• Rahul Khandelwal
• Alok Kumar Rastogi
• Vishal
• Varsha S.
• Madhavi R.P

Object detection, when applied to shelf images can solve many problems in retail stores such as observing the number of products on the shelves and comparing the organized products with the planogram continuously. However, resolving this issue is not simple. A computer, unlike the human eye, analyses pictures in two dimensions. Furthermore, the object's size, orientation, and placement in the picture might all be somewhat different. This study aims to simplify the detection of products in shelves by eliminating manual effort with assistance of deep learning algorithms.

object detection, planogram, machine learning, deep learning, SSD, YOLO, R-CNN, mAP%, FPS

"Survey Paper on Retail Store Object Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 6, page no.j1-j4, June-2023, Available :http://www.jetir.org/papers/JETIR2306901.pdf

"Survey Paper on Retail Store Object Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 6, page no. ppj1-j4, June-2023, Available at : http://www.jetir.org/papers/JETIR2306901.pdf