SOTAVerified

Edge Detection

Edge Detection is a fundamental image processing technique which involves computing an image gradient to quantify the magnitude and direction of edges in an image. Image gradients are used in various downstream tasks in computer vision such as line detection, feature detection, and image classification.

Source: Artistic Enhancement and Style Transfer of Image Edges using Directional Pseudo-coloring

( Image credit: Kornia )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–450 of 490 papers

TitleStatusHype
A Systematic Approach for MRI Brain Tumor Localization, and Segmentation using Deep Learning and Active Contouring—0
A Trio-Method for Retinal Vessel Segmentation using Image Processing—0
Automated Management of Pothole related Disasters Using Image Processing and Geotagging—0
Automated Quantification of White Blood Cells in Light Microscopic Images of Injured Skeletal Muscle—0
Automatic Detection and Rectification of Paper Receipts on Smartphones—0
Automating Attendance Management in Human Resources: A Design Science Approach Using Computer Vision and Facial Recognition—0
A Watermarking Technique Using Discrete Curvelet Transform for Security of Multiple Biometric Features—0
Beyond Camera Motion Blur Removing: How to Handle Outliers in Deblurring—0
Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields—0
Bioacoustical Periodic Pulse Train Signal Detection and Classification using Spectrogram Intensity Binarization and Energy Projection—0
Biomolecular Event Extraction using a Stacked Generalization based Classifier—0
BoundED: Neural Boundary and Edge Detection in 3D Point Clouds via Local Neighborhood Statistics—0
Cable Slack Detection for Arresting Gear Application using Machine Vision—0
CAFENet: Class-Agnostic Few-Shot Edge Detection Network—0
Can Shape Structure Features Improve Model Robustness Under Diverse Adversarial Settings?—0
CDSE-UNet: Enhancing COVID-19 CT Image Segmentation with Canny Edge Detection and Dual-Path SENet Feature Fusion—0
CFAR Edge Detector for Polarimetric SAR Images—0
Classic versus deep learning approaches to address computer vision challenges—0
Clutter Edges Detection Algorithms for Structured Clutter Covariance Matrices—0
CMR motion artifact correction using generative adversarial nets—0
Color Image Edge Detection using Multi-scale and Multi-directional Gabor filter—0
Color Recognition in Challenging Lighting Environments: CNN Approach—0
Combining Deep Learning and Mathematical Morphology for Historical Map Segmentation—0
Comparative analysis of common edge detection techniques in context of object extraction—0
Comparative Study Of Image Edge Detection Algorithms—0
Comparing Edge Detection Methods based on Stochastic Entropies and Distances for PolSAR Imagery—0
Compressed ghost edge imaging—0
Computing the Spatial Probability of Inclusion inside Partial Contours for Computer Vision Applications—0
Content Based Image Indexing and Retrieval—0
Context-Aware Image Denoising with Auto-Threshold Canny Edge Detection to Suppress Adversarial Perturbation—0
Context-Constrained Accurate Contour Extraction for Occlusion Edge Detection—0
Contour Detection in Cassini ISS images based on Hierarchical Extreme Learning Machine and Dense Conditional Random Field—0
Contour Detection in Unstructured 3D Point Clouds—0
Contour Detection Using Contrast Formulas in the Framework of Logarithmic Models—0
Convex Analysis of Mixtures for Separating Non-negative Well-grounded Sources—0
Coupled Segmentation and Edge Learning via Dynamic Graph Propagation—0
CRAFT: A multifunction online platform for speech prosody visualisation—0
Cross-Domain Evaluation of Edge Detection for Biomedical Event Extraction—0
Custom Extended Sobel Filters—0
Cutting-Edge Detection of Fatigue in Drivers: A Comparative Study of Object Detection Models—0
Cycle Pixel Difference Network for Crisp Edge Detection—0
DADU: Dual Attention-based Deep Supervised UNet for Automated Semantic Segmentation of Cardiac Images—0
Dam Burst: A region-merging-based image segmentation method—0
DCSM 2.0: Deep Conditional Shape Models for Data Efficient Segmentation—0
Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing—0
Deep Crisp Boundaries—0
Deep Crisp Boundaries: From Boundaries to Higher-level Tasks—0
Deep Learning-Based Automatic Delineation of Liver Domes in kV Triggered Images for Online Breath-hold Reproducibility Verification of Liver Stereotactic Body Radiation Therapy—0
Deep Learning for Low-Dose CT Denoising—0
Defective Edge Detection Using Cascaded Ensemble Canny Operator—0
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All datasetsBIPEDMDBDUDEDBRINDCIDCityscapes testSBDBSDS500

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DDNODS0.92—Unverified
2DexiNedODS0.9—Unverified
3BDCNODS0.89—Unverified
4LDCODS0.89—Unverified
5CATSODS0.89—Unverified
6RCFODS0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1DexiNed-aODS0.89—Unverified
2DexiNed-fODS0.89—Unverified
3CATSODS0.89—Unverified
4BDCNODS0.89—Unverified
5LDCODS0.88—Unverified
6RCFODS0.88—Unverified
#ModelMetricClaimedVerifiedStatus
1DDNODS0.83—Unverified
2TEEDODS0.83—Unverified
3LDCODS0.82—Unverified
4DexiNedODS0.82—Unverified
5PiDiNetODS0.81—Unverified
#ModelMetricClaimedVerifiedStatus
1LDCODS0.79—Unverified
2PiDiNetODS0.79—Unverified
3BDCNODS0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1SEDODS0.65—Unverified
2DexiNed (WACV'2020)ODS0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1RPCNetAP86.15—Unverified
2CASENetAP70.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CASENetMaximum F-measure71.4—Unverified
2WSOBMaximum F-measure52—Unverified
#ModelMetricClaimedVerifiedStatus
1RCNF10.82—Unverified