Authors :
Arsalan Zahid
Volume/Issue :
Volume 9 - 2024, Issue 2 - February
Google Scholar :
http://tinyurl.com/4wcxseep
Scribd :
http://tinyurl.com/4kydyu4w
DOI :
https://doi.org/10.5281/zenodo.10673266
Abstract :
The inspection of pharmaceutical products,
especially pills, has become an essential process in the
pharmaceutical industry to ensure the quality and safety
of medication. The traditional inspection methods are
time-consuming and prone to errors. The use of deep
learning models such as YOLOv5 has shown promising
results in detecting and classifying pills accurately.
YOLOv5 is a state-of-the-art object detection model that
provides faster and more efficient processing of images
with high accuracy rates. In this abstract, we review the
recent studies on pill inspection using YOLOv5. We
discuss the key features of YOLOv5 that make it suitable
for pill inspection and the challenges associated with this
task. We also highlight the potential benefits of using
YOLOv5 for pill inspection, including improved
accuracy, speed, and cost-effectiveness. Overall, the
application of YOLOv5 in pill inspection can help ensure
the authenticity and integrity of pharmaceutical products,
providing a valuable tool for quality control in the
pharmaceutical industry. The MAP @ 0.5 obtained was 1
after 25-27 epochs.
Keywords :
Defect Detection; Micro-cracks; Photovoltaics; Smart Manufacturing; Quality Inspection.
The inspection of pharmaceutical products,
especially pills, has become an essential process in the
pharmaceutical industry to ensure the quality and safety
of medication. The traditional inspection methods are
time-consuming and prone to errors. The use of deep
learning models such as YOLOv5 has shown promising
results in detecting and classifying pills accurately.
YOLOv5 is a state-of-the-art object detection model that
provides faster and more efficient processing of images
with high accuracy rates. In this abstract, we review the
recent studies on pill inspection using YOLOv5. We
discuss the key features of YOLOv5 that make it suitable
for pill inspection and the challenges associated with this
task. We also highlight the potential benefits of using
YOLOv5 for pill inspection, including improved
accuracy, speed, and cost-effectiveness. Overall, the
application of YOLOv5 in pill inspection can help ensure
the authenticity and integrity of pharmaceutical products,
providing a valuable tool for quality control in the
pharmaceutical industry. The MAP @ 0.5 obtained was 1
after 25-27 epochs.
Keywords :
Defect Detection; Micro-cracks; Photovoltaics; Smart Manufacturing; Quality Inspection.
