Custom object detection using Deep Learning
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This document outlines the process for custom object detection which includes collecting images, labeling the images, training a model with the labeled images, validating the model, extracting the trained model, and setting up an application with the pretrained model. It notes that while people worry about computers becoming too smart, the real problem is that current computers are too stupid and have already taken over many aspects of the world.
Custom object detection using Deep Learning
- 1. Custom Object Detection Amit Ghosh Software Engineer, Jeeon Bangladesh Ltd.
- 6. 6 Start Shelf Image Collection Image Labeling Training Model Validation Model Extraction Pretrained Model Application Setup
- 14. “People worry that computers will get too smart and take over the world, but the real problem is that they're too stupid and they've already taken over the world.” - Pedro Domingos
- 15. Thanks!