4 accepted papers
We present a distributed first-order and second-order adaptive hybrid optimization algorithm (DAHO) for multi-robot systems. A team of robots collaboratively trains a shared deep neural network using only local data while exchanging model updates via peer-to-peer robot communication. Raw data never …
Federated learning is a machine learning paradigm that enables decentralized clients to collaboratively learn a shared model while keeping all the training data local. While considerable research has focused on federated image generation, particularly Generative Adversarial Networks, Variational Aut
Salient object detection identifies objects in an image that grab visual attention. Although contextual features are considered in recent literature, they often fail in real-world complex scenarios. We observe that this is mainly due to two issues: First, most existing datasets consist of simple for…
Psychology studies and behavioural observation show that humans shift their attention from one location to another when viewing an image of a complex scene. This is due to the limited capacity of the human visual system in simultaneously processing multiple visual inputs. The sequential shifting of…