Browsing Faculty of Engineering by Subject "Object detection"
Now showing items 1-4 of 4
-
HM-net: A regression network for object center detection and tracking on wide area motion imagery
(IEEE, 2022)Wide Area Motion Imagery (WAMI) yields high resolution images with a large number of extremely small objects. Target objects have large spatial displacements throughout consecutive frames. This nature of WAMI images makes ... -
Offloading deep learning powered vision tasks from UAV to 5G edge server with denoising
(IEEE, 2023-06)Offloading computationally heavy tasks from an unmanned aerial vehicle (UAV) to a remote server helps improve battery life and can help reduce resource requirements. Deep learning based state-of-the-art computer vision ... -
Variational bayesian multiple instance learning with gaussian processes
(IEEE, 2017)Gaussian Processes (GPs) are effective Bayesian predictors. We here show for the first time that instance labels of a GP classifier can be inferred in the multiple instance learning (MIL) setting using variational Bayes. ... -
YOLODrone+: improved YOLO architecture for object detection in UAV images
(IEEE, 2022)The performance of object detection algorithms running on images taken from Unmanned Aerial Vehicles (UAVs) remains limited when compared to the object detection algorithms running on ground taken images. Due to its various ...
Share this page