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Am J Sports Med
January 2025
Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, New York, New York, USA.
IEEE Trans Pattern Anal Mach Intell
December 2024
Panoptic Part Segmentation (PPS) unifies panoptic and part segmentation into one task. Previous works utilize separate approaches to handle things, stuff, and part predictions without shared computation and task association. We aim to unify these tasks at the architectural level, designing the first end-to-end unified framework, Panoptic-PartFormer.
View Article and Find Full Text PDFFood Chem
December 2024
School of Materials and Chemical Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, PR China. Electronic address:
Herein, we have manufactured a newly designed bifunctional impedimetric and amperometric immunosensor for rapidly detecting erythromycin (ERY) in complicated environments and food stuffs. For this, bimetallic cobalt/cerium-layered double hydroxide nanosheets (CoCe-LDH NSs), which was derived from Co-based zeolite imidazole framework via the structure conversion, was simultaneously utilized as the bioplatform for anchoring the ERY-targeted antibody and for modifying the gold and screen printed electrode. Basic characterizations revealed that CoCe-LDH NSs was composed of mixed metal valences, enrich redox, and abundant oxygen vacancies, facilitating the adhesion on the electrode, the antibody adsorption, and the electron transfers.
View Article and Find Full Text PDFIEEE Trans Pattern Anal Mach Intell
December 2024
Panoptic Scene Graph (PSG) is a challenging task in Scene Graph Generation (SGG) that aims to create a more comprehensive scene graph representation using panoptic segmentation instead of boxes. Compared to SGG, PSG has several challenging problems: pixel-level segment outputs and full relationship exploration (It also considers thing and stuff relation). Thus, current PSG methods have limited performance, which hinders downstream tasks or applications.
View Article and Find Full Text PDFNeural Netw
November 2024
The College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, Zhejiang, China; Hangzhou Xsuan Technology Co., Ltd, Hangzhou, 310052, Zhejiang, China. Electronic address:
Unsupervised semantic segmentation is important for understanding that each pixel belongs to known categories without annotation. Recent studies have demonstrated promising outcomes by employing a vision transformer backbone pre-trained on an image-level dataset in a self-supervised manner. However, those methods always depend on complex architectures or meticulously designed inputs.
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