stručni rad
The problem of automatic classification of photographs, graphics and spatial data is more and more commonly addressed using advanced machine learning methods and related models like Convolutional Artificial Neural Networks (CANN). In the scope of this work, we conducted a study of application of the CANN to an example of emoticon classification. In this paper, chosen methods are described and solutions for data collection and processing, training and evaluation of the model are offered. The presented results show successful application of the model.
CNN; Convolutional Neural Networks; ANN; emoticons; image recognition
Razvojem virtualizacijskih tehnologija raste kompleksnost IT sustava, dok korisnici istovremeno zahtijevaju brži pristup resursima, napredne integracije i jednostavnost korištenja. Jedno od ključnih rješenja za ove izazove primjena je…
Ovaj rad istražuje i uspoređuje mogućnosti prosljeđivanja grafičkih kartica na Hyper-V i KVM hipervizorima prema virtualnim strojevima, detaljno opisujući metode, postupke i razlike u arhitekturi koje utječu na…
The ever-growing usage and adaptation of HTTP/3 in web traffic leverages Quick UDP Internet Connections (QUIC) as a transport protocol. QUIC is widely recognized for reduced latency, enhanced…
