Auswahl der wissenschaftlichen Literatur zum Thema „Weight labels“
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Zeitschriftenartikel zum Thema "Weight labels"
Wang, Zhe, Hao Xu, Pan Zhou und Gang Xiao. „An Improved Multilabel k-Nearest Neighbor Algorithm Based on Value and Weight“. Computation 11, Nr. 2 (13.02.2023): 32. http://dx.doi.org/10.3390/computation11020032.
Der volle Inhalt der QuelleHaunert, Jan-Henrik, und Alexander Wolff. „BEYOND MAXIMUM INDEPENDENT SET: AN EXTENDED MODEL FOR POINT-FEATURE LABEL PLACEMENT“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (07.06.2016): 109–14. http://dx.doi.org/10.5194/isprs-archives-xli-b2-109-2016.
Der volle Inhalt der QuelleHaunert, Jan-Henrik, und Alexander Wolff. „BEYOND MAXIMUM INDEPENDENT SET: AN EXTENDED MODEL FOR POINT-FEATURE LABEL PLACEMENT“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (07.06.2016): 109–14. http://dx.doi.org/10.5194/isprsarchives-xli-b2-109-2016.
Der volle Inhalt der QuelleWang, Wanzhu, und Yong Liu. „Multi-label Feature Selection based on Label-specific features and Manifold Learning“. Academic Journal of Science and Technology 10, Nr. 1 (27.03.2024): 364–69. http://dx.doi.org/10.54097/astymd16.
Der volle Inhalt der QuelleZhang, Yaojie, Huahu Xu, Junsheng Xiao und Minjie Bian. „JoSDW: Combating Noisy Labels by Dynamic Weight“. Future Internet 14, Nr. 2 (02.02.2022): 50. http://dx.doi.org/10.3390/fi14020050.
Der volle Inhalt der QuelleA. S., Saranya, und Santhosh Kumar K. R. „On the total edge irregularity strength of certain classes of cycle related graphs“. Proyecciones (Antofagasta) 43, Nr. 1 (20.03.2024): 53–67. http://dx.doi.org/10.22199/issn.0717-6279-5728.
Der volle Inhalt der QuelleEssayli, Jamal H., Jessica M. Murakami, Rebecca E. Wilson und Janet D. Latner. „The Impact of Weight Labels on Body Image, Internalized Weight Stigma, Affect, Perceived Health, and Intended Weight Loss Behaviors in Normal-Weight and Overweight College Women“. American Journal of Health Promotion 31, Nr. 6 (23.08.2016): 484–90. http://dx.doi.org/10.1177/0890117116661982.
Der volle Inhalt der QuelleKaraca, Adeviyye, Kamil Can Akyol, Mustafa Keşaplı, Faruk Güngör, Umut Cengiz Çakır, Angelika Janitzky und Ramazan Güven. „Do Clothing Labels Play a Role for Weight Estimation in Pediatric Emergencies? A Prospective, Cross-Sectional Study“. Prehospital and Disaster Medicine 36, Nr. 3 (26.02.2021): 295–300. http://dx.doi.org/10.1017/s1049023x21000194.
Der volle Inhalt der QuelleLiu, Jinghua, Songwei Yang, Hongbo Zhang, Zhenzhen Sun und Jixiang Du. „Online Multi-Label Streaming Feature Selection Based on Label Group Correlation and Feature Interaction“. Entropy 25, Nr. 7 (17.07.2023): 1071. http://dx.doi.org/10.3390/e25071071.
Der volle Inhalt der QuelleO’Connor, Alan. „Habitus and field: Punk record labels in Spain“. Punk & Post Punk 10, Nr. 2 (01.06.2021): 265–89. http://dx.doi.org/10.1386/punk_00071_1.
Der volle Inhalt der QuelleDissertationen zum Thema "Weight labels"
Chazelle, Thomas. „Influence sociale sur la représentation corporelle : Approche expérimentale de l'effet des médias et des labels de poids sur des jugements de corpulence“. Electronic Thesis or Diss., Université Grenoble Alpes, 2023. http://www.theses.fr/2023GRALS063.
Der volle Inhalt der QuelleBody representation is the set of cognitive functions that track the state of the body. It is involved in a variety of situations, such as the perception of the physical dimensions of the body, action, and the generation of attitudes towards the body. To perform these functions, it relies on the flexible use of a range of sensorimotor information, as well as on the individual's beliefs, expectations and emotions. Among the sources of information available about the body, social influence can be a risk, maintenance, and severity factor in body image distortions. However, while social influence on the attitudinal aspects of body representation is well established, there is little experimental evidence of such influence on its perceptual aspects. The aim of this thesis is to study the integration of social information into the perceptual dimension of the representation of body size. To this end, we conducted a series of experiments with young women, a demographic that is particularly prone to distortions of body representation. A first axis focuses on interpersonal influence by testing the effect of weight labels on perceptual judgments. To investigate their informational influence, we manipulated the reliability of multiple cues to study how they were combined. Our results indicate that weight labels have a limited influence on judgments of body size. A second axis focuses on another type of social influence, media influence. Visual overexposure to specific body types is associated with body dissatisfaction, and could help explain the perceptual and attitudinal distortions of body representation. In this context, visual adaptation to bodies could explain how prolonged exposure to thin bodies can lead to an overestimation of one's own body size. We tested some of the hypotheses of this adaptation theory of body image distortion. These experiments highlight some limitations of the adaptation account; in particular, it is uncertain whether adaptation effects can influence the representation that individuals have of their own bodies. In conclusion, our results suggest that the perceptual dimension of the representation of body size may be resistant to some types of interpersonal and media social influence
Araújo, Olegário da Cruz de. „In-store attractiveness of national brands and private labels in an emerging market“. reponame:Repositório Institucional do FGV, 2018. http://hdl.handle.net/10438/20705.
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Emerging markets are considered relevant for international manufacturers and retailers to grow their turnovers. In order to achieve their goals, manufacturers and retailers are executing different initiatives to attract new customers such as in-store promotions. However, both in the US and here in Brazil, the results of these actions are questioned. Retailers are also investing in their Private Labels (PLs), which can alter the competitive dynamics within the categories. In the United States and Europe, studies were conducted to assess in-store promotions, impulses and responses in short-term and long-term sales for National Brands (NBs) and also Private Labels (PLs). The research question of this study was to evaluate if in Brazil, an emerging market, the attractiveness of Weighted Distribution, Price and Promotions of National Brands and Private Labels provide similar responses to the impulses. In order to evaluate if the impulses provide long-term residual effects for National Brands (NBs) and Private Labels (PLs), Vectors of Auto Regression (VAR) model was used in a continuous panel of self-service food stores in Greater São Paulo, which is the main metropolitan region of Brazil. The databases by categories (powdered coffee, biscuit, and ready-to-serve fruit juice) contained information of 25 months (November 2013 to November 2015) for each variable (Weighted Distribution, Price and Promotions), by NBs and PLs. The result of this study points out that there is a difference in responses to the impulses (distribution, price, and promotions) between NBs and PLs. National Brands (NBs) showed a greater number of situations with positive residual effects on long-term sales. However, the long-term response on sales occurred only for less than the half of the total potential situations. In other words, more than half of the total potential situations give an absence of statistical significance. The study indicates that there are retailers developing differentiated actions with Private Labels and obtaining, in their sales, positive long-term residual effects. Although modestly, this study contributes to the retail literature by using an econometric model (VAR) to analyze the impulse in some in-store attractiveness variables their long-term sales response to NBs and PLs in an emerging market. In short, the main contribution from the observations of the analyzed categories is that it is possible to Private Label compete without price sensibility and also positioning PL above the average price of the category/segment. The results also suggest that there is an opportunity to review the modus operandi of in-store promotion to get better results.
Mercados emergentes são importantes para as receitas totais de fabricantes e varejistas internacionais. Estudos de companhias globais de pesquisa, que atuam no Brasil, apontam que os investimentos em ações promocionais no ponto-de-venda, pelas Marcas de Fabricantes, aumentaram, mas há questionamentos quanto ao retorno destas iniciativas. Os varejistas também têm investido em Marcas Próprias. Nos Estados Unidos e Europa há vários estudos sobre o estímulos dentro do ponto-de-venda para as Marcas dos Fabricantes e Marcas Próprias e o impacto nas vendas no curto e longo prazo. O objetivo central deste estudo é avaliar se, em um mercado emergente, o nivel de atratividade das ações realizadas pelas Marcas de Fabricantes e Marcas Próprias dentro das lojas proporcionam respostas similares de curto e longo prazo aos impulsos realizados. Para analisar os efeitos destes impulsos foi utilizado o modelo de Vetores de Auto Regressão (VAR) em um painel continuo de lojas de autosserviço alimentar, na principal região metropolitana do Brasil, a Grande São Paulo. As bases de dados por categoria (Café em Pó, Biscoito e Suco Pronto para Consumo), continham informações de 25 meses (novembro de 2013 à novembro de 2015), com dados de distribuição ponderada, preço e promoções, O resultado deste estudo aponta que há diferenças entre Marcas de Fabricantes e Marcas Próprias nas respostas de longo prazo aos estímulos promocionais. Embora as Marcas de Fabricantes tenham apresentado um maior número de situações com efeitos residuais positivos nas vendas de longo prazo do que as Marcas Próprias, apenas menos da metade das situações apresentaram resultados de longo prazo. O estudo também sinaliza que há varejistas desenvolvendo ações diferenciadas com Marcas Próprias e obtendo, em suas vendas, efeitos residuais positivos de longo prazo, na mesma intensidade das Marcas de Fabricantes. Embora de forma modesta, esta pesquisa contribui para a literatura ao utilizar um modelo econométrico (VAR) para analisar os impulsos aplicados em distribuição, preço e promoção das Marcas dos Fabricantes e das Marcas Próprias em um mercado emergente. A principal contribuição deste estudo, a partir das categorias analisadas, é que a Marca Própria, não necessariamente, precisa atuar apenas com um posicionamento de preço baixo e/ou reduzir preços para competir dentro da categoria ou segmento no qual está inserida. Além disto, o estudo também sugere que as há espaço para rever as práticas promocionais ou até operacionais, considerando o baixo retorno proporcionado para Marcas de Fabricantes e Marcas Próprias.
Simmons, Mark R. „Comparison of Weight Loss Outcome Measures in Adolescent Bariatric Surgery Patients using Growth Curve Modeling“. University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447689830.
Der volle Inhalt der QuelleBaier, Moritz C. [Verfasser]. „Living Polymerization to Ultra-High Molecular Weight and Dye-Labeled Polyethylene for Single-Molecule Fluorescence Microscopy and Reactor Blends / Moritz C. Baier“. Konstanz : Bibliothek der Universität Konstanz, 2016. http://d-nb.info/1173616454/34.
Der volle Inhalt der QuelleSarinnapakorn, Kanoksri. „Induction of Classifiers from Multi-labeled Examples: an Information-retrieval Point of View“. Scholarly Repository, 2007. http://scholarlyrepository.miami.edu/oa_dissertations/16.
Der volle Inhalt der QuelleMohammed, Kader Hamno. „Development of a label-free biosensor method for the identification of sticky compounds which disturb GPCR-assays“. Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-220645.
Der volle Inhalt der QuelleMata, Jutta. „Healthy food choice“. Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2008. http://dx.doi.org/10.18452/15723.
Der volle Inhalt der QuelleThis dissertation focuses on food-related decision making, in particular, how food related environments and cognition interact to determine people’s food choices. The first manuscript, “When Diets Last: Lower Cognitive Complexity Increases Diet Adherence,” investigates the role of the cognitive complexity in diet adherence. Can weight loss diets fail because they are too complicated from a cognitive point of view, meaning that dieters are not able to recall or process the diet rules? The impact of excessive cognitive demands on diet adherence were investigated with 1,136 dieters in a longitudinal online-questionnaire. We measured perceived rule complexity controlling for other factors known to influence adherence. Previous diet behavior, self-efficacy, planning and perceived rule complexity predicted an increased risk to quit the diet prematurely, with self-efficacy and diet complexity being the strongest factors. The second manuscript, “Meat Label Design: Effects on Stage Progression, Risk Perception, and Product Evaluation,” presents two studies which tested the impact of health-related meat labels on product evaluation and intention. Specifically, the studies examined how informational content and the context (separate vs. conjoint evaluation) in which labels are assessed influence the evaluation of meat products. The results showed that conjoint assessment of labels can lead to contrary product rankings compared to separate evaluations. Moreover, the results suggest that being exposed to food labels containing specific health-relevant information can increase motivation to consider health aspects in those consumers without previous intention to do so. The third manuscript, “Predicting Children’s Meal Preferences: How Much Do Parents Know?” investigated prediction behavior concerning other people’s food choices. In particular, it asked how accurately and what cues parents use to predict their children’s meal choices. Overall, parents’ prediction accuracy matched the stability of children’s meal choices, implying that accuracy was as high as can be expected. The results suggest parents were able to obtain high predictive accuracy by using specific knowledge about their child’s likes and projecting their own preferences.
McKinnon, Loretta Carmen. „The contribution of psychosocial factors to socioeconomic differences in food purchasing“. Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/60893/1/Loretta_McKinnon_Thesis.pdf.
Der volle Inhalt der QuelleVillars, Clément. „Mesure objective de l’activité physique en conditions de vie libre et relations avec l’adiponectine“. Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10301/document.
Der volle Inhalt der QuelleAccurate measurements of physical activity in free living are needed to establish what dose of physical activity is necessary for obtaining a specific health benefits. The first aim of this work was to validate the Actiheart (which combines heart rate and accelerometry sensors) with doubly labeled water (DLW). We show a good level of concordance between physical activity energy expenditure (PAEE) estimated by Actiheart and DLW. Individualization of the relationship between heart rate and PAEE by an incremental test is needed for an accurate estimate of the PAEE at the individual level and to evaluate changes induced by an intervention. In laboratory, we show that the accuracy of Actiheart is activitydependent. This requires the establishment of their recognition from new sensors and mathematical models. Adiponectin, hormone secreted by adipose tissue, has a role in energy metabolism and its secretion decreases with obesity. However the effects of physical activity remain in contradiction in published studies. The second objective of this work was to evaluate the effect of physical activity and intervention with weight control on plasma adiponectin. We show that the total and high molecular weight adiponectin were negatively associated with modifications of the physical activity level. Further work is however necessary to understand the mechanisms underlying this modulation of plasma adiponectin which does not seem related to changes in synthesis in adipose tissue or muscle
Chen, Kuan-Tzu, und 陳冠慈. „The Impact of Reading Food Nutrition Labels for Weight Control on Working Adults’Body Mass Index“. Thesis, 2012. http://ndltd.ncl.edu.tw/handle/70805620037973064829.
Der volle Inhalt der Quelle國立臺灣大學
健康政策與管理研究所
101
Overweight and obesity is the world''s fifth largest cause of death risk, WHO also estimated that there are at least 2.8 million adults died of overweight or obese. According to the Department of Health, Executive Yuan, R.O.C (Taiwan), "2005-2008 National Nutrition and Health Survey" results of adult overweight and obesity rate of 44.1%, 50.8% were male. Women accounted for 36.9%. 2008 survey by the Ministry of Education student height and weight data show that one in four children are overweight or obese. Overweight and obese has become a health problem. Most of the overweight or obese are cause from diet and physical activity in global, so we focus on the effect of nutrition label using on Body Mass Index BMI. In order to provide obesity prevention and treatment plan at the future. Using 2005 National Health Interview Survey (NHIS), 18 to 64 year-old samples, 4585 female, 6219 male, include basic personal information, self-report height and weight, health behavior, the economic situation, and the health behavior in the food nutrition label reading. We use Propensity Score Matching (PSM) to control other variables. Results showed that the factor of reading food nutrition labels in gender is slightly different. The using of nutrition labels is relative to higher social-economic status, healthy eating behavior, less high-calorie and high sugar eating patterns. The food nutrition using is a part of health behavior, but we found that the user have higher BMI than the other. Government agencies should pay attention to people recommended nutrient intake for cognitive education and related policy implementation, as a health promote information.
Bücher zum Thema "Weight labels"
Brazil. Serviço Nacional de Aprendizagem Industrial. Departamento Nacional. Coletânea de portarias de produtos pré-medidos. Brasília: CNI SENAI, 2000.
Den vollen Inhalt der Quelle findenDay, Gloria. Weight of Labels: A Poetic Display of an Internal Shift. Lulu Press, Inc., 2018.
Den vollen Inhalt der Quelle findenRadman-Livaja, Ivan. Prices and Costs in the Textile Industry in the Light of the Lead Tags from Siscia. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198790662.003.0013.
Der volle Inhalt der QuelleYoung, Deborah E. Swatch Reference Guide for Fashion Fabrics: 5th Edition. 5. Aufl. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9781501373206.
Der volle Inhalt der QuelleZoumbaris, Sharon K., und Marjolijn Bijlefeld. Food and You. Greenwood, 2001. http://dx.doi.org/10.5040/9798400652301.
Der volle Inhalt der QuelleKirchman, David L. Degradation of organic matter. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789406.003.0007.
Der volle Inhalt der QuelleMillan, John. Coins Weights & Measures, Ancient & Modern, of All Nations. Reduced Into English on Above 100 Tables, Collected & Methodiz'd from Newton, Folkes, ... of Specific Gravities, by Newton, Labelye. Gale Ecco, Print Editions, 2018.
Den vollen Inhalt der Quelle findenSarkar, Ajoy K., Ingrid Johnson und Allen C. Cohen. J.J. Pizzuto’s Fabric Science Swatch Kit: 12th Edition. 12. Aufl. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9781501367892.
Der volle Inhalt der QuelleBuchteile zum Thema "Weight labels"
Shield, Andrew DJ. „“White is a color, Middle Eastern is not a color”: Drop-Down Menus, Racial Identification, and the Weight of Labels“. In Immigrants on Grindr, 185–225. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30394-5_6.
Der volle Inhalt der QuelleXu, Jianhua. „Multi-Label Weighted k-Nearest Neighbor Classifier with Adaptive Weight Estimation“. In Neural Information Processing, 79–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24958-7_10.
Der volle Inhalt der QuellePirouz, Matin. „Balanced Weighted Label Propagation“. In Lecture Notes in Networks and Systems, 1–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80126-7_1.
Der volle Inhalt der QuelleWang, Hongzhi, Jung Wook Suh, John Pluta, Murat Altinay und Paul Yushkevich. „Optimal Weights for Multi-atlas Label Fusion“. In Lecture Notes in Computer Science, 73–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22092-0_7.
Der volle Inhalt der QuelleYang, Lei, Zhan Shi, Dan Feng, Wenxin Yang, Jiaofeng Fang, Shuo Chen und Fang Wang. „MLND: A Weight-Adapting Method for Multi-label Classification Based on Neighbor Label Distribution“. In Web and Big Data, 639–54. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60259-8_47.
Der volle Inhalt der QuelleVerma, Gurudatta, und Tirath Prasad Sahu. „Exploring Label-Specific Feature Weights for Multi-label Feature Selection Using FWMABAC-MFS“. In Proceedings of 4th International Conference on Frontiers in Computing and Systems, 321–35. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2611-0_22.
Der volle Inhalt der QuelleSun, Chong, Weiyu Zhou, Zhongshan Song, Fan Yin, Lei Zhang und Jianquan Bi. „Weighted Multi-label Learning with Rank Preservation“. In Big Data, 312–24. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1899-7_22.
Der volle Inhalt der QuelleMohan, Anshuman, Wei Xiang Leow und Aquinas Hobor. „Functional Correctness of C Implementations of Dijkstra’s, Kruskal’s, and Prim’s Algorithms“. In Computer Aided Verification, 801–26. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81688-9_37.
Der volle Inhalt der QuelleWang, Xin, Songlei Jian, Kai Lu und Xiaoping Wang. „Unified Weighted Label Propagation Algorithm Using Connection Factor“. In Advanced Data Mining and Applications, 434–44. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49586-6_29.
Der volle Inhalt der QuelleWang, Lulu, Hong Shen und Hui Tian. „Weighted Ensemble Classification of Multi-label Data Streams“. In Advances in Knowledge Discovery and Data Mining, 551–62. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57529-2_43.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Weight labels"
Feng, Lei, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li und Bo An. „Can Cross Entropy Loss Be Robust to Label Noise?“ In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/305.
Der volle Inhalt der QuelleYang, Xu, Yanan Gu, Kun Wei und Cheng Deng. „Exploring Safety Supervision for Continual Test-time Domain Adaptation“. In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/183.
Der volle Inhalt der QuelleWu, Junshuang, Richong Zhang, Yongyi Mao, Hongyu Guo und Jinpeng Huai. „Modeling Noisy Hierarchical Types in Fine-Grained Entity Typing: A Content-Based Weighting Approach“. In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/731.
Der volle Inhalt der QuelleXiong, Feng, Jiayi Tian, Zhihui Hao, Yulin He und Xiaofeng Ren. „SCMT: Self-Correction Mean Teacher for Semi-supervised Object Detection“. In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/207.
Der volle Inhalt der QuelleKhangura, Jasan, Melanie Flores und Jane Ishmael. „Product text labels indicate the presence of other pharmacologically active ingredients in many OTC hemp- and CBD-containing preparations“. In 2021 Virtual Scientific Meeting of the Research Society on Marijuana. Research Society on Marijuana, 2022. http://dx.doi.org/10.26828/cannabis.2022.01.000.32.
Der volle Inhalt der QuelleZhang, Qian-Wen, Ximing Zhang, Zhao Yan, Ruifang Liu, Yunbo Cao und Min-Ling Zhang. „Correlation-Guided Representation for Multi-Label Text Classification“. In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/463.
Der volle Inhalt der QuelleWu, Yanan, He Liu, Songhe Feng, Yi Jin, Gengyu Lyu und Zizhang Wu. „GM-MLIC: Graph Matching based Multi-Label Image Classification“. In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/163.
Der volle Inhalt der QuelleXia, Shi-Yu, Jiaqi Lv, Ning Xu und Xin Geng. „Ambiguity-Induced Contrastive Learning for Instance-Dependent Partial Label Learning“. In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/502.
Der volle Inhalt der QuelleGoyal, Palash, Divya Choudhary und Shalini Ghosh. „Hierarchical Class-Based Curriculum Loss“. In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/337.
Der volle Inhalt der QuelleYin, Li'ang, Jianhua Han, Weinan Zhang und Yong Yu. „Aggregating Crowd Wisdoms with Label-aware Autoencoders“. In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/184.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Weight labels"
Cao, Shoufeng, Uwe Dulleck, Warwick Powell, Charles Turner-Morris, Valeri Natanelov und Marcus Foth. BeefLedger blockchain-credentialed beef exports to China: Early consumer insights. Queensland University of Technology, Mai 2020. http://dx.doi.org/10.5204/rep.eprints.200267.
Der volle Inhalt der QuelleAlonso, Pablo, Basil Kavalsky, Jose Ignacio Sembler, Hector Conroy, Salvatore Schiavo-Campo, Juan Manuel Puerta, Monika Huppi et al. How is the IDB Serving Higher-Middle-Income Countries?: Borrowers' Perspective. Inter-American Development Bank, Februar 2013. http://dx.doi.org/10.18235/0010547.
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