Zhang et al., 2024 - Google Patents
Context-aware adaptive weighted attention network for real-time surface defect segmentationZhang et al., 2024
- Document ID
- 11822528158624126417
- Author
- Zhang G
- Lu Y
- Jiang X
- Yan F
- Xu M
- Publication year
- Publication venue
- IEEE Transactions on Instrumentation and Measurement
External Links
Snippet
Surface defect detection is an important step in ensuring product quality in various manufacturing industries. Existing methods have achieved significant results, but there are still challenges, such as the lack of real-time detection speed, low contrast between defects …
- 230000007547 defect 0 title abstract description 137
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
- G06K9/4609—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections by matching or filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4642—Extraction of features or characteristics of the image by performing operations within image blocks or by using histograms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
- G06K9/32—Aligning or centering of the image pick-up or image-field
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Liu et al. | A rail surface defect detection method based on pyramid feature and lightweight convolutional neural network | |
Zhang et al. | An efficient lightweight convolutional neural network for industrial surface defect detection | |
Tao et al. | Industrial weak scratches inspection based on multifeature fusion network | |
Xiang et al. | Semi-supervised learning framework for crack segmentation based on contrastive learning and cross pseudo supervision | |
Chu et al. | Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network | |
Wang et al. | A lightweight crack segmentation network based on knowledge distillation | |
Ma et al. | A hierarchical attention detector for bearing surface defect detection | |
Gao et al. | A detection network for small defects of steel surface based on YOLOv7 | |
Xu et al. | Multiple guidance network for industrial product surface inspection with one labeled target sample | |
Zhang et al. | Research on Surface Defect Detection of Rare‐Earth Magnetic Materials Based on Improved SSD | |
IZUMI et al. | Low-cost training data creation for crack detection using an attention mechanism in deep learning models | |
Lv et al. | LAACNet: Lightweight adaptive activation convolution network-based defect detection on polished metal surfaces | |
Zhang et al. | Context-Aware Adaptive Weighted Attention Network for Real-Time Surface Defect Segmentation | |
Lu et al. | Lightweight strip steel defect detection algorithm based on improved YOLOv7 | |
Li et al. | IDP-Net: Industrial defect perception network based on cross-layer semantic information guidance and context concentration enhancement | |
Gong et al. | Few-shot defect detection using feature enhancement and image generation for manufacturing quality inspection | |
Wang et al. | Surface defect detection method for electronic panels based on attention mechanism and dual detection heads | |
Li et al. | YOLOv5s‐GC‐Based Surface Defect Detection Method of Strip Steel | |
Peng et al. | High-Precision Surface Crack Detection for Rolling Steel Production Equipment in ICPS | |
He et al. | AEGLR-Net: Attention enhanced global–local refined network for accurate detection of car body surface defects | |
Xiang et al. | An Industrial Defect Detection Network with Fine-Grained Supervision and Adaptive Contrast Enhancement | |
Poxi et al. | Bushing Surface Defect Detection Method Based on Improved YOLOX | |
Wan et al. | AENet: attention enhancement network for industrial defect detection in complex and sensitive scenarios | |
Zhu et al. | An Improved Feature Enhancement CenterNet Model for Small Object Defect Detection on Metal Surfaces | |
Xi-Xing et al. | A YOLOv5s-GC-based surface defect detection method of strip steel |