[HTML][HTML] Improving Sewer Damage Inspection: Development of a Deep Learning Integration Concept for a Multi-Sensor System
JT Jung, A Reiterer - Sensors, 2024 - mdpi.com
The maintenance and inspection of sewer pipes are essential to urban infrastructure but
remain predominantly manual, resource-intensive, and prone to human error …
remain predominantly manual, resource-intensive, and prone to human error …
Automated detection and segmentation of cracks in concrete surfaces using joined segmentation and classification deep neural network
Automated quality control of pavement and concrete surfaces is essential for maintaining
structural integrity and consistency in the construction and infrastructure industries. This …
structural integrity and consistency in the construction and infrastructure industries. This …
An efficient wastewater collection model for groundwater resource protection in smart cities
Efficient wastewater collection is a critical concern in the development of smart cities, where
sustainable urban infrastructure is paramount. In the context of smart city wastewater …
sustainable urban infrastructure is paramount. In the context of smart city wastewater …
[HTML][HTML] Co-CrackSegment: a new collaborative deep learning framework for pixel-level semantic segmentation of concrete cracks
In an era of massive construction, damaged and aging infrastructure are becoming more
common. Defects, such as cracking, spalling, etc., are main types of structural damage that …
common. Defects, such as cracking, spalling, etc., are main types of structural damage that …
CDD-TR: Automated concrete defect investigation using an improved deformable transformers
Public infrastructures, such as bridges, dams, and buildings, play a key role in urban
development. Structural inspection by visually monitoring and inspecting the structures for …
development. Structural inspection by visually monitoring and inspecting the structures for …
Classification of sewer pipe defects based on an automatically designed convolutional neural network
Y Wang, J Fan, Y Sun - Expert Systems with Applications, 2025 - Elsevier
Accurate classification of sewer pipe defects allows for timely prevention of system failures,
preventing environmental pollution caused by sewage leakage, thereby safeguarding public …
preventing environmental pollution caused by sewage leakage, thereby safeguarding public …
PipeTransUNet: CNN and Transformer fusion network for semantic segmentation and severity quantification of multiple sewer pipe defects
With the continuous development of urbanization, the service life of sewer pipes is gradually
approaching a critical threshold. Defects within pipe networks can significantly affect the …
approaching a critical threshold. Defects within pipe networks can significantly affect the …
Semi‐supervised pipe video temporal defect interval localization
In sewer pipe closed‐circuit television inspection, accurate temporal defect localization is
essential for effective pipe assessment. Industry standards typically do not require time …
essential for effective pipe assessment. Industry standards typically do not require time …
A lightweight multi scale fusion network for IGBT ultrasonic tomography image segmentation
M Song, Z Wang, Y Chen, Y Li, Y **, B Jia - Scientific Reports, 2025 - nature.com
Abstract The Insulated Gate Bipolar Transistor (IGBT) is a crucial power semiconductor
device, and the integrity of its internal structure directly influences both its electrical …
device, and the integrity of its internal structure directly influences both its electrical …
Deep learning, geometric characterization and hydrodynamic modeling for assessing sewer defect impacts on urban flooding: A case study in Guangzhou, China
Q Zhou, Z Situ, W Feng, H Liu, X Liao, J Zhang… - Journal of …, 2024 - Elsevier
Deep learning techniques have offered innovative and efficient tools for accurate and
automated detection of sewer defects by leveraging large-scale sewer data and advanced …
automated detection of sewer defects by leveraging large-scale sewer data and advanced …