coco names

Citation Author(s):
Nvindia
Corporation
Submitted by:
Anusha Mahajan
Last updated:
Tue, 12/19/2023 - 15:12
DOI:
10.21227/a511-aa37
Data Format:
Research Article Link:
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Abstract 

The dataset comprises diverse objects detectable by drones during aerial surveys, encapsulating an extensive array of environmental and man-made elements. Encompassing natural entities like trees, water bodies, terrain features, and vegetation, it also incorporates urban objects such as buildings, roads, vehicles, and infrastructure. The dataset delineates distinct categories, encompassing fine-grained details within each classification, catering to the nuances of aerial detection. It offers a comprehensive spectrum of shapes, sizes, orientations, and environmental contexts, simulating real-world scenarios encountered during drone missions. Rich in diversity, this dataset facilitates training and evaluation of object detection algorithms, enabling drones to discern and classify multifarious objects within their operational landscapes, advancing their precision and adaptability in various applications like environmental monitoring, urban planning, disaster management, and more.

Instructions: 

object list

Comments

new dataset for objects list to detect

Submitted by Anusha Mahajan on Tue, 12/19/2023 - 15:12

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