Use Of Unmanned Aerial Vehicle Uav Video
Wireless Communications with Unmanned Aerial Vehicles Use Of Unmanned Aerial Vehicle Uav.Use Of Unmanned Aerial Vehicle Uav - sorry
The advancements in the design and technology of UAVs are driving the market growth. The deployment of intelligence algorithms in UAVs is developing myriad opportunities and new avenues for the commercial use of drones. The decline in the prices of the drones over the past decade has also fueled its demand for commercial applications. Furthermore, the legalization and adoption of commercial drones in the market by government authorities have also brought many new valuable avenues for the business and usability in the market. However, there are certain applications of the UAVs that are still in the testing phase. The safety and security issues associated with the use of UAVs are among the major factors hindering the market growth. Moreover, stringent government regulations related to the range and payloads are also among the major constraints in the market growth. Emergency management has emerged as one of the most important applications of drones.
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Sign In. Therefore, this paper proposes a novel imagery classification method based on U-Net fully convolution neural network combine with a conditional random field model to process this kind of images. First, deep and abstract visual features are extracted by convolution and pooling operations, and then feature map is reconstructed by deconvolution and upsampling operations. Then, a softmax classifier generates the initial classification results.
OOf, conditional random field is used to optimize the classification results.
The effectiveness and robustness of the proposed method is verified on the UAV imagery data collected from Guangdong Province. Experimental results indicate that the method proposed in this paper can effectively classify different objects with an overall accuracy larger than Article :.
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