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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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 211–220 of 359 papers

Title	Date	Tasks	Status	Hype
FinSBD-2020: The 2nd Shared Task on Sentence Boundary Detection in Unstructured Text in the Financial Domain	Jan 1, 2020	Boundary DetectionSentence	—Unverified	0
aiai at the FinSBD-2 Task: Sentence, list and Item Boundary Detection and Items classification of Financial Texts Using Data Augmentation and Attention	Jan 1, 2020	Boundary DetectionData Augmentation	—Unverified	0
A Region-based Randers Geodesic Approach for Image Segmentation	Dec 20, 2019	Boundary DetectionImage Segmentation	—Unverified	0
RED-NET: A Recursive Encoder-Decoder Network for Edge Detection	Dec 5, 2019	Boundary DetectionDecoder	—Unverified	0
HAMNER: Headword Amplified Multi-span Distantly Supervised Method for Domain Specific Named Entity Recognition	Dec 3, 2019	Boundary Detectionnamed-entity-recognition	—Unverified	0
A novel automatic shot boundary detection algorithm: robust to illumination and motion effect	Nov 10, 2019	Boundary DetectionCamera shot boundary detection	CodeCode Available	0
Controlling Utterance Length in NMT-based Word Segmentation with Attention	Oct 18, 2019	Boundary DetectionMachine Translation	—Unverified	0
Combining Geometric and Topological Information for Boundary Estimation	Oct 10, 2019	Boundary DetectionClustering	CodeCode Available	0
High-Frequency guided Curriculum Learning for Class-specific Object Boundary Detection	Sep 25, 2019	Boundary DetectionObject	—Unverified	0
V1Net: A computational model of cortical horizontal connections	Sep 25, 2019	Boundary Detectionmodel	—Unverified	0

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All datasets RoFT RoFT-chatgpt CoAuthor NYU-Depth V2 TriBERT (in-domain)UruDendro Kinetics 400 PASCAL Context

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	GigaCheck (DN-DAB-DETR)	Accuracy (%)	64.63	—	Unverified
2	RoBERTa + SEP	Accuracy (%)	49.64	—	Unverified
3	PHD + TS ML	Accuracy (%)	23.5	—	Unverified
4	TLE + TS Binary	Accuracy (%)	12.58	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GigaCheck (DN-DAB-DETR)	Accuracy (%)	67.65	—	Unverified
2	RoBERTa + SEP	Accuracy (%)	54.61	—	Unverified
3	TLE + TS Binary	Accuracy (%)	20.02	—	Unverified
4	PHD + TS ML	Accuracy (%)	17.29	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GigaCheck (Mistral-7B-v0.3)	Cohen’s Kappa score	0.42	—	Unverified
2	DeBERTa-v3 (Naive)	Cohen’s Kappa score	0.4	—	Unverified
3	GigaCheck (DN-DAB-DETR)	Cohen’s Kappa score	0.19	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InvPT	odsF	78.1	—	Unverified
2	PGT (Swin-S)	odsF	78.04	—	Unverified
3	PGT (Swin-T)	odsF	77.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GigaCheck (DN-DAB-DETR)	F1@3	0.65	—	Unverified
2	TriBERT (p=2)	F1@3	0.58	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CS-TRD	Average Precision	0.94	—	Unverified
2	INBD	Average Precision	0.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CASTANET+ Ensemble	Pairwise F1	0.81	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InvPT	odsF	73	—	Unverified