Autors: Christoff, N. V., Bardarov, N., Nikolova, D. V.
Title: Automatic Classification of Wood Species Using Deep Learning
Keywords: convolutional neural network; deep learning; tree classifica

References

    Issue

    16th International Conference on INnovations in Intelligent SysTems and Applications (INISTA), pp. 1-5, 2022, France, DOI 10.1109/INISTA55318.2022.9894170

    Цитирания (Citation/s):
    1. Stavrev, S., & Ginchev, D. (2023, May). Prototype Monitoring System Detecting Mental Workload During Pilot Simulation Training. In 2023 International Conference on Military Technologies (ICMT) (pp. 1-6). IEEE. - 2023 - в издания, индексирани в Scopus и/или Web of Science
    2. Masgo Ventura H.K., Bacalla Tenorio J., Santa Cruz Acosta R.C., Inga Merino V.G., Lobaton Arenas C.L., Ferro P., Ticona Chayna E., Marchena-Dioses J., Sanchez-Santillan T., Morales-Rojas E., Automated Classification and Explainability of Cedar (Cedrela montana) and Cinchona (Cinchona pubescens) Using Deep Learning and Grad-CAM: A Case Study in the Amazon Region of Northern Peru, 2026, Forests, issue 7, vol. 17, DOI 10.3390/f17070779, eissn 19994907 - 2026 - в издания, индексирани в Scopus

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus