Enhancing Direction-of-Arrival Estimation with Multi-Task Learning.

There are numerous methods in the literature for Direction-of-Arrival (DOA) estimation, including both classical and machine learning-based approaches that jointly estimate the Number of Sources (NOS) and DOA. However, most of these methods do not fully leverage the potential synergies between these two tasks, which could yield valuable shared information. To address this limitation, in this article, we present a multi-task Convolutional Neural Network (CNN) capable of simultaneously estimating both the NOS and the DOA of the signal.

Experimental characterization of gaseous ion beams produced with the advanced ion source for hadrontherapy (AISHa) at 18 GHz.

The Advanced Ion Source for Hadrontherapy (AISHa) is an electron cyclotron resonance ion source operating at 18 GHz, developed at the Istituto Nazionale di Fisica Nucleare-Laboratori Nazionali del Sud, with the aim of producing high intensity and low emittance highly charged ion beams for hadrontherapy purposes. Moreover, thanks to its unique peculiarities, AISHa is a suitable choice for industrial and scientific applications. In the framework of the INSpIRIT and IRPT projects, in collaboration with the Centro Nazionale di Adroterapia Oncologica, new candidates for cancer treatment are being developed.

Blind quality assessment of authentically distorted images.

Blind image quality assessment (BIQA) of authentically distorted images is a challenging problem due to the lack of a reference image and the coexistence of blends of distortions with unknown characteristics. In this article, we present a convolutional neural network based BIQA model. It encodes the input image into multi-level features to estimate the perceptual quality score.

Composition and Style Attributes Guided Image Aesthetic Assessment.

The aesthetic quality of an image is defined as the measure or appreciation of the beauty of an image. Aesthetics is inherently a subjective property but there are certain factors that influence it such as, the semantic content of the image, the attributes describing the artistic aspect, the photographic setup used for the shot, etc. In this paper we propose a method for the automatic prediction of the aesthetics of an image that is based on the analysis of the semantic content, the artistic style and the composition of the image.