Preskoči na glavno vsebino

Video prikaz dveh novih metod strojnega učenja, ki zasenčita dosedanjo metodo






Rezultat iskanja slik za ijs is2016


Raziskovalci se občasno sestanemo, da drug drugemu predstavimo svoje delo, svoje dosežke. Dobra priložnost za to so znanstvene konference. Ena naj bolj uglednih tovrstnih konferenc na področju umetne inteligence v Sloveniji z naslovom Informacijska družba 2016, se je odvila te dni na institutu Jožef Štefan v Ljubljani.

Rezultat iskanja slik za ijs is2016

Na njej smo obravnavali mnogo zanimivih tem, ki nam nakazujejo smer razvoja informacijske tehnologije v družbi v bližnji prihodnosti. Zadnja leta je vedno bolj v ospredju umetna inteligenca in strojno učenje, trenutno v svetu še posebej odmevajo dosežki globokega učenja. Nekatere druge teme so bile: evidentiranje genetsko modificiranih organizmov v živilih, zaznavanje stresa v službi, priporočanje čtiva, odkrivanje novih zlitin, sinteza slovenskega govora, razvoj avtonomnega vozila; seveda vse skupaj na osnovi umetne inteligence. Sam sem predstavil kolegom dva nova algoritma strojnega učenja, ki sem ju razvil v bližnji preteklosti. Več o vsebini si lahko ogledate v zborniku. Razen vsebine prispevkov, pa je na konferenci pomembno tudi navezovanje stikov s kolegi in izmenjava mnenj z njimi.

Video





Oznake:

Komentarji

Objavite komentar

Priljubljene objave iz tega spletnega dnevnika

Artificial intelligence

          Artificial intelligence (AI) is a relatively young branch of science that stirs the imagination of many. Even movie directors from hollywood are not exceptions. Development in AI area is very fast and there is no indication that this will change soon. I still remember my first contact with learning devices. This happend at the end of the last millennium when I realized neural networks (NN). They have immediately attracted my attention, because such devices were not known till then.           NN are made along the lines of mammalian brain. During the learning NN extract the essence from the data. After the learning we can ask NN questions. It gives us the right answers even to questions that during learning did not participate.  NN learns autonomously and therefore may exceed the teacher's (poeple's) knowledge. Here are some important achievements of artificial intelligence: A couple of years ago the co...
7 komentarjev
Preberite več

Bipropagation demonstration in MatLAB

Here is given an example of the "bipropagation" algorithm for learning of NN. It is written in MatLAB language (R2015a) and is as similar as possible  to  "Deep learning" example "AutoencoderDigitsExample.m" which is included in MatLAB's Neural Network Toolbox. So you can easily compare both algorithms. I believe that my algorithm have few advantages over autoencoder. Please tell me what do you think about it. Please cite me in your works. Thanks a lot. Download demo ====================================================== %% Training a Deep Neural Network for Digit Classification % This example shows how to use the Neural Network Toolbox(TM) to train a % deep neural network to classify images of digits and is very similar to % "AutoencoderDigitsExample.m" which is included in % Neuronal Network ToolBox from MatLAB. This example is made for comparison % of both algorithms. % % Neural networks with multiple hidden layers can be usefu...
Objavite komentar
Preberite več