Adaptive optics can focus light through opaque media by compensating the random phase delay acquired while crossing a scattering curtain. The technique is commonly exploited in many fields, including astrophysics, microscopy, biomedicine and biology. A turbid lens has the capability of producing foci with a resolution higher than conventional optics, however it has a fundamental limit: to obtai...

We describe methods for taking into account unlabeled data in the training of a kernel-based classifier, such as a Support Vector Machines (SVM). We propose two approaches utilizing unlabeled points in the vicinity of labeled ones. Both of the approaches effectively modify the metric of the pattern space, either by using nonspherical Gaussian density estimates which are determined using EM, or ...

Continual Learning (CL) investigates how to train Deep Networks on a stream of tasks without incurring forgetting. CL settings proposed in literature assume that every incoming example is paired with ground-truth annotations. However, this clashes many real-world applications: gathering labeled data, which itself tedious and expensive, becomes infeasible when data flow as stream. This work expl...

quantitative analysis of production through evaluation of inputs consumption quantity is of main principles in agricultural policies, which is followed by increasing in production through optimal use of resources. this study has been conducted to estimate different types of production functions in mechanized farms of broiler chicks located in gorgan city. cross-section survey data were gathered...

Deep learning-based semi-supervised learning (SSL) algorithms have led to promising results in medical images segmentation and can alleviate doctors' expensive annotations by leveraging unlabeled data. However, most of the existing SSL literature tend regularize model training perturbing networks and/or Observing that multi/dual-task attends various levels information which inherent prediction ...

Water migration through heterogeneous soft materials is central to many applications including oil recovery and consumer product stability of foods cosmetics. This slow water transport affects all material properties such as mechanical, optical electrical, but its understanding modelling remains challenging due complex wetting diffusion processes across the material. Here, we study experimental...