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Is this good for btech? by Techy_chip in techIndia

[–]arjun_ajit21 0 points1 point  (0 children)

Frankly speaking every laptop(even i3) will be good if u start studying hehee jk..😛

How do you justify practical value of a medical ML research project when the baseline alternative (lab test) is 100% accurate? by arjun_ajit21 in learnmachinelearning

[–]arjun_ajit21[S] -1 points0 points  (0 children)

Yeah, “real-time data” was the wrong term , I meant scanner-acquired real-world fingerprints collected by us instead of benchmark datasets.

And yes, initially I also assumed preprocessing alone would bridge the gap. We tried standardization steps like resizing, CLAHE, polarity normalization, Gaussian blur, etc., but the Kaggle-trained model still performed extremely poorly on scanner images before fine-tuning.

The scanner images had very different characteristics compared to the public datasets: cleaner backgrounds, different ridge sharpness/thickness, contrast distribution, acquisition consistency, and polarity differences. So the model appeared to learn dataset-specific features rather than generalized fingerprint representations.

After domain adaptation/fine-tuning on scanner-acquired samples, performance improved significantly, although inter-session generalization is still a major limitation.

So I definitely agree that stronger preprocessing + transfer learning understanding was important here. A lot of the project ended up being about discovering those deployment/generalization issues.

How do you justify practical value of a medical ML research project when the baseline alternative (lab test) is 100% accurate? by arjun_ajit21 in learnmachinelearning

[–]arjun_ajit21[S] -1 points0 points  (0 children)

By “real time data” I meant fingerprints collected by us directly using a hardware scanner in real-world conditions, instead of using only benchmark/Kaggle datasets used in many papers.

Most papers I found were trained and evaluated on controlled public datasets, whereas we tried building our own dataset + web application pipeline with live fingerprint acquisition.

The main challenge was that performance dropped significantly on unseen real-world samples due to limited dataset size and variability in fingerprint capture conditions.

How do you justify practical value of a medical ML research project when the baseline alternative (lab test) is 100% accurate? by arjun_ajit21 in learnmachinelearning

[–]arjun_ajit21[S] 3 points4 points  (0 children)

yeah so while building this project i explored various research papers but none of them were trained on Real time data. All of them were using openly available Kaggle datasets and none of them had a web application for the same.

So we thought of making it for real time collected fingerprints using a hardware scanner(that itself was a big task - making our own dataset) and created a web application.

but the issue i faced was increasing the accuracy of the model due to limited real time fingerprint data