El aprendizaje profundo es una técnica emergente de inteligencia artificial (IA) que utiliza
estructuras de análisis sofisticadas llamadas redes neuronales para realizar asociaciones …

When developing new software, testing can take up half of the resources. Although a
considerable amount of work has been done to automate software testing, fixing bugs after …

This thesis focuses on the urgent need to develop an effective threat modeling approach in
the field of Artificial Intelligence (AI) and Machine Learning (ML). The necessity for this …

The study machine learning for software based on Soft Computing technology. It analyzes
Soft Computing components. Their use in software, their advantages and challenges are …

Résumé En apprentissage automatique, un modèle est un programme qui fait des
prédictions ou prend des décisions. Il ne résulte pas d'une activité de programmation …

In Component-Based Software Engineering, the process of selecting software components
is under several risk factors. Traditionally, these have been identified or mitigated with …

Objetivo. Proponer el uso de herramientas de inteligencia artificial como modelo para la
sincronización de las etapas de decisión y compartición espectral de la radio cognitiva …

A probabilistic model checker is a software tool for formal modeling and analysis of systems
that exhibit random or probabilistic behaviour. Over probabilistic models, we analyze an …

MLWare applications is an upcoming term used to refer to Software applications that use
Machine Learning approaches/algorithms (in part) to address the application's objective …

The adoption of Machine Learning (ML) in software applications has increased in domains
like healthcare, banking and others. leading to coining of the term MLWare applications …