In the previous article, we talk about what is UAV and its general application fields, in this article, we extend the UAV’s role in detail.
(1) Vehicle Identification and Tracking
As UAV is equipped with an intelligent monitoring camera, based on background deep learning, people and vehicles on the road can be effectively identified and analyzed. Because of its high-speed and unrestricted 3D space, the characters and vehicles can be identified, monitored, and tracked in any environment.
(2) Air to Ground Detection
UAV can effectively shoot and draw the 3D maps by combining high-speed motion camera and radar, so as to provide 3D stereographs and 2D plans. UAV, as an air platform, can complete various tasks by effectively matching relevant equipment. In addition, artificial intelligence can play more possibilities
(3) Replace Manual Work at Height
In high-altitude operation, if the inspection is carried out by a human workforce, not only it is a waste of time, also it is very dangerous. In order to avoid this danger, the camera that the UAV carries can take pictures of target objects, compare them with the background data, so as to detect whether there are cracks and other hidden dangers on the surface.
(4) Smart Agriculture, Forestry and Plant Protection
Whether it is to improve the efficiency of pesticide spraying or to monitor the prevention and control of crop diseases, pests, weeds, or to track comprehensive plant pollination, or to recognize the plant’s growth, scalable data is needed. Thanks to the UAV collection service, we can obtain high-quality agricultural products and high-quality fruit forests.
At present, AI enterprises have to go through three stages: research and development, training, and implementation, and each stage requires the support of massive basic data sets.
In machine learning, with each round of testing, engineers would discover new possibilities to perfect the model performance, therefore, the workflow changes constantly. There are uncertainty and variability in data labeling. The clients need workers who can respond quickly and make changes in workflow, based on the model testing and validation phase.
Therefore, High-quality labeled data for machine learning algorithms training has become the core part of artificial intelligence development in recent years.
Data Labeling Types in UAV Industry
With real-time workflow management, Bytebridge can provide high-quality data with efficiency:
- ML-assisted capacity can help reduce human errors by automatically pre-labeling, which also gains time.
- The real-time QA and QC are integrated into the labeling workflow as the consensus mechanism is introduced to ensure accuracy.
- All work results are completely screened and inspected by the machine and human workforce.
In this way, ByteBridge can affirm our data acceptance and accuracy rate is over 98%.
- Clients can set labeling rules, iterate data features, attributes, and task flows, scale up or down, make changes.
Clients can monitor the labeling progress and get the results in real-time on the dashboard.
These labeling tools are already available on the dashboard: Image Classification, 2D Boxing, Polygon, Cuboid.
We can provide personalized annotation tools and services according to customer requirements.
- A collaboration of the human-work force and AI algorithms ensure a 50% lower price compared to the conventional market.
If you need data labeling and collection services, please have a look at bytebridge.io, the clear pricing is available.
Please feel free to contact us: firstname.lastname@example.org
1 How the Data Labeling Service Empowers Drones(Unmanned Aerial Vehicles) in 2021? — Part1
2 Labeling Service Case Study — Video Annotation — Vehicle License Plate Recognition
3 Data Annotation Service and Its Key Advantage — Flexibility
4 Eight Common Data Annotation and Labeling Tools
5 What is Semantic Segmentation, Instance Segmentation, Panoramic segmentation?