The Deep learning framework has been widely used in different applications from medicine to engineering. However, there is a lack of works that manage to deal with the issue of hyperparameter fine-tuning, since machine ...

This paper explores mindfulness as an innovation for improving literacy skills of deep reading.

The Deep Learning models have drawn ever-increasing research interest owing to their intrinsic capability of overcoming the drawback of traditional algorithm. Hence, we have adopted the representative Deep Learning methods ...

Deep learning techniques, such as Deep Boltzmann Machines (DBMs), have received considerable attention over the past years due to the outstanding results concerning a variable range of domains. One of the main shortcomings ...

This work presents two Deep Reinforcement Learning (Deep-RL) approaches to enhance the problem of mapless navigation for a terrestrial mobile robot. The methodology focus on comparing a Deep-RL technique based on the Deep ...

With the advent of deep learning, the number of works proposing new methods or improving existent ones has grown exponentially in the last years. In this scenario, “very deep” models were emerging, once they were expected ...