Pregled bibliografske jedinice broj: 1054397
Convolutional Neural Networks and Transfer Learning Based Classification of Natural Landscape Images
Convolutional Neural Networks and Transfer Learning Based Classification of Natural Landscape Images // Journal of universal computer science, 26 (2020), 2; 244-267 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1054397 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Convolutional Neural Networks and Transfer Learning Based Classification of Natural Landscape Images
Autori
Krstinić, Damir ; Braović, Maja ; Božić-Štulić, Dunja
Izvornik
Journal of universal computer science (0948-695X) 26
(2020), 2;
244-267
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
deep learning, transfer learning, convolutional neural networks, image classification, natural landscape images, wildfire smoke
Sažetak
Natural landscape image classification is a difficult problem in computer vision. Many classes that can be found in such images are often ambiguous and can easily be confused with each other (e.g. smoke and fog), and not just by a computer algorithm, but by a human as well. Since natural landscape video surveillance became relatively pervasive in recent years, in this paper we focus on the classification of natural landscape images taken mostly from forest fire monitoring towers. Since these images usually suffer from the lack of the usual low and middle level features (e.g. sharp edges and corners), and since their quality is degraded by atmospheric conditions, this makes the already difficult problem of natural landscape classification even more challenging. In this paper we tackle the problem of automatic natural landscape classification by proposing and evaluating a classifier based on a pretrained deep convolutional neural network and transfer learning.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus