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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
Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension	Apr 29, 2020	Boundary DetectionMachine Reading Comprehension	—Unverified	0
Joint Semantic Segmentation and Boundary Detection using Iterative Pyramid Contexts	Apr 16, 2020	Boundary DetectionEdge Detection	—Unverified	0
Integrating Boundary Assembling into a DNN Framework for Named Entity Recognition in Chinese Social Media Text	Feb 27, 2020	Boundary DetectionChinese Word Segmentation	—Unverified	0
Coronary Wall Segmentation in CCTA Scans via a Hybrid Net with Contours Regularization	Feb 27, 2020	Boundary Detection	—Unverified	0
Multi-Branch Learning for Weakly-Labeled Sound Event Detection	Feb 22, 2020	Audio TaggingBoundary Detection	—Unverified	0
Sequence Labeling Approach to the Task of Sentence Boundary Detection	Jan 20, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	0
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
Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck	Jan 1, 2020	Autonomous DrivingBoundary Detection	—Unverified	0
A Region-based Randers Geodesic Approach for Image Segmentation	Dec 20, 2019	Boundary DetectionImage Segmentation	—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