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Road terrain classification technology for autonomous vehicle

Nomor Panggil e20509864
Pengarang
Subjek
Penerbitan Singapore: Springer Nature, 2019
Kata Kunci :  
 Info Lainnya
Sumber Pengatalogan LibUI eng rda
Tipe Konten text
Tipe Media computer
Tipe Carrier online resource
Deskripsi Fisik xvi, 97 pages : illustration
Tautan https://doi.org/10.1007/978-981-13-6155-5
  • Ketersediaan
  • File Digital: 1
  • Ulasan
  • Sampul
  • Abstrak
Nomor Panggil No. Barkod Ketersediaan
e20509864 02-20-058536152 TERSEDIA
Ulasan:
Tidak ada ulasan pada koleksi ini: 20509864
This book provides cutting-edge insights into autonomous vehicles and road terrain classification, and introduces a more rational and practical method for identifying road terrain. It presents the MRF algorithm, which combines the various sensors classification results to improve the forward LRF for predicting upcoming road terrain types. The comparison between the predicting LRF and its corresponding MRF show that the MRF multiple-sensor fusion method is extremely robust and effective in terms of classifying road terrain. The book also demonstrates numerous applications of road terrain classification for various environments and types of autonomous vehicle, and includes abundant illustrations and models to make the comparison tables and figures more accessible.