Medicinal Boxes Recognition on a Deep Transfer Learning Augmented Reality Mobile Application

被引:6
|
作者
Avola, Danilo [1 ]
Cinque, Luigi [1 ]
Fagioli, Alessio [1 ]
Foresti, Gian Luca [2 ]
Marini, Marco Raoul [1 ]
Mecca, Alessio [1 ]
Pannone, Daniele [1 ]
机构
[1] Sapienza Univ, Rome, Italy
[2] Udine Univ, Udine, Italy
基金
欧洲研究理事会;
关键词
Convolutional neural network; Deep learning; Augmented reality;
D O I
10.1007/978-3-031-06427-2_41
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Taking medicines is a fundamental aspect to cure illnesses. However, studies have shown that it can be hard for patients to remember the correct posology. More aggravating, a wrong dosage generally causes the disease to worsen. Although, all relevant instructions for a medicine are summarized in the corresponding patient information leaflet, the latter is generally difficult to navigate and understand. To address this problem and help patients with their medication, in this paper we introduce an augmented reality mobile application that can present to the user important details on the framed medicine. In particular, the app implements an inference engine based on a deep neural network, i.e., a densenet, fine-tuned to recognize a medicinal from its package. Subsequently, relevant information, such as posology or a simplified leaflet, is overlaid on the camera feed to help a patient when taking a medicine. Extensive experiments to select the best hyperparameters were performed on a dataset specifically collected to address this task; ultimately obtaining up to 91.30% accuracy as well as real-time capabilities.
引用
收藏
页码:489 / 499
页数:11
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