The Keris and The Komputer

[A. G. Maisey]

Here you are people, a link to something that will enthrall and educate, as well as answer many questions that will no longer need to be asked:-

https://www.semanticscholar.org/paper/Hybrid-Method-and-Similarity-to-Recognize-Javanese-Santoso-Hadjon/2265fe6846824779dcaccd79b8eee26265e7ac2a

its all a bit over my head, and in any case, I much prefer the cogitative approach, but I'm sure it will be of interest to others.

[David]

Egads man! What witchcraft is this! LOL! ;) :D

[A. G. Maisey]

Dunno David, above my pay grade.

[Ian]

Alan,

:eek: Unusual approach to identification of the keris. Any idea who might use such technology in a meaningful way?

Ian

[A. G. Maisey]

Well Ian, since I understand very little about the technology used by this method, any opinion of mine on matters such as this must be regarded as inherently defective, but as I sort of flit around the edges of academia without being a part of academia, I have noted that very often people who know very little about one discipline, but a great deal about some other discipline sometimes produce hypotheses that illustrate their phenomenal depth on knowledge in respect of the known discipline whilst at the same time illustrating their abysmal ignorance in respect of the other.

Having this belief as a base upon which to respond to your question, I would venture that those who might use this wizardry to classify a keris would very likely be those who have virtually no understanding of the keris.

[Lee]

Any idea who might use such technology in a meaningful wayI expect this technology could give an airport luggage or postal parcel X-ray inspection device an ability to present a fairly accurate description of the contents to a customs officer without the need of opening...

[ariel]

As far as I could understand, this may be just a training exercise for machine image recognition. Kind of testing a simplified version of facial recognition. Machine reading of CT and MRI scans is under very active development. A very simple version is machine reading of ECGs, and is already widely used.

Kris, with their complexity of forms, are very handy model.

[JeffS]

I work with machine learning for classifying land cover types (forest, grassland etc) on satellite imagery to better under changes over time, like deforestation or development. This particular paper is using edge detection outputs to classify keris types. As such this will broadly allow it to classify broad groups that can be distinguishable with 2-D profile (silhouette) information. As Ariel says, this an interesting academic exercise but certainly can't add to keris understanding which is clearly far more subtle than profile ratios.

[mross]

This is cool stuff, at least to a komputer wienie like me. It seems to be a new take on algorithms to help identify an object. With a database of only 10 comparators it is a little weak. However I thing what we have here is someone has an interest in the Keris and needed to get a paper published. So wallah. Alan I don't think you have anything to worry about in the foreseeable future.

[David]

I work with machine learning for classifying land cover types (forest, grassland etc) on satellite imagery to better under changes over time, like deforestation or development. This particular paper is using edge detection outputs to classify keris types. As such this will broadly allow it to classify broad groups that can be distinguishable with 2-D profile (silhouette) information. As Ariel says, this an interesting academic exercise but certainly can't add to keris understanding which is clearly far more subtle than profile ratios.
I have to point out that you cannot really determine the dhapur of a keris by silhouette edge detection alone. Such a method cannot show, for instance, if the keris has tikel alis, blumbangan, sogokan or other interior keris elements that are essential for proper identification. I am still having problems finding a practical purpose for this methodology. ;)

[mross]

I have to point out that you cannot really determine the dhapur of a keris by silhouette edge detection alone. Such a method cannot show, for instance, if the keris has tikel alis, blumbangan, sogokan or other interior keris elements that are essential for proper identification. I am still having problems finding a practical purpose for this methodology. ;)
Me thinks u r confusing academia with the real world. :D Any relevance is purely coincidental.

[jagabuwana]

Haha this is definitely one of the more niche applications of ai/machine learning I've seen. As many have said, don't know if it helps us as students of the keris, but it's a fun machine learning exercise that can certainly be advanced.

You could probably use some variant or less sophisticated version of a machine learning model used in geospatial applications. If it can recognise topography (depth, height, etc.), then it will be able to distinguish the full array of ricikan that we need to be able to train the machine to make a prediction about what dhapur a keris is.

Imagine being able to take a photo of your keris, uploading it to Keris Warung Kopi, and our resident machine can tell you in seconds. We might put Alan out of a job!
:D

[mariusgmioc]

Are you guys getting bored or what?!

:shrug: