Metode klasifikacije za prepoznavanje rukom pisanih cifara: pregled

Ključne reči: prepoznavanje rukom pisanih cifara, klasifikacija slika, mašina potpornih vektora, duboke neuronske mreže, konvolucijske neuronske mreže, optimi zacija hiperparametara, inteligencija roja, MNIST

Sažetak


Uvod/cilj: U radu je predstavljen pregled metoda za prepoznavanje rukom pisanih cifara testiranih na MNIST skupu podataka.

Metode: Rad analizira, sintetiše i upoređuje razvoj ra- zličitih klasifikatora primenjenih za prepoznavanje rukom pisanih cifara, od linearnih klasifikatora do konvolucijskih neuronskih mreža.

Rezultati: Tačnost klasifikacije za prepoznavanje ru- kom pisanih cifara testirana na skup podataka MNIST dok se koristi skup za treniranje i testiranje je sada ve- ća nego 99,5%. Najuspešnija metoda je konvolucijska neuronska mreža.

Zaključak: Tačno pre- poznavanje različitih stilova rukopisa, konkretno ci- fara, proučavano je decenijama, a u radu su sumirani  postignuti rezultati. Najbolji su postignu- ti sa konvolucijskim neuronskim mrežama, dok su najlošije metode linearni klasifikatori. Konvolucijske neuron-ske mreže daju bolje rezultate ako je skup podataka proširen metodom augmentacije.

 

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Objavljeno
2023/01/30
Rubrika
Pregledni radovi