Sakeena,
Rashika,
Saanihaa Mariyam,
Shireen,
- Assistant Professor, Department of Computer Science and Engineering, P A College of Engineering, Mangalore, Karnataka, India
- Student, Department of Computer Science and Engineering, P A College of Engineering, Mangalore, Karnataka, India
- Student, Department of Computer Science and Engineering, P A College of Engineering, Mangalore, Karnataka, India
- Student, Department of Computer Science and Engineering, P A College of Engineering, Mangalore, Karnataka, India
Abstract
In contemporary pharmaceutical production, the persistent challenges of manual labor, human error, and contamination risks pose significant obstacles to efficiency and product quality. Particularly in sectors such as Ayurvedic products, cosmetics, and medicines, the need for innovation is pressing. Revolution in production process can be addressed by introducing innovative solutions and thereby challenges could be overcome. Through the utilization of advanced technology, the proposed system streamlines sample management and quality control procedures, offering a timely response to the industry’s most pressing concerns. With a focus on Real-time Recognition & Classification and Quality Checking, the system ensures precise identification and labeling of samples while detecting anomalies to uphold stringent quality standards. By automating critical processes, the system minimizes labor costs, increases accuracy, and ultimately enhances overall efficiency and customer satisfaction. This project represents a crucial step forward in pharmaceutical production, promising increased reliability and regulatory compliance in an ever-evolving industry landscape.
Keywords: Convolutional neural network, Deep learning, Machine learning, Classification, Regression, Pharmaceutical Industry.
Sakeena, Rashika, Saanihaa Mariyam, Shireen. Flora-Vision: A Quality Assurance System For The Pharmaceutical Industry. Research & Reviews: A Journal of Pharmaceutical Science. 2024; ():-.
Sakeena, Rashika, Saanihaa Mariyam, Shireen. Flora-Vision: A Quality Assurance System For The Pharmaceutical Industry. Research & Reviews: A Journal of Pharmaceutical Science. 2024; ():-. Available from: https://journals.stmjournals.com/rrjops/article=2024/view=176167
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Research & Reviews: A Journal of Pharmaceutical Science
| Volume | |
| Received | August 24, 2024 |
| Accepted | September 23, 2024 |
| Published | September 28, 2024 |