A5010997711- 3D Surveying and Cultural Heritage
- Topology Optimization in Engineering
- Design Education and Practice
- Generative Adversarial Networks and Image Synthesis
- Solar Radiation and Photovoltaics
- Structural Health Monitoring Techniques
- Aesthetic Perception and Analysis
- Building Energy and Comfort Optimization
- Composite Structure Analysis and Optimization
- AI and Multimedia in Education
- Infrastructure Maintenance and Monitoring
- Advanced Multi-Objective Optimization Algorithms
- Remote Sensing and LiDAR Applications
- Digital Media Forensic Detection
- BIM and Construction Integration
- Energy Load and Power Forecasting
- Wind and Air Flow Studies
- Advanced Vision and Imaging
- Architecture and Computational Design
- Metaheuristic Optimization Algorithms Research
- Image Processing Techniques and Applications
Harbin Institute of Technology
2021-2025
Ministry of Industry and Information Technology
2021-2025
Ministry of Education of the People's Republic of China
2021-2022
Artificial intelligence (AI) provides advanced mathematical frameworks and algorithms for further innovation vitality of classical civil engineering (CE). Plenty complex, time-consuming, laborious workloads design, construction, inspection can be enhanced upgraded by emerging AI techniques. In addition, many unsolved issues unknown laws in the field CE addressed discovered physical machine learning via merging data paradigm with laws. Intelligent science technology profoundly promote current...
Abstract This study develops an autonomous design method for architectural shape sketches by a novel self‐sparse generative adversarial network (self‐sparse GAN), thereby overcoming the problems regarding excessive reliance on sufficient aesthetic knowledge and time consumption in traditional human design. First, new dataset denoted “Sketch” is built using eXtended difference‐of‐Gaussians operator. Second, self‐adaptive sparse transform module (SASTM) designed following each deconvolution...
In the early stages of architectural design, architects convert initial ideas into concrete design schemes, which heavily rely on their creativity and consume considerable time. Therefore, generative methods based artificial intelligence are promising for such tasks. However, effectively communicating concepts to machines is challenging. To address this challenge, paper proposes a novel cross-model approach using textual descriptions assist architects, comprising concept extraction module an...
Abstract Topology optimization aims to find an economic and efficient structure with a lighter overall weight. description functions (TDFs), which are explicit level‐set approach for topology optimization, can obtain the geometry function of topology. However, due original hard thresholding in conventional TDF, TDF is derivative‐free method that requires significant computational resources, creates barriers its widespread adoption among structural engineers. To fix this problem, novel...
Generative adversarial networks (GANs) are an unsupervised generative model that learns data distribution through training. However, recent experiments indicated GANs difficult to train due the requirement of optimization in high dimensional parameter space and zero gradient problem. In this work, we propose a self-sparse network (Self-Sparse GAN) reduces alleviates Self-Sparse GAN, design self-adaptive sparse transform module (SASTM) comprising sparsity decomposition feature-map...