| Technical Name | 基於RetinaNet與Inception-ResNet之自動多藥丸偵測與辨識系統 | ||
|---|---|---|---|
| Project Operator | Tajen University/National Cheng Kung University | ||
| Project Host | 王駿發 | ||
| Summary | The pills detection system is built based on the Feature Pyramid NetworkConvolution Normal Network (CNN). Two-stage CNN architecture is used for pills localizationpill classification. The accuracyexecution time of the pill detection are 900.02s, respectively. | ||
| Market Potential Analysis | 在市場需求部分，裸藥辨識系統主要用於居家長照與醫療院所之用藥安全應用上。在服藥前，讓使用者快速了解服藥內容，可以提升按時服藥的可能性並降低錯誤用藥的可能。在藥物與藥物間外觀相似度極高且易可能產生相斥或降低效用的可能。使用本系統可有效透過影像辨識快速檢索藥丸品項，且快速檢索交互作用的藥物資訊。另一方面，由於不用藥廠間相同藥物不存在統一規格在醫療院所裡，醫師往往因為不了解病患用藥狀況，造成藥品重複開立，或開立互相排斥的藥，大幅增加病患用藥的風險。裸藥辨識系統在醫療單位及居家長照的用藥上具備高度的市場需求潛力。 在裸藥辨識的市場佔有率上，目前裸藥辨識的發展中，本團隊使用卷積神經網路與特徵金字塔網路解決多藥定位以及隨機放置的困難挑戰。在用藥安全管理觀念日漸高漲之下，本技術渴望加速產品化的程度，使用快速及穩健的人工智慧影像辨識技術在裸藥辨識服務上快速搶得市場佔有率。 | ||
| Industrial Applicability | The pill detection can be applied to wide range of situations, such as home medicine safety, understand the unknown drug. Medical personnelpatients often have difficulties in distinguishing unpackaged pills. The improvement in medication knowledgethe provision of adequate pill information to patients have become important issues in an eff | ||
| Keyword | Pill Classification Pill Detection Pill Identification Pill Retrieval Pill Recognition Pill Search Pill Management Security of Family Medication Disposal of Pill Recycling Medical Assistance | ||
- rec122@tajen.edu.tw
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