New Algorithm Reduces Noise

[Chase Goldman]

I think the physical detecting principle would have to be changed or enhanced somewhat for this to really change the treasure hunting game.  I don’t think magnetic induction principles alone can achieve huge gains at this point even with AI applied.  A combination of induction balance or PI for conductive metal detection combined with compact/low power/high resolution Ground Penetrating Radar would be killer for deep, larger cross-section targets.  Magnetic induction would still be needed and would probably dominate for detection of small targets and tiny natural gold.  

Also use of AI and Augmented Reality combined with ultra precise ground mapping would also be a useful tool.  Imagine donning a pair of Augmented Reality glasses that could enable you to see where your coil has actually been to ensure complete ground coverage at a site, visual target logging (to ID target density/concentration).  I mean how many targets are not recovered simply because you didn’t get the coil over the target and not due to an inherent limitation of the machine.  The ultimate objective would be finally giving you the “X Ray” vision ability to actually peer into the ground and “see” buried targets in situ and in real time and without a semi-trailer of electronics needed to achieve that goal.

[GB_Amateur]

11 hours ago, jasong said:

AlphaZero has an open source equivalent called LeelaZero. Leela can run off a laptop computer ok.

Leela Zero is trained by a distributed effort, which is coordinated at the Leela Zero website. Members of the community provide computing resources by running the client, which generates self-play games and submits them to the server. The self-play games are used to train newer networks. Generally, over 500 clients have connected to the server to contribute resources.^[7] The community has provided high quality code contributions as well.^[7]

The above quote is from Wikipedia and is actually referring to the Go (game) version, not the chess version.  Apparently for this to work on a small platform the 'crowd learning' aspect would need to be carried over.  So users would share the learning their individual detectors experience in some kind of uploadable & downloadable database.  Interesting.  I hope there are enough users to make that useful.  Or in addition will the detector company have some kind of robot course where the software is trained and then incorporated??

When I was looking into artificial neural nets (ANN's) which I think is Alpha's artificial intelligence method, I was told it typically takes hundreds of thousands of datapoints to build a reasonable model.  Maybe metal detecting can be done with considerably less -- I think that's going to be a requirement.  But as you say, it will likely require "thinking outside the box" so conventional wisdom could put placed on its ear.

[green]

I'm probably wrong, wouldn't be the first time. Detection is S/N. Noise is random, don't know if algorithm can reduce something that keeps changing.

[GotAU?]

Another area of promise is computer enhanced digital signal processing and frequency analysis. Our detectors already do this, but they are limited in discriminating because there’s limited AI behind the signal processing. There are subtle sound differences a detector gives off on certain targets that experienced operators learn as they use their machines that help cue them to what may or may not be a good target, and if a detector could be programmed to learn this along the way, that would be something.

I used to work as a wildlife biologist and did bat surveys using a program that would learn different types of bat calls to help identify them from recorded ultrasonic call files. It would compare different frequency characteristics to known calls to find a best fit.  There is currently research being done on mine and UXO detectors to help them better discriminate between trash and hot targets. Part of the processing uses frequency analysis using polar plotting that compares signal amplitude, timing and frequency. It’s an interesting way to look at the signals and how they are  analyzed.

I tried this out in my yard once using my smartphone and a frequency analysis app with my SDC as I ran it over aluminum, iron and a bit of gold,  but there was too much EMI to do it well and I gave up.  Sometime I want to try it out in the field under real conditions.  It has some promise, and it would also be a great way for people with compromised hearing to be able to see exactly what their PI detector is saying  because instead of just a few LED lights turning on from a target, the display from the phone app gives a lot of information about the signal.

[mh9162013]

17 hours ago, Steve Herschbach said:

You know, when I was a teenager you could buy a pocket calculator that added, subtracted, multiplied, and divided with a couple other little functions for $500. I told my friend and partner Dudley that someday they would give them away free. He of course scoffed but in later days now he brings it up a lot that I was right. Never underestimate how quickly and how fast technology can advance giving us more power at lower prices. The expensive high tech toys of today are no different.

Just to add on what Steve said, today, you can buy a birthday or holiday card that plays music when you open it up. This card has more computing power than was available to the entire Allied armies of WW2. But today, when we're done with the card, we throw it away.

[mh9162013]

1 hour ago, GotAU? said:

There are subtle sound differences a detector gives off on certain targets that experienced operators learn as they use their machines that help cue them to what may or may not be a good target, and if a detector could be programmed to learn this along the way, that would be something.

That makes me wonder, what if a detector had a simple boolean algorithm that, after every hole you dug, it asks you if it was a "good" find or "trash." After a few hundred digs, I bet it could do a darn good job of being able to figure out if its user is likely to dig the next time the machine gets a signal.

[GotAU?]

46 minutes ago, mh9162013 said:

That makes me wonder, what if a detector had a simple boolean algorithm that, after every hole you dug, it asks you if it was a "good" find or "trash." After a few hundred digs, I bet it could do a darn good job of being able to figure out if its user is likely to dig the next time the machine gets a signal.

That may actually work.  There are several research papers out there on this very type of research, like this one using frequency analysis of detector signals to get more accurate target discrimination: https://www.ndt.net/article/ecndt2006/doc/Tu.4.5.4.pdf

Another interesting part of the above paper is how they are mapping out the shape of objects by using a small camera to determine the position of the detector as it sweeps across a buried object, the resulting image is like what one would get with a GPR but such a setup could be much simpler and less costly.  Something else to add to the GPX 6500!   ?

[EL NINO77]

When developing new detection technologies, I would focus more from my point of view on the elimination of erroneous or unnecessary data, especially the data that are unnecessary for certain types of detection. Here I would use AI.

In terms of the range and sensitivity of the detector, I would like to improve the quality of the S / N parameter of the received signal .. it can be improved in several ways ..

[GB_Amateur]

1 hour ago, EL NINO77 said:

I would focus more from my point of view on the elimination of erroneous or unnecessary data, especially the data that are unnecessary for certain types of detection.

Would you give examples of these unwanted data?