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 ...

Restricted Boltzmann Machines (RBMs) are among the most widely pursed techniques in the context of deep learning-based applications. Their usage enables sundry parallel implementations, which have become pivotal in nowadays ...

Deep learning techniques have been paramount in the last years, mainly due to their outstanding results in a number of applications, that range from speech recognition to face-based user identification. Despite other ...

While the number of studies dealing with fine root dynamics in deep soils layers (depth > 1 m) has increased sharply recently, the phenology, the morphology, the anatomy and the role of deep fine roots are still poorly ...

The integrity of the various structures within the feet depends on their blood supply. Lesions of the feet often require revascularization, which if successful avoids the need for amputation. To provide greater anatomical ...

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 ...