A5083749288- Video Surveillance and Tracking Methods
- Cultural Heritage Materials Analysis
- Digital Holography and Microscopy
- Autism Spectrum Disorder Research
- Face recognition and analysis
- Gaze Tracking and Assistive Technology
- Face and Expression Recognition
- Conservation Techniques and Studies
- AI in cancer detection
- Advanced Neural Network Applications
- Cell Image Analysis Techniques
- Advanced Image and Video Retrieval Techniques
- Image Processing Techniques and Applications
- Color Science and Applications
- Emotion and Mood Recognition
- Microplastics and Plastic Pollution
- Industrial Vision Systems and Defect Detection
- Assistive Technology in Communication and Mobility
- Radiomics and Machine Learning in Medical Imaging
- Water Quality Monitoring Technologies
- 3D Surveying and Cultural Heritage
- Spectroscopy and Chemometric Analyses
- IoT and Edge/Fog Computing
- Social Robot Interaction and HRI
- Biometric Identification and Security
National Research Council
2015-2024
Institute of Applied Science and Intelligent Systems
2019-2023
Universidade Federal do Rio Grande do Norte
2021-2022
Amazon (United States)
2022
University of Florence
2022
University of Modena and Reggio Emilia
2022
Universidad de Las Palmas de Gran Canaria
2022
Marche Polytechnic University
2022
Webb Institute
2022
Technical University of Munich
2022
Automatic facial expression recognition (FER) is a topic of growing interest mainly due to the rapid spread assistive technology applications, as human-robot interaction, where robust emotional awareness key point best accomplish task. This paper proposes comprehensive study on application histogram oriented gradients (HOG) descriptor in FER problem, highlighting this powerful technique could be effectively exploited for purpose. In particular, highlights that proper set HOG parameters can...
Microplastics (MPs) are a major environmental concern due to their possible impact on water pollution, wildlife, and the food chain. Reliable, rapid, high‐throughput screening of MPs from other components sample after sieving and/or digestion is still highly desirable goal avoid cumbersome visual analysis by expert users under optical microscope. Here, new approach presented that combines 3D coherent imaging with machine learning (ML) achieve accurate automatic detection in filtered samples...
The rapid advances of transportation infrastructure have led to a dramatic increase in the demand for smart systems capable monitoring traffic and street safety. Fundamental these applications are community-based evaluation platform benchmark object detection multi-object tracking. To this end, we organize AVSS2017 Challenge on Advanced Traffic Monitoring, conjunction with International Workshop Street Surveillance Safety Security (IWT4S), evaluate state-of-the-art tracking algorithms...
Alzheimer’s disease (AD) is the most common form of dementia. Computer-aided diagnosis (CAD) can help in early detection associated cognitive impairment. The aim this work to improve automatic dementia MRI brain data. For purpose, we used an established pipeline that includes registration, slicing, and classification steps. contribution research was investigate for first time, our knowledge, three current promising deep convolutional models (ResNet, DenseNet, EfficientNet) two...
This paper gives an overview of the cutting-edge approaches that perform facial cue analysis in healthcare area. The document is not limited to global face but it also concentrates on methods related local cues (e.g., eyes). A research taxonomy introduced by dividing its main features: eyes, mouth, muscles, skin, and shape. For each feature, computer vision-based tasks aiming at analyzing goals could be pursued are detailed.
In this paper, a computational approach is proposed and put into practice to assess the capability of children having had diagnosed Autism Spectrum Disorders (ASD) produce facial expressions. The based on computer vision components working sequence images acquired by an off-the-shelf camera in unconstrained conditions. Action unit intensities are estimated analyzing local appearance then both temporal geometrical relationships, learned Convolutional Neural Networks, exploited regularize...
Autism Spectrum Disorders (ASD) are a group of lifelong disabilities that affect people's communication and understanding social cues. The state the art witnesses how technology, in particular robotics, may offer promising tools to strengthen research therapy ASD. This work represents first attempt use machine-learning strategies during robot-ASD children interactions, terms facial expression imitation, making possible an objective evaluation children's behaviours then giving possibility...
The computational analysis of facial expressions is an emerging research topic that could overcome the limitations human perception and get quick objective outcomes in assessment neurodevelopmental disorders (e.g., Autism Spectrum Disorders, ASD). Unfortunately, there have been only a few attempts to quantify expression production most scientific literature aims at easier task recognizing if either present or not. Some face this challenging exist but they do not provide comprehensive study...
Diatoms are among the dominant phytoplankters in marine and freshwater habitats, important biomarkers of water quality, making their identification classification one current challenges for environmental monitoring. To date, taxonomy species populating a column is still conducted by biologists on basis own experience. On other hand, deep learning recognized as elective technique solving image problems. However, large amount training data usually needed, thus requiring synthetic enlargement...
Several studies have found a delay in the development of facial emotion recognition and expression children with an autism spectrum condition (ASC). interventions been designed to help fill this gap. Most them adopt technological devices (i.e., robots, computers, avatars) as social mediators reported evidence improvement. Few aimed at promoting abilities and, among these, most focused on recognition. Moreover, crucial point is generalization ability acquired during treatment naturalistic...
Colorectal cancer is one of the most lethal cancers because late diagnosis and challenges in selection therapy options. The histopathological colon adenocarcinoma hindered by poor reproducibility a lack standard examination protocols required for appropriate treatment decisions. In current study, using state-of-the-art approaches on benchmark datasets, we analyzed different architectures ensembling strategies to develop efficient network combinations improve binary ternary classification. We...
Information and communication technologies (ICTs) have been proved to a great impact in enhancing social, communicative, language development children with autism spectrum disorders (ASDs) as demonstrated by plenty of effective technological tools reported the literature for diagnosis, assessment, treatment such neurological diseases. On contrary, there are very few works exploiting ICT study mechanisms that trigger behavioral patterns during specialized sessions focused on social...
It has been proved that Autism Spectrum Disorders (ASD) are associated with amplified emotional responses and poor control. Underlying mechanisms characteristics of these difficulties in using, sharing responding to emotions still not understood. This is because advanced computational approaches for studying details facial expressions have based on the use invasive instruments (such markers motion capture or Electromyographs) can affect behaviors and, above all, restrict possibility...
This paper presents a detailed study about different algorithmic configurations for estimating soft biometric traits. In particular, recently introduced common framework is the starting point of study: it includes an initial facial detection, subsequent traits description, data reduction step, and final classification step. The are featured by descriptors strategies to build training dataset scale in input classifier. Experimental proofs have been carried out on both publicly available...
The management of water resources is becoming increasingly important in several contexts, including agriculture. Recently, innovative agricultural practices, advanced sensors, and Internet Things (IoT) devices have made it possible to improve the efficiency use. However, application control strategies based on machine learning techniques that enables adoption smart irrigation scheduling immediate economic, social, environmental benefits. This challenging research area has attracted attention...
Automatic recognition of products on grocery shelf images is a new and attractive topic in computer vision machine learning since, it can be exploited different application areas. This paper introduces complete end-to-end pipeline, without preliminary radiometric spatial transformations usually involved while dealing with the considered issue, provides systematic investigation recent models based convolutional neural networks for addressing product task by exploiting proposed pipeline...
Computer vision is a powerful tool for healthcare applications since it can provide objective diagnosis and assessment of pathologies, not depending on clinicians’ skills experiences. It also help speed-up population screening, reducing health care costs improving the quality service. Several works summarise systems in medical imaging, whereas less work devoted to surveying approaches goals using ambient intelligence, i.e., observing individuals natural settings. Even more, there lack papers...
A quantitative morphological analysis of archaeological objects represents an important element for historical evaluations, artistic studies and conservation projects. At present, a variety contact instruments high-resolution surface survey is available on the market, but because their invasivity they are not well received in field artwork conservation. On contrary, optical testing techniques have seen successful growth last few years due to effectiveness safety. In this work we present...