SOTAVerified

Boundary Detection

Boundary Detection is a vital part of extracting information encoded in images, allowing for the computation of quantities of interest including density, velocity, pressure, etc.

Source: A Locally Adapting Technique for Boundary Detection using Image Segmentation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–275 of 359 papers

TitleStatusHype
Automatic lesion boundary detection in dermoscopy—0
Video searching and fingerprint detection by using the image query and PlaceNet-based shot boundary detection method—0
Geometric Constrained Joint Lane Segmentation and Lane Boundary Detection—0
Using Semantics for Granularities of Tokenization—0
WiSeBE: Window-based Sentence Boundary EvaluationCode0
DOOBNet: Deep Object Occlusion Boundary Detection from an ImageCode0
A Divide-and-Conquer Approach to Geometric Sampling for Active Learning—0
Linear-Time Constituency Parsing with RNNs and Dynamic Programming—0
Moving TIGER beyond Sentence-Level—0
D\'etection automatique de phrases en domaine de sp\'ecialit\'e en fran (Sentence boundary detection for specialized domains in French )—0
Deep Motion Boundary Detection—0
Sentence Boundary Detection for French with Subword-Level Information Vectors and Convolutional Neural Networks—0
Automated image segmentation for detecting cell spreading for metastasizing assessments of cancer development—0
Recurrent Pixel Embedding for Instance GroupingCode0
Coordination Boundary Identification with Similarity and Replaceability—0
Volumetric Data Exploration with Machine Learning-Aided Visualization in Neutron Science—0
Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts—0
Semantic Segmentation from Limited Training Data—0
APPD: Adaptive and Precise Pupil Boundary Detection using Entropy of Contour GradientsCode0
Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts—0
Combining Global Models for Parsing Universal Dependencies—0
A Locally Adapting Technique for Boundary Detection using Image Segmentation—0
The Devil is in the Decoder: Classification, Regression and GANsCode0
Ubernet: Training a Universal Convolutional Neural Network for Low-, Mid-, and High-Level Vision Using Diverse Datasets and Limited Memory—0
Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural NetworksCode0
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All datasetsRoFTRoFT-chatgptCoAuthorNYU-Depth V2TriBERT (in-domain)UruDendroKinetics 400PASCAL Context

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GigaCheck (DN-DAB-DETR)Accuracy (%)64.63—Unverified
2RoBERTa + SEPAccuracy (%)49.64—Unverified
3PHD + TS MLAccuracy (%)23.5—Unverified
4TLE + TS BinaryAccuracy (%)12.58—Unverified
#ModelMetricClaimedVerifiedStatus
1GigaCheck (DN-DAB-DETR)Accuracy (%)67.65—Unverified
2RoBERTa + SEPAccuracy (%)54.61—Unverified
3TLE + TS BinaryAccuracy (%)20.02—Unverified
4PHD + TS MLAccuracy (%)17.29—Unverified
#ModelMetricClaimedVerifiedStatus
1GigaCheck (Mistral-7B-v0.3)Cohen’s Kappa score0.42—Unverified
2DeBERTa-v3 (Naive)Cohen’s Kappa score0.4—Unverified
3GigaCheck (DN-DAB-DETR)Cohen’s Kappa score0.19—Unverified
#ModelMetricClaimedVerifiedStatus
1InvPTodsF78.1—Unverified
2PGT (Swin-S)odsF78.04—Unverified
3PGT (Swin-T)odsF77.05—Unverified
#ModelMetricClaimedVerifiedStatus
1GigaCheck (DN-DAB-DETR)F1@30.65—Unverified
2TriBERT (p=2)F1@30.58—Unverified
#ModelMetricClaimedVerifiedStatus
1CS-TRDAverage Precision0.94—Unverified
2INBDAverage Precision0.75—Unverified
#ModelMetricClaimedVerifiedStatus
1CASTANET+ EnsemblePairwise F10.81—Unverified
#ModelMetricClaimedVerifiedStatus
1InvPTodsF73—Unverified