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| 2. |
- Han, L., et al.
(författare)
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Cell transcriptomic atlas of the non-human primate Macaca fascicularis
- 2022
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Ingår i: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 604:7907, s. 723-731
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Tidskriftsartikel (refereegranskat)abstract
- Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell–cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.
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| 3. |
- Kristan, Matej, et al.
(författare)
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The first visual object tracking segmentation VOTS2023 challenge results
- 2023
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Ingår i: 2023 IEEE/CVF International conference on computer vision workshops (ICCVW). - : Institute of Electrical and Electronics Engineers Inc.. - 9798350307443 - 9798350307450 ; , s. 1788-1810
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking Segmentation VOTS2023 challenge is the eleventh annual tracker benchmarking activity of the VOT initiative. This challenge is the first to merge short-term and long-term as well as single-target and multiple-target tracking with segmentation masks as the only target location specification. A new dataset was created; the ground truth has been withheld to prevent overfitting. New performance measures and evaluation protocols have been created along with a new toolkit and an evaluation server. Results of the presented 47 trackers indicate that modern tracking frameworks are well-suited to deal with convergence of short-term and long-term tracking and that multiple and single target tracking can be considered a single problem. A leaderboard, with participating trackers details, the source code, the datasets, and the evaluation kit are publicly available at the challenge website1
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| 4. |
- Zhang, Huai, et al.
(författare)
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A global survey on the use of the international classification of diseases codes for metabolic dysfunction-associated fatty liver disease.
- 2024
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Ingår i: Hepatology international. - 1936-0541.
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Tidskriftsartikel (refereegranskat)abstract
- With the implementation of the 11th edition of the International Classification of Diseases (ICD-11) and the publication of the metabolic dysfunction-associated fatty liver disease (MAFLD) nomenclature in 2020, it is important to establish consensus for the coding of MAFLD in ICD-11. This will inform subsequent revisions of ICD-11.Using the Qualtrics XM and WJX platforms, questionnaires were sent online to MAFLD-ICD-11 coding collaborators, authors of papers, and relevant association members.A total of 890 international experts in various fields from 61 countries responded to the survey. We also achieved full coverage of provincial-level administrative regions in China. 77.1% of respondents agreed that MAFLD should be represented in ICD-11 by updating NAFLD, with no significant regional differences (77.3% in Asia and 76.6% in non-Asia, p=0.819). Over 80% of respondents agreed or somewhat agreed with the need to assign specific codes for progressive stages of MAFLD (i.e. steatohepatitis) (92.2%), MAFLD combined with comorbidities (84.1%), or MAFLD subtypes (i.e., lean, overweight/obese, and diabetic) (86.1%).This global survey by a collaborative panel of clinical, coding, health management and policy experts, indicates agreement that MAFLD should be coded in ICD-11. The data serves as a foundation for corresponding adjustments in the ICD-11 revision.
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| 6. |
- Bhat, Goutam, et al.
(författare)
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NTIRE 2022 Burst Super-Resolution Challenge
- 2022
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Ingår i: 2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2022). - : IEEE. - 9781665487399 - 9781665487405 ; , s. 1040-1060
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Konferensbidrag (refereegranskat)abstract
- Burst super-resolution has received increased attention in recent years due to its applications in mobile photography. By merging information from multiple shifted images of a scene, burst super-resolution aims to recover details which otherwise cannot be obtained using a simple input image. This paper reviews the NTIRE 2022 challenge on burst super-resolution. In the challenge, the participants were tasked with generating a clean RGB image with 4x higher resolution, given a RAW noisy burst as input. That is, the methods need to perform joint denoising, demosaicking, and super-resolution. The challenge consisted of 2 tracks. Track 1 employed synthetic data, where pixel-accurate high-resolution ground truths are available. Track 2 on the other hand used real-world bursts captured from a handheld camera, along with approximately aligned reference images captured using a DSLR. 14 teams participated in the final testing phase. The top performing methods establish a new state-of-the-art on the burst super-resolution task.
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| 7. |
- Lei, Lei, et al.
(författare)
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Displacement Identification by Computer Vision for ConditionMonitoring of Rail Vehicle Bearings
- 2021
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 21:6
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Tidskriftsartikel (refereegranskat)abstract
- Bearings of rail vehicles bear various dynamic forces. Any fault of the bearing seriouslythreatens running safety. For fault diagnosis, vibration and temperature measured from the bogieand acoustic signals measured from trackside are often used. However, installing additional sensingdevices on the bogie increases manufacturing cost while trackside monitoring is susceptible toambient noise. For other application, structural displacement based on computer vision is widelyapplied for deflection measurement and damage identification of bridges. This article proposesto monitor the health condition of the rail vehicle bearings by detecting the displacement of boltson the end cap of the bearing box. This study is performed based on an experimental platform ofbearing systems. The displacement is monitored by computer vision, which can image real-timedisplacement of the bolts. The health condition of bearings is reflected by the amplitude of thedetected displacement by phase correlation method which is separately studied by simulation. Toimprove the calculation rate, the computer vision only locally focuses on three bolts rather thanthe whole image. The displacement amplitudes of the bearing system in the vertical direction arederived by comparing the correlations of the image’s gray-level co-occurrence matrix (GLCM). Forverification, the measured displacement is checked against the measurement from laser displacementsensors, which shows that the displacement accuracy is 0.05 mm while improving calculation rate by68%. This study also found that the displacement of the bearing system increases with the increase inrotational speed while decreasing with static load
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| 8. |
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| 9. |
- Pecunia, Vincenzo, et al.
(författare)
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Roadmap on energy harvesting materials
- 2023
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Ingår i: Journal of Physics. - : IOP Publishing. - 2515-7639. ; 6:4
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Tidskriftsartikel (refereegranskat)abstract
- Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.
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| 10. |
- Xu, Xu, et al.
(författare)
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Robust Gaze Point Estimation for Metaverse With Common Mode Features Suppression Network
- 2024
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Ingår i: IEEE transactions on consumer electronics. - : Institute of Electrical and Electronics Engineers (IEEE). - 0098-3063 .- 1558-4127. ; 70:1, s. 2090-2098
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Tidskriftsartikel (refereegranskat)abstract
- Gaze point estimation is an essential technology in extended reality devices, and plays a vital role in the metaverse with consumer health. A challenging issue is the great variation underlying the gaze-related encode information, which makes current methods difficult to generate gaze point with stable quality among different persons. To this end, we propose a robust framework to generate high-accuracy gaze point from appearance. Specifically, eyes and face regions are fused into network to enrich high-level features. Then, we develop a common mode features suppression network (CMFS-Net) to predict the gaze bias between the input image and standard image. It is based on the differential amplifier. In addition, a Point-Mean algorithm is designed to generate the estimated gaze point from candidate points. The performance of the CMFS-Net is evaluated on three gaze estimation datasets, GazePC, GazeCapture, and Rice TabletGaze. Among them, the GazePC is collected by ourselves which composes 41.25K images from 165 participants. Experimental results demonstrate that our model is effective and robust for appearance-based gaze point estimation, and has advantages over peer methods.
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