Tensor-Factorization-Based 3D Single Image Super-Resolution with Semi-Blind Point Spread Function Estimation

The second row shows (from left to right) the results obtained us- ing the Maximum Likelihood (ML) approach proposed in [6], using the ML-NL approach (using only the likelihood term

classical image alignment technique applied on two successive images and then describe our technique that derives from image alignment. The image reference, i.e. the first image of

The AUTOFocus mode is a semi-automatic closed loop process as it needs the surgeon’s supervision to correctly converge to- ward the target in three steps: at each iteration the

Finally, we explore the independent effects of both program components (cash versus conditionalities) by analyzing the relationship between the level of cash

ةنزاوملا زجع ىلع ةيدقنلا ةسايسلا رثأ : حيضوتل ىلع ةيدقنلا ةسايسلا ريثأت زجع لا تاريغتملا نم ةعومجم ذخأن ةينازيملا م يدقنلا ةسايسلاب رثأتت يتلا ةفلتخ و

To evaluate this novelty detection approach on a visual navigation domain, we trained an autoencoder on a set of simulated camera images from a hallway-type

— Fluid collected in floating réservoirs with the anterior oesophagus cannulated and the posterior oeso- phagus ligated and severed, or cannulated and severed, as

Since the objective of a fusion method is to simulate a target image at a given date, in order to perform the validation it was necessary to generate fused images at target dates