Latch-ocr Computer Vision Project
Updated 2 years ago
Here are a few use cases for this project:
-
Quality Control in Manufacturing: The Latch-ocr model can be used in a manufacturing setting where it can identify different alphanumeric codes stamped onto metal parts. This could assist in quality control, tracing products, recognizing product codes, and sorting items.
-
Automating Data Entry: The model could be used for automating the process of data entry by scanning and interpreting alphanumeric codes from metal objects, saving resources and improving accuracy.
-
Component Identification In Electronics: In electronic assembly or disassembly procedures, this model could identify and track metal parts labelled with OCR classes to ensure correct assembly or to identify specific pieces for replacement.
-
Theft Deterrence in Retail Stores: The model could be used in retail environments to identify Price or Product codes on metal items, particularly in shops selling hardware or electronic components. This can help prevent theft or misplacement of goods.
-
Historical Artifacts Analysis: Archaeologists and historians can use the model to identify and catalogue historical metal artifacts which may have alphanumeric engravings. This could provide important insights into the origin, date, and context of the artifact.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
latch-ocr-kkfmo_dataset,
title = { Latch-ocr Dataset },
type = { Open Source Dataset },
author = { GANESH JOSHI },
howpublished = { \url{ https://universe.roboflow.com/ganesh-joshi/latch-ocr-kkfmo } },
url = { https://universe.roboflow.com/ganesh-joshi/latch-ocr-kkfmo },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { dec },
note = { visited on 2024-11-25 },
}