Ditapis dengan
Low-cost real-time aerial object detection and GPS location tracking pipeline
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
Integrating multi-user digitising actions for mapping gully outlines using a …
Scalable and transferable methods for generating reliable reference data for automated remote sensing approaches are crucial, especially for mapping complex Earth surface processes such as gully erosion in low-populated and inaccessible areas. As an alternative for the labour-intense in-situ authoritative mapping, collaborative approaches enable volunteers to generate redundant independent geoi…
- Edisi
- Vol.12, April 2024
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 15 hlm PDF, 17.316 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Pol-InSAR-Island - A benchmark dataset for multi-frequency Pol-InSAR data lan…
This paper presents Pol-InSAR-Island, the first publicly available multi-frequency Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR) dataset labeled with detailed land cover classes, which serves as a challenging benchmark dataset for land cover classification. In recent years, machine learning has become a powerful tool for remote sensing image analysis. While there are numerou…
- Edisi
- Vol.10, December 2023
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 13 hlm PDF, 19,559 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Spatially autocorrelated training and validation samples inflate performance …
Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote sensing are becoming standard analytical tools in the geosciences. A series of studies has presented the seemingly outstanding performance of CNN for predictive modelling. However, the predictive performance of such models is commonly estimated using random cross-validation, which does not account for spat…
- Edisi
- Vol.5, August 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 10 hlm PDF, 5.589 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Detection of anomalous vehicle trajectories using federated learning
Nowadays mobile positioning devices, such as global navigation satellite systems (GNSS) but also external sensor technology like cameras allow an efficient online collection of trajectories, which reflect the behavior of moving objects, such as cars. The data can be used for various applications, e.g., traffic planning or updating maps, which need many trajectories to extract and infer the desi…
- Edisi
- Vol.4, April 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 12 hlm PDF, 3.981 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Comparison of neural networks and k-nearest neighbors methods in forest stand…
In the remote sensing of forests, point cloud data from airborne laser scanning contains high-value information for predicting the volume of growing stock and the size of trees. At the same time, laser scanning data allows a very high number of potential features that can be extracted from the point cloud data for predicting the forest variables. In some methods, the features are first extracte…
- Edisi
- Vol.4, April 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 17 hlm PDF, 13.215 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Deep learning : modernisasi machine learning untuk big data
Sejumlah perusahaan raksasa telah sukses membangun banyak aplikasi berbasis deep leraning (DL) yang inpresif, penuh keajaiban. Kesuksesan ini merupakan hasil kerja keras selama bertahun-tahun dalam membangun sistem-sistem berbasis DL, mulai dari gagasan, arsitektur model, teknik pembelajaran, hingga framework sampai dihasilkan performance yang mendekati, bahkan melebihi kemampuan manusia. Kons…
- Edisi
- -
- ISBN/ISSN
- 978-623-7131-21-2
- Deskripsi Fisik
- xiv, 249 hlm. : 24 cm.
- Judul Seri
- -
- No. Panggil
- 006.3 SUY d
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