20.500.12556/RUL-154905 Prepoznavanje obrokov in ugrizov s strojnim učenjem na podlagi meritev pametne ure magistrsko delo Predicting meals and bites with machine learning based on measurements of a smartwatch Magistrska naloga predstavi pristop zaznavanja obrokov in ugrizov. Podatki so bili pridobljeni v eksperimentu, v katerem je sodelovalo 12 posameznikov, ki so s pomočjo žiroskopa in pospeškomera, nameščenih v pameti uri, merili premike zapestja v svojem običajnem življenju. Skupno so posneli za 570 ur podatkov in pri tem zajeli 169 obrokov. Glavni del algoritma za zaznavanje obrokov in ugrizov temelji na uporabi globokega učenja. Pri rezultatih, dobljenih s pomočjo prečnega preverjanja, je mera F1 v primeru zaznavanja obrokov znašala 0,91, medtem ko je pri zaznavanju ugrizov znašala 0,83. To kaže, da se je algoritem relativno uspešno naučil prepoznavati obroke v običajnem življenju posameznikov, medtem ko se je prepoznavanje ugrizov izkazalo za večji izziv. The master’s thesis proposes an approach of predicting meals and bites. The data was obtained in the wild, in an experiment in which 12 participants measured the movements of their wrists via a gyroscope and an accelerometer installed in a smartwatch. The data includes 169 meals and has the total duration of 570 hours. The main part of the algorithm for the predictions of meals and bites is based on deep learning. The results obtained with a cross-validation show that the F1 score of the predictions of meals equals 0.91, while the F1 score of the predictions of bites equals 0.83. This shows that the algorithm relatively successfully learned to recognize meals in the wild, while the predictions of bites proved to be more challenging. strojno učenje globoko učenje prepoznavanje prehranjevanja machine learning deep learning eating recognition true false false Slovenski jezik Angleški jezik Magistrsko delo/naloga 2024-03-08 08:15:04 2024-03-08 08:15:07 2024-05-29 09:41:30 0000-00-00 00:00:00 2024 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 139739 187908355 12032.pdf 12032.pdf 1 36ABE1B9D9AA7FC10D9D401B214092E1 7aef5bcd1bd1b504997be2c4c72b81364893d871956bb9415665681dd571bd12 980c3dee-dd1b-11ee-b35c-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=181547 Fakulteta za matematiko in fiziko 0 0 0