Boundary and lens rigidity for non-convex manifolds

We study the boundary and lens rigidity problems on domains without assuming the convexity of the boundary. We show that such rigidities hold when the domain is a simply connected compact Riemannian surface without conjugate points. For the more general class of non-trapping compact Riemannian surfaces with no conjugate points, we show lens rigidity. We also prove the injectivity of the X-ray transform on tensors in a variety of settings with non-convex boundary and, in some situations, allowing a non-empty trapped set.Comment: 40 pages, 2 figure

A general support theorem for analytic double fibration transforms

We develop a systematic approach for resolving the analytic wave front set for a class of integral geometry transforms appearing in various tomography problems. Combined with microlocal analytic continuation, this leads to uniqueness and support theorems for analytic integral transforms which are in the microlocal double fibration framework introduced by Guillemin. For the case of ray transforms, we show that the double fibration setup has a concrete interpretation in terms of curve families obtained by projecting integral curves of a fixed vector field on some fiber bundle down to the base. This setup includes geodesic X-ray type transforms, null bicharacteristic ray transforms and transforms related to real principal type systems. We also study transforms integrating over submanifolds of any codimension, and give geometric characterizations for the Bolker condition required for recovering singularities. Our approach is based on a general result related to recovering the analytic wave front set of a function from its transform given by a suitable analytic elliptic Fourier integral operator. This approach extends and unifies a number of previous works. We use wave packet transforms to extrapolate the geometric features of wave front set propagation for such operators when their canonical relation satisfies the Bolker condition.Comment: 46 page

A study on different experimental configurations for age, race, and gender estimation problems

This paper presents a detailed study about different algorithmic configurations for estimating soft biometric traits. In particular, a recently introduced common framework is the starting point of the study: it includes an initial facial detection, the subsequent facial traits description, the data reduction step, and the final classification step. The algorithmic configurations are featured by different descriptors and different strategies to build the training dataset and to scale the data in input to the classifier. Experimental proofs have been carried out on both publicly available datasets and image sequences specifically acquired in order to evaluate the performance even under real-world conditions, i.e., in the presence of scaling and rotation

Why reintroducing military conscription in Europe would be counterproductive

The reintroduction of military conscription has frequently been proposed as a way to instil national values in younger citizens. These arguments have gained added significance in Europe following Russia’s invasion of Ukraine. Drawing on new research, Vincenzo Bove, Riccardo Di Leo and Marco Giani argue that many of the proposed benefits of conscription are difficult to identify empirically. Indeed, far from fostering cohesion among citizens, conscription appears to be linked to a decline in institutional trust

Vision-based Human Fall Detection Systems using Deep Learning: A Review

Human fall is one of the very critical health issues, especially for elders and disabled people living alone. The number of elder populations is increasing steadily worldwide. Therefore, human fall detection is becoming an effective technique for assistive living for those people. For assistive living, deep learning and computer vision have been used largely. In this review article, we discuss deep learning (DL)-based state-of-the-art non-intrusive (vision-based) fall detection techniques. We also present a survey on fall detection benchmark datasets. For a clear understanding, we briefly discuss different metrics which are used to evaluate the performance of the fall detection systems. This article also gives a future direction on vision-based human fall detection techniques