Artefact PARTICLE
Research on "artefact particle" spans diverse fields, focusing on improving the detection, classification, and analysis of particles, often within complex backgrounds or noisy data. Current efforts leverage machine learning, particularly convolutional neural networks and transformers, to enhance accuracy and efficiency in tasks such as object detection in images (e.g., microscopy, LiDAR), particle tracking in videos, and material characterization. These advancements have significant implications for various applications, including autonomous driving, materials science, high-energy physics, and medical imaging, by enabling more robust and automated analysis of complex datasets.
Papers
Biohybrid Microrobots Based on Jellyfish Stinging Capsules and Janus Particles for In Vitro Deep-Tissue Drug Penetration
Sinwook Park, Noga Barak, Tamar Lotan, Gilad Yossifon
Is Multiple Object Tracking a Matter of Specialization?
Gianluca Mancusi, Mattia Bernardi, Aniello Panariello, Angelo Porrello, Rita Cucchiara, Simone Calderara