The healthy transportation of energy and its delivery to distant places is one of the vital issues in terms of ensuring the continuity of energy. There are various types of poles used in power transmission lines and they can be classified according to different voltage levels. In general, the type of pole used depends on a number of factors, including the voltage level of the transmission line, the location of the line, and the expected load and weather conditions. The fact that different types of poles have different properties and are designed to withstand different loads and weather conditions reveals that the poles used in power transmission lines should be classified. By classifying the poles, engineers can ensure that the appropriate pole is selected for each location along the transmission line. This helps ensure that the transmission line can transmit energy safely, efficiently and reliably. It may be useful and necessary to use a deep learning model trained and tested with visual data to classify poles used in power transmission lines. Automating the pole classification process can save time and resources and help ensure that the appropriate pole is selected for each location along the transmission line. Additionally, visual data can provide valuable information on the condition of the poles and help identify potential maintenance needs. Classifying poles using deep learning techniques such as Convolutional Neural Networks (CNNs) can contribute to science by improving our understanding of the physical properties and behavior of power transmission poles. Data collected and analyzed using deep learning models can help inform the design of future power transmission systems and contribute to the development of more efficient, secure and reliable energy infrastructure. In this study, automatic classification of poles used in power transmission lines was performed using convolutional neural networks and successful accuracy rates were achieved. ORCID NO: 0000-0001-9105-508X
Keywords: High Voltage Poles, CNN, Transfer Learning
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