DEEP LEARNING APPROACHES FOR DAMAGE DETECTION IN E-COMMERCE PACKAGING
Abstract & Details
Research Area
Computer Science & Engineering
Keywords
Damage detection
deep learning
e-commerce logistics
packaging integrity
convolutional neural network
YOLO
Faster R-CNN
image classification
last-mile delivery
Abstract
With the rapid growth of e-commerce, ensuring the quality and safety of packages during transit has become a major concern for online retailers and logistics providers. Damaged goods result in dissatisfied customers, increased return rates, and significant economic losses. Manual inspection is labor-intensive and largely inefficient. To address this challenge, this research explores the application of deep learning techniques for automated damage detection in e-commerce packaging. Using convolutional neural networks (CNN) and object detection frameworks such as YOLOv5 and Faster R-CNN, this study demonstrates a robust system that identifies and classifies damage types (e.g., dents, tears, punctures) in real-time from images captured during last-mile deliveries. The system achieved over 94% accuracy in damage detection and significantly reduced inspection time and human error.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Lokesh Kakkar | Bhagwant University, Ajmer |
| 2 | Prof.(Dr.) V. K. Sharma | Bhagwant University, Ajmer |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Kakkar, Lokesh & Sharma, Prof.(Dr.) V. K. (2025). DEEP LEARNING APPROACHES FOR DAMAGE DETECTION IN E-COMMERCE PACKAGING. International Journal of Advance Research and Innovative Ideas In Education, 11(2), 2698-2702.
MLA Style
Kakkar, Lokesh, and Prof.(Dr.) V. K. Sharma. "DEEP LEARNING APPROACHES FOR DAMAGE DETECTION IN E-COMMERCE PACKAGING." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, 2025, pp. 2698-2702.
IEEE Style
Lokesh Kakkar and Prof.(Dr.) V. K. Sharma, "DEEP LEARNING APPROACHES FOR DAMAGE DETECTION IN E-COMMERCE PACKAGING," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, pp. 2698-2702, 2025.
Vancouver Style
Kakkar Lokesh, Sharma Prof.(Dr.) V. K.. DEEP LEARNING APPROACHES FOR DAMAGE DETECTION IN E-COMMERCE PACKAGING. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(2):2698-2702.
Harvard Style
Kakkar, Lokesh & Sharma, Prof.(Dr.) V. K. (2025) 'DEEP LEARNING APPROACHES FOR DAMAGE DETECTION IN E-COMMERCE PACKAGING', International Journal of Advance Research and Innovative Ideas In Education, 11(2), pp. 2698-2702.
Chicago Style
Kakkar, Lokesh and Prof.(Dr.) V. K. Sharma. "DEEP LEARNING APPROACHES FOR DAMAGE DETECTION IN E-COMMERCE PACKAGING." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 2698-2702.
Turabian Style
Kakkar, Lokesh and Prof.(Dr.) V. K. Sharma. "DEEP LEARNING APPROACHES FOR DAMAGE DETECTION IN E-COMMERCE PACKAGING." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 2698-2702.
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