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- Kristanl, Matej, et al.
(författare)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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| 2. |
- Wang, Ying, et al.
(författare)
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Preliminary exploration of hsa_circ_0032131 levels in peripheral blood as a potential diagnostic biomarker of osteoarthritis
- 2019
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Ingår i: Genetic Testing and Molecular Biomarkers. - : Mary Ann Liebert. - 1945-0265 .- 1945-0257. ; 23:10, s. 717-721
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Tidskriftsartikel (refereegranskat)abstract
- Background: Osteoarthritis (OA) is a common chronic degenerative joint disease characterized by articular cartilage degeneration and synovitis. CircRNAs are increasingly being recognized as functional endogenous RNAs with a stable structure and high tissue specificity. Recent studies have shown that some circRNAs may be involved in the initiation and progression of OA and that there is differential expression of circRNAs in chondrocytes in vitro isolated from patients with OA.Purposes: In this study, we aimed to determine if circRNA levels in the peripheral blood of Chinese Han patients with OA would be diagnostic based on the previous in vitro studies.Methods: We collected peripheral blood samples from 25 patients suffering from OA and 25 healthy controls and measured hsa_circ_0032131_CBC1 RNA levels through quantitative RT-PCR (qRT-PCR). The statistical basis for evaluating the diagnostic value was to calculate the area under the receiver operator characteristic (ROC) curve.Results: The results of the qRT-PCR for hsa_circ_0032131_CBC1 were consistent with those of the microarray analysis. The ROC curve shows that hsa_circ_0032131 holds diagnostic value for OA (0.8455, p < 0.01).Conclusions: Our research indicates that differentially expressed circRNAs may be involved in the development of OA and could be used diagnostically.
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| 3. |
- Wang, Ying, et al.
(författare)
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Screening for Differentially Expressed Circular RNAs in the Cartilage of Osteoarthritis Patients for Their Diagnostic Value
- 2019
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Ingår i: Genetic Testing and Molecular Biomarkers. - : Mary Ann Liebert. - 1945-0265 .- 1945-0257. ; 23:10, s. 706-716
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Tidskriftsartikel (refereegranskat)abstract
- Background: Osteoarthritis (OA) is the most prevalent osteoarticular disease, which typically involves chronic cartilage degeneration and synovitis. The latest research shows that circular RNAs (circRNAs) play a role in the development of a variety of diseases, including osteoarthrosis.Purposes: The aim of this study was to explore the expression of circRNAs in OA chondrocytes and predict biomarkers for diagnosis.Materials and Methods: The circRNA expression profile was analyzed through use of the Gene Spring software V13.0; differentially expressed circRNAs were screened by comparing OA chondrocytes and normal articular chondrocytes. We validated the microarray data by quantitative real-time polymerase chain reaction analyses of OA chondrocytes and chondrocytes from normal controls. TargetScan software and miRanda software were used to predict networks of circRNA–miRNA interactions in cartilage. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) analyses were applied to predict the functions of differentially expressed circRNAs.Results: Overall, 1380 circRNAs were differentially expressed between OA chondrocytes and normal articular chondrocytes (fold-change ≥2, p ≤ 0.05), including 215 that were upregulated and 1165 that were downregulated circRNAs. After analyzing the differentially expressed circRNA genes, the top 20 enriched GO entries and KEGG pathways were annotated. The hsa_circrna_0032131 was identified for further analysis. A circRNA–miRNA network was constructed to represent the 10 most likely target genes associated with the validated circRNA.Conclusions: Our research suggests that some of the differentially expressed circRNAs in OA chondrocytes compared to normal chondrocytes are etiologically associated with the pathological process of OA. It was found that hsa_circRNA_0032131 likely participates in the initiation and progression of OA and has potential as a diagnostic marker.Clinical Relevance: To analyze the difference of circRNA expression profiles between OA and normal controls and explore biomarkers for diagnosis.
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