IR measurements and image processing for enhanced-vision systems in civil aviation

2001 ◽  
Author(s):  
Kurt R. Beier ◽  
Jochen Fries ◽  
Rupert M. Mueller ◽  
Gintautas Palubinskas
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joan Carles Puchalt ◽  
Antonio-José Sánchez-Salmerón ◽  
Eugenio Ivorra ◽  
Silvia Llopis ◽  
Roberto Martínez ◽  
...  

AbstractTraditionally Caenorhabditis elegans lifespan assays are performed by manually inspecting nematodes with a dissection microscope, which involves daily counting of live/dead worms cultured in Petri plates for 21–25 days. This manual inspection requires the screening of hundreds of worms to ensure statistical robustness, and is therefore a time-consuming approach. In recent years, various automated artificial vision systems have been reported to increase the throughput, however they usually provide less accurate results than manual assays. The main problems identified when using these vision systems are the false positives and false negatives, which occur due to culture media changes, occluded zones, dirtiness or condensation of the Petri plates. In this work, we developed and described a new C. elegans monitoring machine, SiViS, which consists of a flexible and compact platform design to analyse C. elegans cultures using the standard Petri plates seeded with E. coli. Our system uses an active vision illumination technique and different image-processing pipelines for motion detection, both previously reported, providing a fully automated image processing pipeline. In addition, this study validated both these methods and the feasibility of the SiViS machine for lifespan experiments by comparing them with manual lifespan assays. Results demonstrated that the automated system yields consistent replicates (p-value log rank test 0.699), and there are no significant differences between automated system assays and traditionally manual assays (p-value 0.637). Finally, although we have focused on the use of SiViS in longevity assays, the system configuration is flexible and can, thus, be adapted to other C. elegans studies such as toxicity, mobility and behaviour.


Author(s):  
Szymon Szczęsny ◽  
Damian Huderek

This chapter discusses the concept of using Spiking Neural Networks (SNN), i.e. 3rd generation networks for image processing in UAV vision systems. The discussion concerns the complexity of various network models and basic limitations of hardware implementations of classifiers based on such networks. This chapter provides an example of classifying objects using SNN and discusses the implementation complexity of such networks.


Author(s):  
S. Muramatsu ◽  
Y. Otsuka ◽  
H. Takenaga ◽  
Y. Kobayashi ◽  
I. Furusawa ◽  
...  

2007 ◽  
Vol 56 (5) ◽  
pp. 1675-1687 ◽  
Author(s):  
Abdelhafid Elouardi ◽  
Samir Bouaziz ◽  
Antoine Dupret ◽  
Lionel Lacassagne ◽  
Jacques-Olivier Klein ◽  
...  

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