AIRCRAFT DETECTION IN LOW VISIBILITY USING ARTIFICIAL INTELLIGENCE
Bad weather often interferes with the functioning of the air transport system. One example is the frequent flight delays for commercial aircraft, resulting in losses for both the airline and passengers. Artificial Intelligence (AI) technology can now minimize delays caused by bad weather, especia...
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| Format: | Final Project |
| Language: | Indonesia |
| Subjects: | |
| Online Access: | https://digilib.itb.ac.id/gdl/view/69269 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Bad weather often interferes with the functioning of the air transport system. One
example is the frequent flight delays for commercial aircraft, resulting in losses for
both the airline and passengers. Artificial Intelligence (AI) technology can now
minimize delays caused by bad weather, especially in low visibility conditions. This
undergraduate thesis discusses AI modeling that can detect aircraft in a low
visibility weather condition, especially in the airport area. The employed method is
the deep learning approach with the YOLOv4 algorithm (single-stage detection),
which is regarded as one of the optimal platforms in this field. There are 600 images
used in this work to create and train three different models. Image Dehazing filter
is employed on the training data before it is trained to produce the detection model.
The result shows that the model has a good performance in terms of performance
metrices. Thus, this model is suitable to be used to detect aircraft in low visibility
conditions. |
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