Deep learning for asteroids autonomous terrain relative navigation

A survey on deep learning in medical image analysis

Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.07.005 · Cited by 15,332 · see citing works

Flownet: Learning optical flow with convolutional networks

Dosovitskiy, A., Fischer, P., Ilg, E., Hausser, P., Hazirbas, C., Golkov, V., Smagt, P. V. D., Cremers, D., & Brox, T. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.316 · Cited by 4,313 · see citing works

Learning a Similarity Metric Discriminatively, with Application to Face Verification

Chopra, S., Hadsell, R., & LeCun, Y. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.202 · Cited by 4,036 · see citing works

Learning to compare image patches via convolutional neural networks

Zagoruyko, S., & Nikos Komodakis, A. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7299064 · Cited by 1,540 · see citing works

Pruning and quantization for deep neural network acceleration: A survey

Liang, T., Glossner, J., Wang, L., Shi, S., & Zhang, X. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.07.045 · Cited by 969 · see citing works

Discriminative Learning of Deep Convolutional Feature Point Descriptors

Simo‐Serra, E., Trulls, E., Ferraz, L., Kokkinos, I., Fua, P., & Moreno-Noguer, F. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.22 · Cited by 804 · see citing works

OSIRIS-REx: Sample Return from Asteroid (101955) Bennu

LAURETTA, D. S., Balram-Knutson, S. S., Beshore, E. C., Boynton, W. V., d’Aubigny, C. D., DellaGiustina, D. N., Enos, H., Golish, D. R., Hergenrother, C. W., Howell, E. S., et al. (2017) · Space Science Reviews · doi:10.1007/s11214-017-0405-1 · Cited by 664 · see citing works

Template matching using fast normalized cross correlation

Briechle, K., & Hanebeck, U. D. (2001) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.421129 · Cited by 542 · see citing works

The unexpected surface of asteroid (101955) Bennu

The OSIRIS-REx Team, LAURETTA, D. S., DellaGiustina, D. N., Bennett, C. A., Golish, D. R., Becker, K. J., Balram-Knutson, S. S., Barnouin, O. S., Becker, T. L., Bottke, W. F., et al. (2019) · Nature · doi:10.1038/s41586-019-1033-6 · Cited by 539 · see citing works

2014 Science and Information Conference

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Learning by Tracking: Siamese CNN for Robust Target Association

Leal-Taixe, L., Canton-Ferrer, C., & Schindler, K. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2016.59 · Cited by 444 · see citing works

Deep learning-based image recognition for autonomous driving

Fujiyoshi, H., Hirakawa, T., & Yamashita, T. (2019) · IATSS Research · doi:10.1016/j.iatssr.2019.11.008 · Cited by 439 · see citing works

Hayabusa2 Mission Overview

Watanabe, S., Tsuda, Y., Yoshikawa, M., Tanaka, S., Saiki, T., & Nakazawa, S. (2017) · Space Science Reviews · doi:10.1007/s11214-017-0377-1 · Cited by 362 · see citing works

TinyML Meets IoT: A Comprehensive Survey

Dutta, L., & Bharali, S. (2021) · Internet of Things · doi:10.1016/j.iot.2021.100461 · Cited by 342 · see citing works

A review of cooperative and uncooperative spacecraft pose determination techniques for close-proximity operations

Opromolla, R., Fasano, G., Rufino, G., & Grassi, M. (2017) · Progress in Aerospace Sciences · doi:10.1016/j.paerosci.2017.07.001 · Cited by 330 · see citing works

Hayabusa—Its technology and science accomplishment summary and Hayabusa-2

Kawaguchi, J., Fujiwara, A., & Uesugi, T. (2008) · Acta Astronautica · doi:10.1016/j.actaastro.2008.01.028 · Cited by 274 · see citing works

Overview of Terrain Relative Navigation Approaches for Precise Lunar Landing

Johnson, A. E., & Montgomery, J. F. (2008) · 2008 IEEE Aerospace Conference · doi:10.1109/aero.2008.4526302 · Cited by 169 · see citing works

High-Performance Embedded Computing in Space: Evaluation of Platforms for Vision-Based Navigation

Lentaris, G., Maragos, K., Stratakos, I., Papadopoulos, L., Papanikolaou, O., Soudris, D., Lourakis, M., Zabulis, X., González-Arjona, D., & Furano, G. (2018) · Journal of Aerospace Information Systems · doi:10.2514/1.i010555 · Cited by 122 · see citing works

2020 International Conference for Emerging Technology (INCET)

(2020) · doi:10.1109/incet49848.2020 · Cited by 109 · see citing works

Dual-Path Siamese CNN for Hyperspectral Image Classification With Limited Training Samples

Huang, L., & Chen, Y. (2020) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2020.2979604 · Cited by 104 · see citing works

Sketching out the details: Sketch-based image retrieval using convolutional neural networks with multi-stage regression

Bui, T., Ribeiro, L., Ponti, M. A., & Collomosse, J. P. (2018) · Computers & Graphics · doi:10.1016/j.cag.2017.12.006 · Cited by 94 · see citing works

Compact descriptors for sketch-based image retrieval using a triplet loss convolutional neural network

Bui, T., Ribeiro, L., Ponti, M. A., & Collomosse, J. P. (2017) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2017.06.007 · Cited by 86 · see citing works

Accelerating Neural Network Inference on FPGA-Based Platforms—A Survey

Wu, R., Guo, X., Du, J., & Li, J. (2021) · Electronics · doi:10.3390/electronics10091025 · Cited by 79 · see citing works

Lessons learned from OSIRIS-REx autonomous navigation using natural feature tracking

Lorenz, D. A., Olds, R., May, A., et al. (2017) · Proceedings - IEEE Aerospace Conference · doi:10.1109/aero.2017.7943684 · Cited by 71 · see citing works

Overview of Image Matching Based on ORB Algorithm

Luo, C. W., Yang, W. P., Huang, P., & Zhou, J. W. (2019) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1237/3/032020 · Cited by 71 · see citing works

Image-based autonomous navigation of Hayabusa2 using artificial landmarks: The design and brief in-flight results of the first landing on asteroid Ryugu

Ogawa, N., Terui, F., Mimasu, Y., et al. (2020) · Astrodynamics · doi:10.1007/s42064-020-0070-0 · Cited by 60 · see citing works

Rosetta Lander – Philae: Landing preparations

Ulamec, S., Biele, J., Blazquez, A., et al. (2014) · Acta Astronautica · doi:10.1016/j.actaastro.2014.11.019 · Cited by 54 · see citing works

Retrieval of brain MRI with tumor using contrastive loss based similarity on GoogLeNet encodings

Deepak, S., & Ameer, P. M. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.103993 · Cited by 54 · see citing works

Vision-based guidance, navigation, and control of Hayabusa spacecraft - Lessons learned from real operation -

Hashimoto, T., Kubota, T., Kawaguchi, J., et al. (2010) · IFAC Proceedings Volumes · doi:10.3182/20100906-5-jp-2022.00045 · Cited by 28 · see citing works

A deep learning approach for optical autonomous planetary relative terrain navigation

Campbell, T. S., Furfaro, R., Linares, R., & Gaylor, D. E. (2017) · Cited by 13 · see citing works

A Configurable Architecture for Running Hybrid Convolutional Neural Networks in Low-Density FPGAs

Véstias, M. P., Duarte, R. P., de Sousa, J. T., & Neto, H. C. (2020) · IEEE Access · doi:10.1109/access.2020.3000444 · Cited by 13 · see citing works

Recovery of Bennu’s orientation for the OSIRIS-REx mission: implications for the spin state accuracy and geolocation errors

Mazarico, E., Rowlands, D. D., Sabaka, T. J., et al. (2017) · Journal of Geodesy · doi:10.1007/s00190-017-1058-2 · Cited by 12 · see citing works

Probabilistic regression for autonomous terrain relative navigation via multi-modal feature learning

Kim, I., & Singh, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-81377-z · Cited by 6 · see citing works

Autonomous Navigation via a Cascading CNN Framework Leveraging Synthetic Terrain Images

Rolen, A., & Singh, S. (2023) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-47969-4_41 · Cited by 2 · see citing works

Improved SINS/CNS Integrated Navigation System with Fault Detection Based on Statistical Distance

Gao, G., Gao, S., Peng, X., et al. (2019) · IEEE International Conference on Unmanned Systems (ICUS) · doi:10.1109/icus48101.2019.8995916 · Cited by 1 · see citing works

Principle of Navigation by CNS and Research on SINS/CNS Integrated Navigation System

Cui, N. (2007) · Journal of Nanjing University of Science and Technology · Cited by 2 · see citing works

Simulation analysis of CNS/SINS integrated navigation system

Zhi-yua, H. (2013) · Engineering of Surveying and Mapping

Design of all-weather celestial navigation system

Du, H., Hongchi, S., Mu, R., et al. (2018) · Young Scientists Forum 2017 · doi:10.1117/12.2317547

Research on the airborne SINS/CNS integrated navigation system assisted by BD navigation system

Xie, M., Yang, X., Han, J., et al. (2016) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2229568 · Cited by 4 · see citing works