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An Intelligent Image Segmentation Annotation Method Based on Segment Anything Model
Training of supervised neural network models requires a large amount of high-quality datasets with true values. In computer vision tasks such as...
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An efficient weakly semi-supervised method for object automated annotation
Object annotation is essential for computer vision tasks, and more high-quality annotated data can effectively improve the performance of vision...
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Interactive object annotation based on one-click guidance
Due to the large workload of manual annotation of datasets, uneven data quality and high professional thresholds have been a problem. Based on the...
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Annotation of scientific uncertainty using linguistic patterns
Scientific uncertainty is an integral part of the research process and inherent to the construction of new knowledge. In this paper, we investigate...
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Why do students reply? Uncovering the socio-semantic entanglement in web annotation activities
Web annotation environments are widely used in education based on the premise that student interaction in these environments benefits individual and...
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A Diverse Environment Coal Gangue Image Segmentation Model Combining Improved U-Net and Semi-supervised Automatic Annotation
The problem of uneven illumination in the coal gangue image and the existence of fine coal gangue reduces the accuracy of the coal gangue location,...
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Efficient Annotation and Learning for 3D Hand Pose Estimation: A Survey
In this survey, we present a systematic review of 3D hand pose estimation from the perspective of efficient annotation and learning. 3D hand pose...
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Central Attention with Multi-Graphs for Image Annotation
In recent decades, the development of multimedia and computer vision has sparked significant interest among researchers in the field of automatic...
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Investigating annotation noise for named entity recognition
Recent studies revealed that even the most widely used benchmark dataset still contains more than 5% sample-level annotation noise in Named Entity...
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APRE: Annotation-Aware Prompt-Tuning for Relation Extraction
Prompt-tuning has been successfully applied to support classification tasks in natural language processing and has achieved promising performance....
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A novel entity joint annotation relation extraction model
The social network is an indispensable part of our life. Text is the most common carrier in social networks. Extracting entities and relationships...
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Partial Image Active Annotation (PIAA): An Efficient Active Learning Technique Using Edge Information in Limited Data Scenarios
Active learning (AL) algorithms are increasingly being used to train models with limited data for annotation tasks. However, the selection of data...
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Semi-automatic Annotation for Mentions in Hindi Text
Annotated corpora are required for the development of modern, accurate, and robust techniques for Natural Language Processing (NLP) downstream...
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Ant: a process aware annotation software for regulatory compliance
Accurate data annotation is essential to successfully implementing machine learning (ML) for regulatory compliance. Annotations allow organizations...
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Improving loss function for deep convolutional neural network applied in automatic image annotation
Automatic image annotation (AIA) is a mechanism for describing the visual content of an image with a list of semantic labels. Typically, there is a...
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Identifying temporal changes in student engagement in social annotation during online collaborative reading
Social annotation plays a crucial role in nurturing and sustaining a collaborative reading community, offering the potential to enhance students’...
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Radiological Medical Imaging Annotation and Visualization Tool
Significant medical image visualization and annotation tools, tailored for clinical users, play a crucial role in disease diagnosis and treatment....
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Automatic Bharatanatyam Dance Video Annotation Tool Using CNN
Dance video analysis and interpretation have been challenging tasks in computer vision due to the lack of availability of annotated data. We may get...
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Reducing Human Annotation Effort Using Self-supervised Learning for Image Segmentation
Image segmentation stands out as one of the most computationally demanding computer vision tasks, posing challenges not only due to the substantial...
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Part-of-Speech and Sequence Annotation
This chapter describes a selection of neural network architectures to annotate the words of a text with their part of speech. Starting from...