Answer-first summary for fast verification
Answer: Use Cloud Vision AutoML with the existing dataset.
The correct answer is A: Use Cloud Vision AutoML with the existing dataset. This option is the most suitable because AutoML simplifies the model building process by allowing you to upload your labeled images, after which it takes care of model selection, training, and evaluation. Given that you have a labeled dataset with an average of 1000 examples per component, the dataset is sufficient for AutoML. This approach requires minimal custom development and allows for quick integration into your app, making it ideal for a Proof-Of-Concept within a few working days.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
No comments yet.
You work for a manufacturing company that sources up to 750 different components, each from a different supplier. Your team has collected a labeled dataset that averages 1000 examples for each unique component. The goal is to create an app that assists warehouse workers in identifying incoming components through photos. Your objective is to develop a functional prototype of this app as a Proof-Of-Concept within a few working days. What should you do?
A
Use Cloud Vision AutoML with the existing dataset.
B
Use Cloud Vision AutoML, but reduce your dataset twice.
C
Use Cloud Vision API by providing custom labels as recognition hints.
D
Train your own image recognition model leveraging transfer learning techniques.