The growing demand for energy-efficient solutions has led to increased interest in analyzing building facades,as buildings contribute significantly to energy consumption in urban environments.However,conventional imag...The growing demand for energy-efficient solutions has led to increased interest in analyzing building facades,as buildings contribute significantly to energy consumption in urban environments.However,conventional image segmentation methods often struggle to capture fine details such as edges and contours,limiting their effectiveness in identifying areas prone to energy loss.To address this challenge,we propose a novel segmentation methodology that combines object-wise processing with a two-stage deep learning model,Cascade U-Net.Object-wise processing isolates components of the facade,such as walls and windows,for independent analysis,while Cascade U-Net incorporates contour information to enhance segmentation accuracy.The methodology involves four steps:object isolation,which crops and adjusts the image based on bounding boxes;contour extraction,which derives contours;image segmentation,which modifies and reuses contours as guide data in Cascade U-Net to segment areas;and segmentation synthesis,which integrates the results obtained for each object to produce the final segmentation map.Applied to a dataset of Korean building images,the proposed method significantly outperformed traditional models,demonstrating improved accuracy and the ability to preserve critical structural details.Furthermore,we applied this approach to classify window thermal loss in real-world scenarios using infrared images,showing its potential to identify windows vulnerable to energy loss.Notably,our Cascade U-Net,which builds upon the relatively lightweight U-Net architecture,also exhibited strong performance,reinforcing the practical value of this method.Our approach offers a practical solution for enhancing energy efficiency in buildings by providing more precise segmentation results.展开更多
Traditional Chinese architecture in the narrative of a system has existed more than 3,000 years. As the core values of the enlightenment function of social ethics, traditional architecture externalizes symbol of ＂st...Traditional Chinese architecture in the narrative of a system has existed more than 3,000 years. As the core values of the enlightenment function of social ethics, traditional architecture externalizes symbol of ＂state＂ sensual ethical echo. So metaphorical rules in architecture can combine with the normal life. Traditional architectural form as famous communication home Marshall McLuhan＇s ＂human extension＂, leads the order and the rules in the form of elevation. The spread of universal ethics, traditional architectural symmetry axis ceremony, and the adornment of the mythical thinking component, are traditional Chinese ethics of society to describe the core of creation through three points sequence structure constraint. The wisdom of metaphor in these ideas is the life gene of Chinese culture. In the construction of the contemporary social upheaval spreading vision, recognition of traditional architecture ethics through righteousness obviously has been recasting social ethics of ＂treatment＂.展开更多
基金supported by Korea Institute for Advancement of Technology(KIAT):P0017123,the Competency Development Program for Industry Specialist.
文摘The growing demand for energy-efficient solutions has led to increased interest in analyzing building facades,as buildings contribute significantly to energy consumption in urban environments.However,conventional image segmentation methods often struggle to capture fine details such as edges and contours,limiting their effectiveness in identifying areas prone to energy loss.To address this challenge,we propose a novel segmentation methodology that combines object-wise processing with a two-stage deep learning model,Cascade U-Net.Object-wise processing isolates components of the facade,such as walls and windows,for independent analysis,while Cascade U-Net incorporates contour information to enhance segmentation accuracy.The methodology involves four steps:object isolation,which crops and adjusts the image based on bounding boxes;contour extraction,which derives contours;image segmentation,which modifies and reuses contours as guide data in Cascade U-Net to segment areas;and segmentation synthesis,which integrates the results obtained for each object to produce the final segmentation map.Applied to a dataset of Korean building images,the proposed method significantly outperformed traditional models,demonstrating improved accuracy and the ability to preserve critical structural details.Furthermore,we applied this approach to classify window thermal loss in real-world scenarios using infrared images,showing its potential to identify windows vulnerable to energy loss.Notably,our Cascade U-Net,which builds upon the relatively lightweight U-Net architecture,also exhibited strong performance,reinforcing the practical value of this method.Our approach offers a practical solution for enhancing energy efficiency in buildings by providing more precise segmentation results.
文摘Traditional Chinese architecture in the narrative of a system has existed more than 3,000 years. As the core values of the enlightenment function of social ethics, traditional architecture externalizes symbol of ＂state＂ sensual ethical echo. So metaphorical rules in architecture can combine with the normal life. Traditional architectural form as famous communication home Marshall McLuhan＇s ＂human extension＂, leads the order and the rules in the form of elevation. The spread of universal ethics, traditional architectural symmetry axis ceremony, and the adornment of the mythical thinking component, are traditional Chinese ethics of society to describe the core of creation through three points sequence structure constraint. The wisdom of metaphor in these ideas is the life gene of Chinese culture. In the construction of the contemporary social upheaval spreading vision, recognition of traditional architecture ethics through righteousness obviously has been recasting social ethics of ＂treatment＂.
