Results 251 to 260 of about 479,142 (270)

Full-scale indexing and semantic annotation of CT imaging: boosting FAIRness. [PDF]

BMC Med Inform Decis Mak
Ulrich H, Hendel R, Bergh B, Schreiweis B.   +3 more
europepmc   +1 more source

Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations

Annual Meeting of the Association for Computational Linguistics, 2023
In this paper, we present an innovative process-oriented math process reward model called \textbf{Math-Shepherd}, which assigns a reward score to each step of math problem solutions.
Peiyi Wang, Lei Li, Zhihong Shao, R. Xu, Damai Dai, Yifei Li, Deli Chen, Y.Wu, Zhifang Sui   +8 more
semanticscholar   +1 more source

Contrastive learning of global and local features for medical image segmentation with limited annotations

Neural Information Processing Systems, 2020
A key requirement for the success of supervised deep learning is a large labeled dataset - a condition that is difficult to meet in medical image analysis.
K. Chaitanya, Ertunç Erdil, Neerav Karani, E. Konukoglu   +3 more
semanticscholar   +1 more source

CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotations

European Conference on Computer Vision, 2020
As facial interaction systems are prevalently deployed, security and reliability of these systems become a critical issue, with substantial research efforts devoted.
Yuanhan Zhang, Zhen-fei Yin, Yidong Li, Guojun Yin, Junjie Yan, Jing Shao, Ziwei Liu   +6 more
semanticscholar   +1 more source

Can Unconfident LLM Annotations Be Used for Confident Conclusions?

North American Chapter of the Association for Computational Linguistics
Large language models (LLMs) have shown high agreement with human raters across a variety of tasks, demonstrating potential to ease the challenges of human data collection.
Kristina Gligori'c, Tijana Zrnic, Cinoo Lee, Emmanuel J. Candès, Dan Jurafsky   +4 more
semanticscholar   +1 more source

Learning Visual Representations with Caption Annotations

European Conference on Computer Vision, 2020
Pretraining general-purpose visual features has become a crucial part of tackling many computer vision tasks. While one can learn such features on the extensively-annotated ImageNet dataset, recent approaches have looked at ways to allow for noisy, fewer,
Mert Bulent Sariyildiz, J. Perez, Diane Larlus   +2 more
semanticscholar   +1 more source

Augmenting the National Institutes of Health Chest Radiograph Dataset with Expert Annotations of Possible Pneumonia.

Radiology: Artificial Intelligence, 2019
This dataset is intended to be used for machine learning and is composed of annotations with bounding boxes for pulmonary opacity on chest radiographs which may represent pneumonia in the appropriate clinical setting.
G. Shih, Carol C. Wu, S. Halabi, M. Kohli, L. Prevedello, T. Cook, Arjun Sharma, J. Amorosa, V. Arteaga, M. Galperin-Aizenberg, R. Gill, M. Godoy, Stephen Hobbs, J. Jeudy, Archana T. Laroia, P. Shah, D. Vummidi, K. Yaddanapudi, A. Stein   +18 more
semanticscholar   +1 more source

Annotation: Trichotillomania

Journal of Child Psychology and Psychiatry, 1991
In spite of intriguing new information about trichotillomania, the most basic information about its prevalence, natural history, and treatment is lacking. While there is evidence that trichotillomania is more common than expected, epidemiological data are needed to establish the true frequency and pattern of associated disorders, and cross-cultural ...
S E, Swedo, J L, Rapoport
openaire   +2 more sources