Topic 1 Question 99
A company uses camera images of the tops of items displayed on store shelves to determine which items were removed and which ones still remain. After several hours of data labeling, the company has a total of 1,000 hand-labeled images covering 10 distinct items. The training results were poor. Which machine learning approach fulfills the company's long-term needs?
Convert the images to grayscale and retrain the model
Reduce the number of distinct items from 10 to 2, build the model, and iterate
Attach different colored labels to each item, take the images again, and build the model
Augment training data for each item using image variants like inversions and translations, build the model, and iterate.
ユーザの投票
コメント(8)
- 正解だと思う選択肢: D
Data Augumentation is the way to go here.
How does converting to grayscale help? What if the colors of the items are relevant in object identification???
👍 10ovokpus2022/06/23 - 正解だと思う選択肢: D
D, i guess
👍 4Istdanagan2022/04/20 - 正解だと思う選択肢: D
D is my answer for this. A can help but it'll need more than that.
👍 4cron00012022/04/22
シャッフルモード