PERPUSTAKAAN BIG

  • Beranda
  • Informasi
  • Berita
  • Bantuan
  • Area Pustakawan
  • Area Anggota
  • Pilih Bahasa :
    Bahasa Arab Bahasa Bengal Bahasa Brazil Portugis Bahasa Inggris Bahasa Spanyol Bahasa Jerman Bahasa Indonesia Bahasa Jepang Bahasa Melayu Bahasa Persia Bahasa Rusia Bahasa Thailand Bahasa Turki Bahasa Urdu

Pencarian berdasarkan :

SEMUA Pengarang Subjek ISBN/ISSN Pencarian Spesifik

Pencarian terakhir:

{{tmpObj[k].text}}

Ditapis dengan

  • Tahun Penerbitan
    To
  • Ketersediaan
  • Lampiran
  • Tipe Koleksi
    Lihat Lebih Banyak
  • Format Fisik Dokumen
    Lihat Lebih Banyak
  • Lokasi
  • Bahasa
Ditemukan 5 dari pencarian Anda melalui kata kunci: subject="Real-time"
cover
Revolutionizing the future of hydrological science: Impact of machine learnin…
Komentar Bagikan
Rajib MaityAman SrivastavaSubharthi SarkarMohd Imran Khan

Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are revolutionizing hydrology, driving significant advancements in water resource management, modeling, and prediction. This review synthesizes cutting-edge developments, methodologies, and applications of AI-ML-DL across key hydrological processes. By critically evaluating these techniques against traditional models, w…

Edisi
Vol.24, December 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
16 hlm PDF, 2.174 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Deep learning for real-time P-wave detection: A case study in Indonesia’s e…
Komentar Bagikan
Sri WidiyantoroDadan RamdaniAjat SudrajatAdi WibowoLeni Sophia HelianiCecep PratamaDavid Prambudi SaharaMizan Bustanul Fuady BisriSidik Tri WibowoSatriawan Rasyid Purnama

Detecting seismic events in real-time for prompt alerts and responses is a challenging task that requires accurately capturing P-wave arrivals. This task becomes even more challenging in regions like Indonesia, where widely spaced seismic stations exist. The wide station spacing makes associating the seismic signals with specific even more difficult. This paper proposes a novel deep learning-ba…

Edisi
Vol.24, December 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
16 hlm PDF, 16.531 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Modeling river flow for flood forecasting: A case study on the Ter river
Komentar Bagikan
Fabián Serrano-LópezSergi Ger-RocaMaria SalamóJerónimo Hernández-González

Floods affect chronically many communities around the world. Their socioeconomic impact increases year-by-year, boosted by global warming and climate change. Combined with long-term preemptive measures, preparatory actions are crucial when floods are imminent. In the last decade, machine learning models have been used to anticipate these hazards. In this work, we model the Ter river (NE Spain),…

Edisi
Vol.23, September 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
12 hlm PDF, 2.425 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Low-cost real-time aerial object detection and GPS location tracking pipeline
Komentar Bagikan
Allan LagoSahaj PatelAditya Singh

Real-time object detection and tracking is an active area of aerial remote sensing research that enables many environmental and ecological monitoring and preservation applications. Despite the development of several solutions tailored for these specific applications, trade-offs between cost efficiency and feature richness persist. This paper proposes a lightweight, low-cost, and modular approac…

Edisi
Vol.13, August 2024
ISBN/ISSN
1872-8235
Deskripsi Fisik
8 hlm PDF, 7.920 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Semantic segmentation of raw multispectral laser scanning data from urban env…
Komentar Bagikan
Antero KukkoHarri KaartinenJuha HyyppJosef TaherMikael ReichlerPetri Manninen

Real-time semantic segmentation of point clouds has increasing importance in applications related to 3D city modelling and mapping, automated inventory of forests, autonomous driving and mobile robotics. Current state-of-the-art point cloud semantic segmentation methods rely heavily on the availability of 3D laser scanning data. This is problematic in regards of low-latency, real-time applicati…

Edisi
Vol.12, April 2024
ISBN/ISSN
1872-8235
Deskripsi Fisik
17 hlm PDF, 21.188 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
PERPUSTAKAAN BIG
  • Informasi
  • Layanan
  • Pustakawan
  • Area Anggota

Tentang Kami

Perpustakaan Badan Informasi Geospasial adalah perpustakaan yang dikelola oleh Badan Informasi Geospasial. Perpustakaan ini memiliki koleksi yang berkaitan dengan informasi geospasial dan literatur terkait lainnya.

Statistik Pengunjung Web

Hari Ini : 1 Pekan Terakhir : 1 Bulan Terakhir : Total Kunjungan :

Cari

masukkan satu atau lebih kata kunci dari judul, pengarang, atau subjek

Donasi untuk SLiMS Kontribusi untuk SLiMS?

© 2026 — Senayan Developer Community

Ditenagai oleh SLiMS
Pilih subjek yang menarik bagi Anda
  • Batas Wilayah
  • Ekologi
  • Fotogrametri
  • Geografi
  • Geologi
  • GIS
  • Ilmu Tanah
  • Kartografi
  • Manajemen Bencana
  • Oceanografi
  • Penginderaan Jauh
  • Peta
Icons made by Freepik from www.flaticon.com
Pencarian Spesifik