Abubakar Siddique

2 accepted papers

2026

Prompt-Free Unknown Label Generation for Open World Detection in Remote Sensing

Abdullah Azeem, Ruisheng Wang, Qingquan Li, Abubakar Siddique

CVPR 2026

Autonomous object detection in remote sensing requires systems that can discover new categories and assign them usable labels during deployment. Existing Open-World Object Detectors identify unknown objects but leave them unnamed until manual annotation. In contrast, Open-Vocabulary Detectors recogn

Cited by 0 Source ↗Scholar ↗

2022

Self-Supervised Learning for Panoptic Segmentation of Multiple Fruit Flower Species

Abubakar Siddique, Amy Tabb, Henry Medeiros

RA-L 2022

Convolutional neural networks trained using manually generated labels are commonly used for semantic or instance segmentation. In precision agriculture, automated flower detection methods use supervised models and post-processing techniques that may not perform consistently as the appearance of the

Cited by 13 Source ↗code ↗Scholar ↗