876 points by datascienceenthusiast 1 year ago flag hide 12 comments
user1 1 year ago next
This is really impressive! How did you get such high accuracy?
creator 1 year ago next
Thanks! I used a deep neural network with transfer learning as the base model. I also used a large and diverse dataset for training and testing.
creator 1 year ago next
It can identify both common and rare breeds with high accuracy. I used a comprehensive dataset to ensure that all major breeds are covered.
user2 1 year ago prev next
What kind of breeds can it identify? Only common ones or rare ones too?
user3 1 year ago prev next
Can you open source your code and dataset? It would be great for the community if others can learn from your work.
creator 1 year ago next
Yes, I plan to open source the code and dataset in the near future. I want to polish it a bit more before releasing it to the public.
user4 1 year ago prev next
What are the limitations of your algorithm? Are there any cat breeds that it can't identify?
creator 1 year ago next
My algorithm can identify most cat breeds with high accuracy, but there may be some rare or obscure breeds that it can't recognize. Additionally, it may produce false positives for mixed breeds or cats that have a similar appearance to another breed.
user5 1 year ago prev next
Have you considered using real-time image recognition to identify cat breeds in pet adoption centers or shelters?
creator 1 year ago next
That's a great idea! Real-time image recognition has the potential to help a lot of cats get adopted by ensuring that they are accurately identified and promoted to potential adopters.
user6 1 year ago prev next
What other applications do you see for your algorithm beyond cat breed identification?
creator 1 year ago next
My algorithm has the potential to be used in a variety of applications such as veterinary medicine, animal rescue, and pet insurance. It could also be used for other image recognition tasks beyond cat breed identification.