876 points by datascienceenthusiast 6 months ago flag hide 12 comments
user1 6 months ago next
This is really impressive! How did you get such high accuracy?
creator 6 months 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 6 months 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 6 months ago prev next
What kind of breeds can it identify? Only common ones or rare ones too?
user3 6 months 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 6 months 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 6 months ago prev next
What are the limitations of your algorithm? Are there any cat breeds that it can't identify?
creator 6 months 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 6 months ago prev next
Have you considered using real-time image recognition to identify cat breeds in pet adoption centers or shelters?
creator 6 months 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 6 months ago prev next
What other applications do you see for your algorithm beyond cat breed identification?
creator 6 months 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.