Small Object Aerial Person Detection Dataset

<p><strong>Small Object Aerial Person Detection Dataset:</strong></p> <p>The aerial dataset publication comprises a collection of frames captured from unmanned aerial vehicles (UAVs) during flights over the University of Cyprus campus and Civil Defense exercises. The dataset is primarily intended for people detection, with a focus on detecting small objects due to the top-view perspective of the images. The dataset includes annotations generated in popular formats such as YOLO, COCO, and VOC, making it highly versatile and accessible for a wide range of applications. Overall, this aerial dataset publication represents a valuable resource for researchers and practitioners working in the field of computer vision and machine learning, particularly those focused on people detection and related applications.</p> <p>&nbsp;</p> <table> <tbody> <tr> <td>Subset</td> <td>Images</td> <td>People</td> </tr> <tr> <td>Training</td> <td>2092</td> <td>40687</td> </tr> <tr> <td>Validation</td> <td>523</td> <td>10589</td> </tr> <tr> <td>Testing</td> <td>521</td> <td>10432</td> </tr> </tbody> </table> <p>&nbsp;</p> <p>It is advised to further enhance the dataset so that random augmentations are probabilistically applied to each image prior to adding it to the batch for training. Specifically, there are a number of possible transformations such as geometric (rotations, translations, horizontal axis mirroring, cropping, and zooming), as well as image manipulations (illumination changes, color shifting, blurring, sharpening, and shadowing).</p>