Bird species identification is becoming increasingly crucial for avian biodiversity conservation and assisting ornithologists in quantifying the presence of birds in a given area. Convolutional Neural Networks (CNNs) are ...

The rapid evolution of technology directly impacts the skills and jobs needed in the next decade. Users can, intentionally or unintentionally, develop different skills by creating, interacting with, and consuming the content ...

Probabilistic databases have emerged as an extension of relational databases that can handle uncertain data under possible worlds semantics. Although the problems of creating effective means of probabilistic data representation ...

Sequential recommendation aims to predict the user’s next action based on personal action sequences. The major challenge in this task is how to achieve high performance recommendation under the data sparsity problem. ...

The study of placeness has been focus for researchers trying to understand the impact of locations on their surroundings and tourism, the loss of it by globalization and modernization and its effect on tourism, or the ...

In the last couple of years, there has been an increasing need for Human-Computer Interaction (HCI) systems that do not require touching the devices to control them, such as ATMs, self service kiosks in airports, terminals ...

This paper analyses changes in some items of the User Experience Questionnaire (UEQ) for use in the context of Costa Rican culture. Although a Spanish version of the UEQ was created in 2012, we use a double-translation and ...

A clustering validation index (CVI) is employed to evaluate an algorithm’s clustering results. Generally, CVI statistics can be split into three classes, namely internal, external, and relative cluster validations. Most ...

Artificial intelligence presents different approaches, one of these is the use of neural network algorithms, a particular context is the farming sector and these algorithms support the detection of diseases in flowers, ...

Video surveillance for real-world anomaly detection and prevention using deep learning is an important and difficult research area. It is imperative to detect and prevent anomalies to develop a nonviolent society. Realworld ...