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Pregled bibliografske jedinice broj: 1031286

Detection of Toy Soldiers Taken from a Bird’s Perspective Using Convolutional Neural Networks

Sambolek, Saša; Ivašić-Kos, Marina
Detection of Toy Soldiers Taken from a Bird’s Perspective Using Convolutional Neural Networks // 11th International Conference ICT Innovations / Gievska, S. ; Madjarov, G. (ur.).
Ohrid, Sjeverna Makedonija: Springer, 2019. str. 13-26 doi:10.1007/978-3-030-33110-8_2 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)

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Naslov
Detection of Toy Soldiers Taken from a Bird’s Perspective Using Convolutional Neural Networks

Autori
Sambolek, Saša ; Ivašić-Kos, Marina

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

ISBN
978-3-030-33109-2

Skup
11th International Conference ICT Innovations

Mjesto i datum
Ohrid, Sjeverna Makedonija, 17.10.2019. - 19.10.2019

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Object detectors ; SSD ; Faster R-CNN

Sažetak
This paper describes the use of two different deep-learning approaches for object detection to recognize a toy soldier. We use recordings of toy soldiers in different poses under different scenarios to simulate the appearance of persons on footage taken by drones. Recordings from a bird’s eye view are today widely used in the search for missing persons in non-urban areas, border control, animal movement control, and the like. We have compared the single-shot multi-box detector (SSD) with the MobileNet or Inception V2 as a backbone, SSDLite with MobileNet and Faster R- CNN combined with Inception V2 and ResNet50. The results show that Faster R-CNN detects small objects such as toy soldiers more successfully than SSD, and the training time of Faster R-CNN is much shorter than that of SSD.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA

Projekti:
HRZZ-IP-2016-06-8345 - Automatsko raspoznavanje akcija i aktivnosti u multimedijalnom sadržaju iz domene sporta (RAASS) (Ivašić Kos, Marina, HRZZ - 2016-06) ( CroRIS)

Ustanove:
Fakultet informatike i digitalnih tehnologija, Rijeka

Profili:

Avatar Url Marina Ivašić Kos (autor)

Avatar Url Saša Sambolek (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada doi link.springer.com

Citiraj ovu publikaciju:

Sambolek, Saša; Ivašić-Kos, Marina
Detection of Toy Soldiers Taken from a Bird’s Perspective Using Convolutional Neural Networks // 11th International Conference ICT Innovations / Gievska, S. ; Madjarov, G. (ur.).
Ohrid, Sjeverna Makedonija: Springer, 2019. str. 13-26 doi:10.1007/978-3-030-33110-8_2 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Sambolek, S. & Ivašić-Kos, M. (2019) Detection of Toy Soldiers Taken from a Bird’s Perspective Using Convolutional Neural Networks. U: Gievska, S. & Madjarov, G. (ur.)11th International Conference ICT Innovations doi:10.1007/978-3-030-33110-8_2.
@article{article, author = {Sambolek, Sa\v{s}a and Iva\v{s}i\'{c}-Kos, Marina}, year = {2019}, pages = {13-26}, DOI = {10.1007/978-3-030-33110-8\_2}, keywords = {Object detectors, SSD, Faster R-CNN}, doi = {10.1007/978-3-030-33110-8\_2}, isbn = {978-3-030-33109-2}, title = {Detection of Toy Soldiers Taken from a Bird’s Perspective Using Convolutional Neural Networks}, keyword = {Object detectors, SSD, Faster R-CNN}, publisher = {Springer}, publisherplace = {Ohrid, Sjeverna Makedonija} }
@article{article, author = {Sambolek, Sa\v{s}a and Iva\v{s}i\'{c}-Kos, Marina}, year = {2019}, pages = {13-26}, DOI = {10.1007/978-3-030-33110-8\_2}, keywords = {Object detectors, SSD, Faster R-CNN}, doi = {10.1007/978-3-030-33110-8\_2}, isbn = {978-3-030-33109-2}, title = {Detection of Toy Soldiers Taken from a Bird’s Perspective Using Convolutional Neural Networks}, keyword = {Object detectors, SSD, Faster R-CNN}, publisher = {Springer}, publisherplace = {Ohrid, Sjeverna Makedonija} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Conference Proceedings Citation Index - Science (CPCI-S)
  • Scopus

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