Kiri J. E. I. Walch`ile, Argentorati

http://tartu.ester.ee/record=b1880783~S1*es

Kiri tundmatule, Strasbourg

http://tartu.ester.ee/record=b1863654~S1*es

Industrial Segment Anything -- a Case Study in Aircraft Manufacturing, Intralogistics, Maintenance, Repair, and Overhaul

Deploying deep learning-based applications in specialized domains like the aircraft production industry typically suffers from the training data availability problem. Only a few datasets represent non-everyday objects, situations, and tasks. Recent advantages in research around Vision Foundation Models (VFM) opened a new area of tasks and models with high generalization capabilities in non-semantic and semantic predictions. As recently demonstrated by the Segment Anything Project, exploiting VFM's zero-shot capabilities is a promising direction in tackling the boundaries spanned by data, context, and sensor variety. Although, investigating its application within specific domains is subject to ongoing research. This paper contributes here by surveying applications of the SAM in aircraft production-specific use cases. We include manufacturing, intralogistics, as well as maintenance, repair, and overhaul processes, also representing a variety of other neighboring industrial domains. Besides presenting the various use cases, we further discuss the injection of domain knowledge

Plasmodium falciparum populations from northeastern Myanmar display high levels of genetic diversity at multiple antigenic loci

Levels of genetic diversity of the malaria parasites and multiclonal infections are correlated with transmission intensity. In order to monitor the effect of strengthened malaria control efforts in recent years at the China-Myanmar border area, we followed the temporal dynamics of genetic diversity of three polymorphic antigenic markers msp1, msp2, and glurp in the Plasmodium falciparum populations. Despite reduced malaria prevalence in the region, parasite populations exhibited high levels of genetic diversity. Genotyping 258 clinical samples collected in four years detected a total of 22 PCR size alleles. Multiclonal infections were detected in 45.7% of the patient samples, giving a minimum multiplicity of infection of 1.41. The majority of alleles experienced significant temporal fluctuations through the years. Haplotype diversity based on the three-locus genotypes ranged from the lowest in 2009 at 0.33 to the highest in 2010 at 0.80. Sequencing of msp1 fragments from 36 random samples of five allele size groups detected 13 different sequences, revealing an additional layer of genetic complexity. This study suggests that despite reduced prevalence of malaria infections in this region, the parasite population size and transmission intensity remained high enough to allow effective genetic recombination of the parasites and continued maintenance of genetic diversity

Towards Recognition of Human Actions in Collaborative Tasks with Robots: Extending Action Recognition with Tool Recognition Methods

This paper presents a novel method for online tool recognition in manual assembly processes. The goal was to develop and implement a method that can be integrated with existing Human Action Recognition (HAR) methods in collaborative tasks. We examined the state-of-the-art for progress detection in manual assembly via HAR-based methods, as well as visual tool-recognition approaches. A novel online tool-recognition pipeline for handheld tools is introduced, utilizing a two-stage approach. First, a Region Of Interest (ROI) was extracted by determining the wrist position using skeletal data. Afterward, this ROI was cropped, and the tool located within this ROI was classified. This pipeline enabled several algorithms for object recognition and demonstrated the generalizability of our approach. An extensive training dataset for tool-recognition purposes is presented, which was evaluated with two image-classification approaches. An offline pipeline evaluation was performed with twelve tool classes. Additionally, various online tests were conducted covering different aspects of this vision application, such as two assembly scenarios, unknown instances of known classes, as well as challenging backgrounds. The introduced pipeline was competitive with other approaches regarding prediction accuracy, robustness, diversity, extendability/flexibility, and online capability

CAMERAS 6. PERFORMING ORGANIZATION CODE

This study was conducted in cooperation with the U.S. Department of Transportation, Federal Highwa

Argentina sub Germanis

Échelle(s) : [1:11 140] Mensura 200 pert franc (3,5 cm)Appartient à l’ensemble documentaire : BNUStr007Appartient à l’ensemble documentaire : BNUStras