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Back to week 1 page: Link
If your post satsifies the requirements (1), (2), you will receive 0.5 points for the post.
📗 Go to the MobileNet demo: Link (TensorFlow.js) or Link (Pytorch). Find two images of the same object (or two similar objects), one of which is classified correctly and the other is classified incorrectly. Share the screenshots of the images and the labels on Piazza, and briefly discuss why you think the image may be classified incorrectly.
📗 The images can be photos you take, pictures you draw, or images you find on the Internet, you should explain in the post where you got the images from.
📗 In order for an image to be classified correctly, the object in the image must come from one of the ImageNet classes: Link.
📗 Other references in case you would like to include MobileNet in your applications: Keras: Link, TensorFlow.js: Link.
Images from Korean TV Series "Start Up" (2020) via Netflix.
If your post satisfies the requirements (1), (2), (3), one of the course staff will "like" your post and you will receive 0.5 points for the post. Remember to use the correct Piazza tag in d1 to d12.
The past exams can be found on pages X1, X2, X3, X4, X5, X6, X7, X8,
Back to week 1 page: Link
# D Discussion Topic
📗 Please create a follow-up discussion post on the Piazza (it is okay to post anonymously). No Canvas submissions are required. The grades will be updated at the end of the week on Canvas: Link| Requirement | Discussion | Note |
| Topic | see below | |
| Due Date | suggested: June 26 | no points after: July 16 |
| Max per Week | 2 | 1 per topic |
| Type of Post | Piazza follow-up | |
| Include | (1) Image or screenshot | |
| - | (2) Brief discussion or explanation | (one or two sentences) |
If your post satsifies the requirements (1), (2), you will receive 0.5 points for the post.
📗 Go to the MobileNet demo: Link (TensorFlow.js) or Link (Pytorch). Find two images of the same object (or two similar objects), one of which is classified correctly and the other is classified incorrectly. Share the screenshots of the images and the labels on Piazza, and briefly discuss why you think the image may be classified incorrectly.
📗 The images can be photos you take, pictures you draw, or images you find on the Internet, you should explain in the post where you got the images from.
📗 In order for an image to be classified correctly, the object in the image must come from one of the ImageNet classes: Link.
📗 Other references in case you would like to include MobileNet in your applications: Keras: Link, TensorFlow.js: Link.
Images from Korean TV Series "Start Up" (2020) via Netflix.
# D Sharing Solutions on Piazza
📗 Use the sign-up sheet: Google Sheet. You can sign up and post anonymously (anonymous Piazza posts are not anonymous to instructors).| Requirement | Past Exam Questions | Note |
| List of Questions | X1 | 1 |
| Due Date | suggested: June 26 | no points after: July 10 |
| Name of Post | X?Q? | |
| Max per Week | suggested: 2 | no points if more than 4 |
| Piazza Tag | d1 | |
| Type of Post | public Piazza note | |
| Include | (1) Screenshot of the question | |
| - | (2) Detailed step-by-step solution | |
| - | (3) Brief explanation of each step |
If your post satisfies the requirements (1), (2), (3), one of the course staff will "like" your post and you will receive 0.5 points for the post. Remember to use the correct Piazza tag in d1 to d12.
The past exams can be found on pages X1, X2, X3, X4, X5, X6, X7, X8,
Last Updated: April 29, 2024 at 1:11 AM