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Found 4 papers, 2 papers with code
Sequence Models for Drone vs Bird Classification
Moreover, we propose a new drone vs. bird sequence classification dataset to train and evaluate the proposed architectures.
Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection
In this work, an open-source framework called Slicing Aided Hyper Inference (SAHI) is proposed that provides a generic slicing aided inference and fine-tuning pipeline for small object detection.
Track Boosting and Synthetic Data Aided Drone Detection
Our method approaches the drone detection problem by fine-tuning a YOLOv5 model with real and synthetically generated data using a Kalman-based object tracker to boost detection confidence.
Ranked #1 on
Object Detection
on Drone vs Bird
(using extra training data)
Automated question generation and question answering from Turkish texts
In this work, we fine-tune a multilingual T5 (mT5) transformer in a multi-task setting for QA, QG and answer extraction tasks using Turkish QA datasets.
