186 points by signaturegeek 7 months ago flag hide 19 comments
john_doe 7 months ago next
Fascinating project! Just curious, what kind of accuracy rate are you seeing with this handwriting signature verification system?
jane_programmer 7 months ago next
@john_doe We're currently testing the accuracy rates but we have seen close to 95% success during initial testing.
alex_deeplearn 7 months ago prev next
@john_doe Very nice! You can try incorporating additional features like pressure sensitivity data to potentially improve accuracy rates
frank_the_tank 7 months ago prev next
Really like the concept, but do you have any plan to open source your codebase? It would be a great resource for those of us in the machine learning/computer vision community
coding_nerd 7 months ago next
@frank_the_tank To be determined! The goal is to polish the system and make it more robust for commercial use
user123 7 months ago prev next
Impressive! I'd love to know what kind of neural network architecture you used for this project.
ml_engineer 7 months ago next
@user123 We used a combination of CNNs and LSTMs to analyze and model the handwriting patterns.
ai_insider 7 months ago prev next
@user123 You may want to try using attention mechanisms or transformers to enhance the model's focus on critical areas within the signature images
mt_hacker 7 months ago prev next
Would this have any application in the field of digital signatures?
sig_research 7 months ago next
@mt_hacker Yes, this system could potentially be used to verify digital signatures as well, as long as they are based on written input.
sig_analyst 7 months ago next
@sig_research That's an interesting idea, blurring the line between physical and digital verification methods.
ml_hacker 7 months ago prev next
@sig_analyst That would certainly make things more interesitng, and possibly increase the user base for a product like this!
os_enthusiast 7 months ago next
@ml_hacker It's true. This could open the door for many exciting collaborations and developments!
hacker007 7 months ago prev next
Have you tried using any type of generative models to augment your data for training the system?
deep_vision 7 months ago next
@hacker007 Yes, we tested GANs for data augmentation. They proved helpful in increasing the system's robustness a bit.
gan_artist 7 months ago next
@deep_vision GANs are indeed pretty cool. Did you try using Conditional GANs (cGANs) for more control in generating specific signature patterns?
deep_vision 7 months ago next
@gan_artist Actually we focused mostly on augmenting our existing dataset for now, but exploring cGANs is an interesting idea for future work!
quant_learner 7 months ago prev next
What would be your approach for a real-time, streamlined integration into an existing application or service?
api_developer 7 months ago next
@quant_learner We would suggest using a lightweight RESTful API or an event-driven microservices architecture for real-time integration. Another approach would be to use TensorFlow.js with a WebWorker for faster browser-based processing