LF-YOLO: A Lighter and Faster YOLO for Weld Defect Detection of X-Ray Image

Complex-YOLO: Real-time 3D Object Detection on Point Clouds

Lidar based 3D object detection is inevitable for autonomous driving, because it directly links to environmental understanding and therefore builds the base for prediction and motion planning. The capacity of inferencing highly sparse 3D data in real-time is an ill-posed problem for lots of other application areas besides automated vehicles, e.g. augmented reality, personal robotics or industri...

YOLo 84, No.lc8 JOURNAL OF GEOPHYSICAL RESEARCH

Image Semantic Transformation: Faster, Lighter and Stronger

We propose Image-Semantic-Transformation-ReconstructionCircle(ISTRC) model, a novel and powerful method using facenet’s Euclidean latent space to understand the images. As the name suggests, ISTRC construct the circle, able to perfectly reconstruct images. One powerful Euclidean latent space embedded in ISTRC is FaceNet’s last layer with the power of distinguishing and understanding images. Our...

Feature Extraction and Optimisation for X-ray Weld Image Classification

Computer aided image analysis systems for radiographic inspection (X-ray or gamma ray) are among the most commonly used Non-destructive Evaluation (NDE) methods. The accuracy of these systems is very much depending on the selected features which are extracted from weld defect images. In this paper, we firstly introduce a computer aided image analysis system for X-ray image inspection and evalua...

Weld defect detection in industrial radiography based digital image processing

Industrial radiography is a famous technique for the identification and evaluation of discontinuities, or defects, such as cracks, porosity and foreign inclusions found in welded joints. Although this technique has been well developed, improving both the inspection process and operating time, it does suffer from several drawbacks. The poor quality of radiographic images is due to the physical n...