 Our numerical results show that combining super-resolution with gradient sparsity is particularly helpful for object detection and labelling tasks (such as QR scanning and land-cover classification), for which our results are shown to improve the classification precision of standard clustering algorithms and state-of-the art deep architectures 3 .
<clarity>  Our numerical results show that combining super-resolution with gradient sparsity is particularly helpful for object detection and labelling tasks (such as QR scanning and land-cover classification), for which our results are shown to improve the classification precision of standard clustering algorithms and state-of-the art deep architectures 3 .
 Our numerical results show that combining super-resolution with gradient sparsity is particularly helpful for object detection and labelling tasks (such as QR scanning and land-cover classification), for which our results are shown to improve the 3 .