Vision Transformer Neural Nets Application for Object Recognition over Water in Um Qaser Port - Hanoon, Fatima Mallak; Ali, Khawla Hussein (International Journal of Intelligent Systems and Applications in Engineering, 2023)
The objective of this work is to give the of an experimental investigation into the efficiency of contemporary models of visual transformers utilized within the context of machine vision systems in robotic complexes for the purpose of object detection.On the basis of the findings of the research that was conducted, several suggestions have been developed on the application of models to the challenge of categorizing maritime traffic in Iraqi ports. Object recognition in ports is a crucial task for ensuring the safety and security of the port facilities. In this paper, Our study involved utilizing Vision Transformer (ViT) neural networks to identify above-water objects in Um Qaser port. We gathered a set of images of such objects from the port and employed the ViT model to train on this dataset. The outcomes of our study demonstrate that ViT neural networks perform better than conventional convolutional neural networks (CNNs) for this purpose, with a classification accuracy exceeding 90%.