vicoslab/segdec-net-plusplus-conbuildmat2023
SegDecNet++: an official PyTorch implementation for "Automated detection and segmentation of cracks in concrete surfaces using joined segmentation and classification deep neural network" paper
This helps civil engineers, construction managers, or quality inspectors automatically identify and map cracks in concrete surfaces. You input digital images of concrete, and it outputs segmented images highlighting the exact location and extent of cracks. This allows for efficient assessment of infrastructure integrity without manual, time-consuming inspections.
No commits in the last 6 months.
Use this if you need an automated, precise way to detect and segment cracks in concrete from digital images for structural assessment or maintenance planning.
Not ideal if you need to analyze cracks in materials other than concrete, or if you require on-site, real-time detection without image processing.
Stars
17
Forks
3
Language
Python
License
—
Category
Last pushed
Oct 02, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/vicoslab/segdec-net-plusplus-conbuildmat2023"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Karl1109/SCSegamba
[CVPR 2025] SCSegamba: Lightweight Structure-Aware Vision Mamba for Crack Segmentation in Structures
Yuki-11/CSSR
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-Resolution (CSSR)...
mo26-web/Surface-Crack-Detection-with-DL
This is a Surface Crack Detection project implemented with the Tensorflow. We fine tuning some...
ak2502/crack-detection
A crack detection system which detects percentage of cracks on the road and warns about the...
MachineLearningVisionRG/mcs-dataset
Marble Crack Segmentation (MCS) Dataset for semantic segmentation on marble images.