

The robot Pepper provides a bad depth estimation. In this paper, we present a method for improving that 3D estimation. The method is based on using the RGB image to predict monocular depth. As it will be shown, the combination of both, monocular and 3D depth, provides a better 3D data.

Accurate visual hand pose estimation at joint level has several applications for human-robot interaction, natural user interfaces and virtual/augmented reality applications. However, it is still an open problem being addressed by the computer vision community. Recent novel deep learning techniques may help circumvent the limitations of standard app...

The accelerated growing of the percentage of elder people, persons with brain-injured related conditions and intellectually challenged are some of the main concerns of the developed countries. These persons often require special cares and even almost permanent overseers that help them to carry out diary tasks. With this issue in mind, we propose an...

In recent years, we have seen a large growth in the number of applications which use deep learning-based object detectors. Autonomous driving assistance systems (ADAS) are one of the areas where they have the most impact. This work presents a novel study evaluating a state-of-the-art technique for urban object detection and localization. In particu...

Semantic localization for mobile robots involves an accurate determination of the kind of place where a robot is located. Therefore, the representation of the knowledge of this place is crucial for the robot. In this paper we present a study for finding a robust model for scene classification procedure for a mobile robot. The proposed system uses C...

In this work, we evaluate the relevance of the choice of loss function in the regression of the Agatston score from 3D heart volumes obtained from non-contrast non-ECG gated chest computed tomography scans. The Agatston score is a well-established metric of cardiovascular disease, where an index of coronary artery disease (CAD) is computed by segme...

The great demographic change leading to an ageing society demands technological solutions to satisfy the increasing varied elderly needs. This paper presents PHAROS, an interactive robot system that recommends and monitors physical exercises designed for the elderly. The aim of PHAROS is to be a friendly elderly companion that periodically suggests...