The trend of bringing machine learning (ML) to the Internet Things (IoT) field devices is becoming ever more relevant, also reducing overall energy need applications. ML models are usually trained in cloud and then deployed on edge devices. Most IoT generate large amounts unlabeled data, which expensive challenging annotate. This paper introduces self-learning autonomous inferencing pipeline (A...

Abstract Image dehazing is an increasingly widespread approach to address the degradation of images natural environment by low-visibility weather, dust and other phenomena. Advances in autonomous systems platforms have increased need for low-complexity, high-performing techniques. However, while recent learning-based image approaches significantly performance, this has often been at expense com...