Journal Article10.1016/J.PATREC.2011.08.022
Pill-ID
TL;DR: In this paper, the authors used robust SIFT and MLBP descriptors to match drug pill images based on several features (i.e., imprint, color, and shape) of the tablet.
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About: This article is published in Pattern Recognition Letters. The article was published on 01 May 2012. The article focuses on the topics: Legal drug.
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Citations
Fast and accurate medication identification
Natalia Larios Delgado,Naoto Usuyama,Amanda K. Hall,Rebecca J Hazen,Max Ma,Siva Sahu,Jessica Lundin +6 more
- 28 Feb 2019
TL;DR: This work shows a deep-learning application that can help reduce avoidable errors with their attendant risk, i.e., correctly identifying prescription medication, which is currently a tedious and error-prone task.
A Drug Identification Model developed using Deep Learning Technologies: Experience of a Medical Center in Taiwan
TL;DR: A deep learning-based model for blister-packaged drug identification, with an accuracy greater than 90%.
Development of fine-grained pill identification algorithm using deep convolutional network
TL;DR: The superior performance of DCN underscores the potential of Deep Learning model in the application of pill identification and verification in the healthcare institutes.
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The national library of medicine pill image recognition challenge: An initial report
Ziv Yaniv,Jessica Faruque,Sally Howe,Kathel Dunn,David Sharlip,Andrew R. Bond,Pablo R. Perillan,Olivier Bodenreider,Michael J. Ackerman,Terry S. Yoo +9 more
- 01 Oct 2016
TL;DR: This challenge was motivated by the need to easily identify unknown prescription pills both by healthcare personnel and the general public, and an initial promising step towards development of an NLM software system and application-programming interface facilitating pill identification.
41
Few-Shot Pill Recognition
Suiyi Ling,Andreas Pastor,Jing Li,Zhaohui Che,Wang Junle,Jieun Kim,Patrick Le Callet +6 more
- 14 Jun 2020
TL;DR: A new pill image database is first developed with more varied imaging conditions and instances for each pill category, and a W2-net is proposed for better pill segmentation and the proposed model outperforms state-of-the-art models on both the National Institute of Health and the CURE database.
References
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
TL;DR: A generalized gray-scale and rotation invariant operator presentation that allows for detecting the "uniform" patterns for any quantization of the angular space and for any spatial resolution and presents a method for combining multiple operators for multiresolution analysis.
Visual pattern recognition by moment invariants
TL;DR: It is shown that recognition of geometrical patterns and alphabetical characters independently of position, size and orientation can be accomplished and it is indicated that generalization is possible to include invariance with parallel projection.
Score normalization in multimodal biometric systems
TL;DR: Study of the performance of different normalization techniques and fusion rules in the context of a multimodal biometric system based on the face, fingerprint and hand-geometry traits of a user found that the application of min-max, z-score, and tanh normalization schemes followed by a simple sum of scores fusion method results in better recognition performance compared to other methods.
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