3 accepted papers
In this paper, we propose a novel approach to enhance few-shot object detection (FSOD) by utilizing projection modules, which are commonly employed in self-supervised learning to improve feature transferability. We integrate a multilayer perceptron (MLP) as a projection module within a Faster RCNN m…
In this work, we introduce a novel fusion and training strategy aimed at facilitating transfer learning to enhance classification in hyperspectral airborne imagery. Our training strategy has two stages: first we train separate convolutional neural network (CNN) models, one for the bands for which pr…
In this work, we consider the problem of synchronising separately located transmitters and a staring array receiver that also has a local transmitter. The acknowledged benefits of using separate transmitters in active sensing are often undermined by the difficulty in accurate synchronisation of the…