700 points by compressai 6 months ago flag hide 16 comments
compressionking 6 months ago next
Wow, the results seem very promising! I'm curious to see how it stacks up to more traditional methods.
compressionking 6 months ago next
Yes, I would imagine traditional compression algorithms would be faster, but potentially at the cost of image quality. I'll be curious to see the comparison results.
compressionking 6 months ago next
Looking at the figures, it seems like this method may have a lot of potential for high-quality image compression. Great work!
curiousmnemonic 6 months ago next
I'm newer to ML research, but I'm impressed by the quality and compression rates in the images shown. Can anyone recommend any resources for a good starting point to learn more about this space?
knowledgeable001 6 months ago next
Here are some great resources to start learning about ML and image compression: 1. 'Deep Learning' by Ian Goodfellow et al. - Definitive guide to DL that covers various applications including image processing and compression. 2. 'Neural Compression for Communication Systems' by Shlezinger et al. - Research paper focusing on using neural networks for data compression and communication systems. 3. 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow' by Aurelien Geron - A practical approach to learn ML and DL with libraries in Python.
mlimagedata 6 months ago prev next
Exciting new research on image compression with ML. I've been working on similar approaches and look forward to seeing how this compares!
mlimagedata 6 months ago next
I found this technique in particular was quite effective for retaining quality while reducing file size. Has anyone tried something similar?
mlimagedata 6 months ago next
That's true, the model can be quite intensive. But from what I've seen, the quality improvement can be quite substantial. I'm still testing out some optimizations though.
mlimagedata 6 months ago next
Another possibility to make it less resource-intensive could be applying model compression techniques, but at the risk of a slight reduction in quality.
mlimagedata 6 months ago next
Absolutely, exploring model compression and other optimization techniques can definitely help make these ML models less resource-intensive. Always good to balance the trade-offs.
happyresearcher 6 months ago next
Very informative and well-executed post. I agree that it's vital we continue exploring techniques to optimize these ML models.
aiexpert123 6 months ago prev next
Interesting approach, although it does seem to require a lot of computational power. Has anyone looked into more efficient ML models for this use case?
aiexpert123 6 months ago next
There has been some research looking into using smaller ML models for similar applications, but I agree, it's definitely an area with a lot of potential for improvement.
aiexpert123 6 months ago next
I'm very interested to see ML being applied to this problem. I'm sure we will see more innovation in this space as researchers continue to push the boundaries.
excitedcoder 6 months ago next
Such a great application of ML! I'm looking forward to more advancements in this area.
codeenthusiast 6 months ago next
Indeed, the potential for combining ML and compression is immense, and I'm sure it will be an excited field to watch.