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README.md

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 ## Overview
 
-The Earthwork Network Architecture (ENA) is the deep learning model designed to compare the accurate estimation prediction of earthwork quantities in construction. This repository includes four distinct deep learning models—MLP, LSTM, Transformers, and LLM-based architectures (BERT)—tailored for automating and enhancing earthwork quantity estimation from CAD-based cross-sectional drawings.
+Earthwork Network Architecture (ENA) is designed to compare deep learning models for accurate estimation prediction of earthwork volumes from CAD-based cross-sectional drawings in construction engineering domain. The construction field, commonly known as AEC (Architecture, Engineering and Construction), has lagged behind other fields in the development of AI and LLM models for various reasons. In this open source, we demonstrate that LLM based on Transformers can be extended and applied to various applications in the engineering field through various comparisons among different methods. However, we also note that LLM may not be a cost-effective method for certain use cases. This huggingface repository contains four unique ENA deep learning models: MLP, LSTM, Transformers, and LLM-based architecture tailored to automate and improve earthwork volume estimation from CAD-based cross-sectional drawings.
 <img src="https://huggingface.co/mac999/earthwork-net-model/resolve/main/doc/img3.webp" width="600">
 <img src="https://huggingface.co/mac999/earthwork-net-model/resolve/main/doc/img5.png" width="600">