Готові списки джерел за темами / Category classification

Добірка наукової літератури з теми "Category classification"

Автор: Grafiati
Опубліковано: 14 березня 2023

Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями

Оберіть тип джерела:

Зміст

Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Category classification".

Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.

Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.

Статті в журналах з теми "Category classification"

1

&NA;. "Levemir granted pregnancy Category B classification." Reactions Weekly &NA;, no. 1397 (April 2012): 2. http://dx.doi.org/10.2165/00128415-201213970-00005.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

&NA;. "Pregnancy Category D classification for Myfortic." Inpharma Weekly &NA;, no. 1617 (December 2007): 17. http://dx.doi.org/10.2165/00128413-200716170-00051.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Kazan, Serap, and Hakan Karakoca. "Product Category Classification with Machine Learning." Sakarya University Journal of Computer and Information Sciences 2, no. 1 (April 30, 2019): 18–27. http://dx.doi.org/10.35377/saucis.02.01.523139.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Li, Luoqing, Chuanwu Yang, and Qiwei Xie. "1D embedding multi-category classification methods." International Journal of Wavelets, Multiresolution and Information Processing 14, no. 02 (March 2016): 1640006. http://dx.doi.org/10.1142/s0219691316400063.

Повний текст джерела
Анотація:
In this paper, we propose a novel semi-supervised multi-category classification method based on one-dimensional (1D) multi-embedding. Based on the multiple 1D embedding based interpolation technique, we embed the high-dimensional data into several different 1D manifolds and perform binary classification firstly. Then we construct the multi-category classifiers by means of one-versus-rest and one-versus-one strategies separately. A weight strategy is employed in our algorithm for improving the classification performance. The proposed method shows promising results in the classification of handwritten digits and facial images.
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Ross, Brian H., Susan A. Gelman, and Karl S. Rosengren. "Children's category-based inferences affect classification." British Journal of Developmental Psychology 23, no. 1 (March 2005): 1–24. http://dx.doi.org/10.1348/026151004x20108.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Yamauchi, Takashi, and Arthur B. Markman. "Category Learning by Inference and Classification." Journal of Memory and Language 39, no. 1 (July 1998): 124–48. http://dx.doi.org/10.1006/jmla.1998.2566.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Feroe, Aliya G., Rachel A. Flaugh, Tara A. Baxter, Aditi S. Majumdar, Patricia E. Miller, and Mininder S. Kocher. "Novel Mri Classification for Osteochondritis Dissecans of the Knee: A Validation Study." Orthopaedic Journal of Sports Medicine 10, no. 5_suppl2 (May 1, 2022): 2325967121S0041. http://dx.doi.org/10.1177/2325967121s00412.

Повний текст джерела
Анотація:
Background: A simpler three-category magnetic resonance imaging (MRI) classification system for osteochondritis dissecans (OCD) of the knee was recently shown to have comparable reliability to the existing five-category Hefti system. The validity and clinical utility of this simpler system as an alternative to the Hefti system has yet to be established. Hypothesis/Purpose: The purpose of this study was to assess whether a novel, simpler three-category MRI classification system for OCD of the knee demonstrates equal or better validity and correlates more strongly with treatment than the five-category Hefti classification. Methods: Demographic data and arthroscopic findings were collected from the medical and surgical records of 144 knees of children and adolescents with arthroscopically diagnosed knee OCD. MRI assessment of OCD lesions was conducted by two independent raters. Inter-rater reliability for novel and Hefti classifications was assessed by estimating weighted kappa ( kw). Agreement between MRI classification and arthroscopic findings was assessed by estimating kw coefficients. Classifications were dichotomized into 1,2 versus 3 for the novel system, and the sensitivity and specificity of classification was estimated as compared to arthroscopic findings. Correlation between arthroscopic classification and treatment type was assessed by estimating Spearman’s coefficient. Results: There was substantial interrater agreement with the proposed system’s ratings on MRI ( kw=0.66; 955 CI=0.56-0.75) and moderate agreement for Hefti system’s ratings on MRI ( kw=0.57; 955 CI=0.47-0.67) (Table 1). There was no difference detected in the agreement statistics for the proposed versus Hefti classifications (p=0.89). Binary agreement of the novel classification using dichotomous categories was slightly worse than the three-category classification. When 1&2s were combined, the agreement was moderate with k=0.41 (95% CI=0.25-0.58) and when 2&3s were combined, the agreement was fair with k=0.34 (95% CI=0.21-0.48). There was strong correlation between novel classification on arthroscopy with treatment type ( r=0.85; 95% CI = 0.80-0.89) and between Hefti classification and treatment type ( r=0.82; 95% CI = 0.75-0.86) (Table 2). Conclusion: The validity and clinical utility of the proposed three-category MRI classification system for knee OCD is comparable to that of the five-category Hefti system. This simpler classification system provides a foundation for the subsequent establishment of an operative treatment algorithm for knee OCD. [Table: see text][Table: see text]
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Ragab, Ahmed Refaat Sobhy Ahmed. "A New Classification for Ad-Hoc Network." International Journal of Interactive Mobile Technologies (iJIM) 14, no. 14 (August 28, 2020): 214. http://dx.doi.org/10.3991/ijim.v14i14.14871.

Повний текст джерела
Анотація:
<span>This paper focus on developing a new practical classification for ad-hoc networks, were all the past classifications revolve upon three main categories respectively, mobile ad- hoc network (MANET), Vehicle ad-hoc network (VANET) and Flying ad-hoc network (FANET). My new classification will illustrate Underwater vehicle ad-hoc network (UWVANET) as the fourth category in ad-hoc main classification, showing the powerful and the weakness of each category defined.</span>
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Amini, Massoud, George A. Elliott, and Nasser Golestani. "The Category of Bratteli Diagrams." Canadian Journal of Mathematics 67, no. 5 (October 1, 2015): 990–1023. http://dx.doi.org/10.4153/cjm-2015-001-8.

Повний текст джерела
Анотація:
AbstractA category structure for Bratteli diagrams is proposed and a functor from the category of AF algebras to the category of Bratteli diagrams is constructed. Since isomorphism of Bratteli diagrams in this category coincides with Bratteli’s notion of equivalence, we obtain in particular a functorial formulation of Bratteli’s classification of AF algebras (and at the same time, of Glimm’s classification of UHF algebras). It is shown that the three approaches to classification of AF algebras, namely, through Bratteli diagrams, K-theory, and a certain natural abstract classifying category, are essentially the same from a categorical point of view.
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Zhong, Jincheng, and Shuhui Chen. "Efficient multi-category packet classification using TCAM." Computer Communications 169 (March 2021): 1–10. http://dx.doi.org/10.1016/j.comcom.2020.12.027.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Дисертації з теми "Category classification"

1

Cai, Lijuan. "Multilabel classification over category taxonomies." View abstract/electronic edition; access limited to Brown University users, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3318298.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Watkins, Peter. "Classification of sheep category using chemical analysis and statistical classification algorithms." Thesis, Watkins, Peter (2011) Classification of sheep category using chemical analysis and statistical classification algorithms. PhD thesis, Murdoch University, 2011. https://researchrepository.murdoch.edu.au/id/eprint/6249/.

Повний текст джерела
Анотація:
In Australia, dentition (eruption of permanent incisors) is used as a proxy for age to define sheep meat quality. Lamb is defined as having no permanent incisors, hogget as having at least one incisor and mutton is defined as having two or more incisors. Classification of the carcase is done at the abattoir prior to the removal of an animal’s head. Recently, an Australian Senate inquiry into meat marketing reported that there was concern that substitution of hogget and mutton for lamb may be occurring in the industry. At present, no objective method is available that can be used for classifying sheep category. The general aims of this thesis were to i) evaluate whether chemical analysis of branched chain fatty acid (BCFA) content could be used as an objective tool to determine sheep age, ii) understand the effect that some production factors had on BCFA concentrations in Australian sheep and iii) develop new approaches (whether chemical and/or statistical) for determining sheep category (age). BCFAs are implicated as the main contributors to “mutton flavour”, often associated with the cooked meat of older animals. BCFAs are reported to increase with age, which suggests that chemical analysis of these compounds could be used as an objective method. Concentrations of three BCFAs (4-methyloctanoic (MOA), 4-ethyloctanoic (EOA) and 4- methylnonanoic (MNA) acids) were measured in a survey of fat samples taken from 533 sheep carcases at abattoirs in New South Wales, Victoria and Western Australia. This thesis shows that, on its own, chemical analysis of the BCFAs is not sufficient to discriminate lamb from hogget and mutton as pre-slaughter nutrition is a significant factor in classifying sheep using this approach. Uncertainty at the BCFA concentration ranges found in Australian sheep was determined to be high making it difficult to discriminate between sheep carcases of different ages based on the BCFA level. Fast gas chromatography was evaluated as the basis for a high throughput chemical technique but was not sufficiently sensitive for BCFA measurements. Solid-phase microextraction (SPME) was also found to be suitable for sampling 3-methylindole and p-cresol, compounds responsible for diet-related “pastoral flavour” in sheep fat, but further work is needed to validate this approach for measurement of these compounds in sheep fat. Statistical classification algorithms, when applied to the chromatograms measured for the 533 carcasses, showed great promise for predicting sheep category. Specifically, the random forests algorithm, when applied to mean-centred data, gave 100% predictive accuracy when differentiating between lamb, hogget and mutton. This approach could be used for the development of an objective method for determining sheep age and category, suitable for use by the Australian sheep meat industry.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Erdem, Ibrahim Aykut. "Category Knowledge, Skeleton-based Shape Matching And Shape Classification." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12610118/index.pdf.

Повний текст джерела
Анотація:
Skeletal shape representations, in spite of their structural instabilities, have proven themselves as effective representation schemes for recognition and classification of visual shapes. They capture part structure in a compact and natural way and provide insensitivity to visual transformations such as occlusion and articulation of parts. In this thesis, we explore the potential use of disconnected skeleton representation for shape recognition and shape classification. Specifically, we first investigate the importance of contextual information in recognition where we extend the previously proposed disconnected skeleton based shape matching methods in different ways by incorporating category knowledge into matching process. Unlike the view in syntactic matching of shapes, our interpretation differentiates the semantic roles of the shapes in comparison in a way that a query shape is being matched with a database shape whose category is known a priori. The presence of context, i.e. the knowledge about the category of the database shape, influences the similarity computations, and helps us to obtain better matching performance. Next, we build upon our category-influenced matching framework in which both shapes and shape categories are represented with depth-1 skeletal trees, and develop a similarity-based shape classification method where the category trees formed for each shape category provide a reference set for learning the relationships between categories. As our classification method takes into account both within-category and between-category information, we attain high classification performance. Moreover, using the suggested classification scheme in a retrieval task improves both the efficiency and accuracy of matching by eliminating unrelated comparisons.
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Frisk, Dubsky Brendan. "Description and classification of the category oftwo-dimensional real commutative division algebras." Thesis, Uppsala universitet, Algebra och geometri, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-183467.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Khan, Rahat. "Discriminative image representations using spatial and color information for category-level classification." Phd thesis, Université Jean Monnet - Saint-Etienne, 2013. http://tel.archives-ouvertes.fr/tel-01073099.

Повний текст джерела
Анотація:
Image representation is in the heart of many computer vision algorithms. Different computer vision tasks (e.g. classification, detection) require discriminative image representations to recognize visual categories. In a nutshell, the bag-of-visual-words image representation is the most successful approach for object and scene recognition. In this thesis, we mainly revolve around this model and search for discriminative image representations. In the first part, we present a novel approach to incorporate spatial information in the BoVW method. In this framework, we present a simple and efficient way to infuse spatial information by taking advantage of the orientation and length of the segments formed by pairs of similar descriptors. We introduce the notion of soft-similarity to compute intra and inter visual word spatial relationships. We show experimentally that, our method adds important discriminative information to the BoVW method and complementary to the state-of-the-art method. Next, we focus on color description in general. Differing from traditional approaches of invariant description to account for photometric changes, we propose discriminative color descriptor. We demonstrate that such a color description automatically learns a certain degree of photometric invariance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape descriptor, the proposed color descriptor obtain excellent results on four challenging data sets.Finally, we focus on the most accurate color representation i.e. multispectral reflectance which is an intrinsic property of a surface. Even with the modern era technological advancement, it is difficult to extract reflectance information without sophisticated instruments. To this end, we propose to use the display of the device as an illuminant while the camera captures images illuminated by the red, green and blue primaries of the display. Three illuminants and three response functions of the camera lead to nine response values which are used for reflectance estimation. Results show that the accuracy of the spectral reconstruction improves significantly over the spectral reconstruction based on a single illuminant. We conclude that, multispectral data acquisition is potentially possible with consumer hand-held devices such as tablets, mobiles, and laptops
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Chatterton, Michelle. "External Validity of Grammatical Word Category Classification Using an Adaptation and Selection Model." BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5658.

Повний текст джерела
Анотація:
The process of acquiring language requires children to learn grammatical categories and apply these categories to new words. Researchers have proposed various explanations of this process in the form of algorithms and computational modeling. Recently, adaptation and selection models have been tested and applied as a possible explanation to the process of acquiring grammatical categories. These studies have proven promising, however, the external validity of this approach has not been examined by grammatically coding samples outside the training corpus. The current thesis applies an adaptation and selection model, which pauses the evolution of dictionaries after every thousand cycles to allow the tagging of 30 outside samples, which are then checked for tagging accuracy. The accuracy across the five training corpora by the six thousandth cycle averaged 76.75%. Additional research is needed to explore the effects of altering the parameters in the model.
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Musayeva, Khadija. "Generalization Performance of Margin Multi-category Classifiers." Thesis, Université de Lorraine, 2019. http://www.theses.fr/2019LORR0096/document.

Повний текст джерела
Анотація:
Cette thèse porte sur la théorie de la discrimination multi-classe à marge. Elle a pour cadre la théorie statistique de l’apprentissage de Vapnik et Chervonenkis. L’objectif est d’établir des bornes de généralisation possédant une dépendances explicite au nombre C de catégories, à la taille m de l’échantillon et au paramètre de marge gamma, lorsque la fonction de perte considérée est une fonction de perte à marge possédant la propriété d’être lipschitzienne. La borne de généralisation repose sur la performance empirique du classifieur ainsi que sur sa "capacité". Dans cette thèse, les mesures de capacité considérées sont les suivantes : la complexité de Rademacher, les nombres de recouvrement et la dimension fat-shattering. Nos principales contributions sont obtenues sous l’hypothèse que les classes de fonctions composantes calculées par le classifieur ont des dimensions fat-shattering polynomiales et que les fonctions composantes sont indépendantes. Dans le contexte du schéma de calcul introduit par Mendelson, qui repose sur les relations entre les mesures de capacité évoquées plus haut, nous étudions l’impact que la décomposition au niveau de l’une de ces mesures de capacité a sur les dépendances (de la borne de généralisation) à C, m et gamma. En particulier, nous démontrons que la dépendance à C peut être considérablement améliorée par rapport à l’état de l’art si la décomposition est reportée au niveau du nombre de recouvrement ou de la dimension fat-shattering. Ce changement peut affecter négativement le taux de convergence (dépendance à m), ce qui souligne le fait que l’optimisation par rapport aux trois paramètres fondamentaux se traduit par la recherche d’un compromis
This thesis deals with the theory of margin multi-category classification, and is based on the statistical learning theory founded by Vapnik and Chervonenkis. We are interested in deriving generalization bounds with explicit dependencies on the number C of categories, the sample size m and the margin parameter gamma, when the loss function considered is a Lipschitz continuous margin loss function. Generalization bounds rely on the empirical performance of the classifier as well as its "capacity". In this work, the following scale-sensitive capacity measures are considered: the Rademacher complexity, the covering numbers and the fat-shattering dimension. Our main contributions are obtained under the assumption that the classes of component functions implemented by a classifier have polynomially growing fat-shattering dimensions and that the component functions are independent. In the context of the pathway of Mendelson, which relates the Rademacher complexity to the covering numbers and the latter to the fat-shattering dimension, we study the impact that decomposing at the level of one of these capacity measures has on the dependencies on C, m and gamma. In particular, we demonstrate that the dependency on C can be substantially improved over the state of the art if the decomposition is postponed to the level of the metric entropy or the fat-shattering dimension. On the other hand, this impacts negatively the rate of convergence (dependency on m), an indication of the fact that optimizing the dependencies on the three basic parameters amounts to looking for a trade-off
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Zhao, Li. "An Eye Tracking Investigation of Classification Behavior on a Basic Family of Category Structures." Ohio University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1564763671842416.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Zeng, Yue, and Yue Zeng. "Variable Screening Methods in Multi-Category Problems for Ultra-High Dimensional Data." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/624579.

Повний текст джерела
Анотація:
Variable screening techniques are fast and crude techniques to scan high-dimensional data and conduct dimension reduction before a refined variable selection method is applied. Its marginal analysis feature makes the method computationally feasible for ultra-high dimensional problems. However, most existing screening methods for classification problems are designed only for binary classification problems. There is lack of a comprehensive study on variable screening for multi-class classification problems. This research aims to fill the gap by developing variable screening for multi-class problems, to meet the need of high dimensional classification. The work has useful applications in cancer study, medicine, engineering and biology. In this research, we propose and investigate new and effective screening methods for multi-class classification problems. We consider two types of screening methods. The first one conducts screening for multiple binary classification problems separately and then aggregates the selected variables. The second one conducts screening for multi-class classification problems directly. In particular, for each method we investigate important issues such as choices of classification algorithms, variable ranking, and model size determination. We implement various selection criteria and compare their performance. We conduct extensive simulation studies to evaluate and compare the proposed screening methods with existing ones, which show that the new methods are promising. Furthermore, we apply the proposed methods to four cancer studies. R code has been developed for each method.
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Lazaruk, O. V. "Pecularities of metastases in women of Chernivtsi region with invasive ductal breast carcinoma according to TNM classification (category T-N)." Thesis, БДМУ, 2017. http://dspace.bsmu.edu.ua:8080/xmlui/handle/123456789/16801.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Книги з теми "Category classification"

1

Canada, Treasury Board Classification Human Resources Information Systems and Pay Division. Classification standard: Printing operations : operational category. [Ottawa]: Treasury Board of Canada, Secretariat, 1988.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Canada. Treasury Board. Human Resources Information Systems and Pay Division., ed. Classification standard, Historical Research, Scientific and Professional Category. [Ottawa]: Classification, Human Resources Information Systems and Pay Division, Personnel Policy Branch, 1987.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Canada. Treasury Board. Division de la classification, des systèmes d'information sur les ressources humaines et de la paie. Classification standard: General labour and trade operational category. [Ottawa]: The Board, 1988.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Spray, Judith A. Multiple-category classification using a sequential probability ratio test. Iowa City, Iowa: American College Testing Program, 1993.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Spray, Judith A. Multiple-category classification using a sequential probability ratio test. Iowa City, Iowa: American College Testing Program, 1993.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Spray, Judith A. Multiple-category classification using a sequential probability ratio test. Iowa City, Iowa: American College Testing Program, 1993.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Canada. Treasury Board. Classification, Human Resources Information Systems and Pay Division. Personnel Policy Branch., ed. Classification standard, financial administration: Administrative and foreign service category. [Ottawa?]: Classification, Human Resources Information Systems and Pay Division, Personnel Policy Branch, 1987.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Zhao, Yi. Understanding Census 2000: Race category changes & comparisons. [Olympia, Wash.]: Washington State Office of Financial Management, 2001.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Bowmaster, Ron. Assessment of agricultural land by category: Taxation. Lincoln, Neb. (P.O. Box 94945, Lincoln 68509): Nebraska Legislative Council, Legislative Research Division, 1988.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Canada. Conseil du trésor. Direction de la politique du personnel., ed. Management category : position evaluation plan =: Catégorie de la gestion : guide d'évaluation des postes. Ottawa, Ont: Treasury Board of Canada = Conseil du trésor du Canada, 1990.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Частини книг з теми "Category classification"

1

Eggen, Theo J. H. "Three-Category Adaptive Classification Testing." In Elements of Adaptive Testing, 373–87. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-85461-8_19.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Fujinaka, Toru, Michifumi Yoshioka, and Sigeru Omatu. "Category Classification Using Neural Networks." In Soft Computing in Industrial Electronics, 324–45. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1783-6_9.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Loeblich, Alfred R., and Helen Tappan. "Cladegroups, Category Not Recognized by ICZN." In Foraminiferal Genera and Their Classification, 717–18. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4899-5760-3_6.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Mutasim, Aunnoy K., Rayhan Sardar Tipu, M. Raihanul Bashar, and M. Ashraful Amin. "Video Category Classification Using Wireless EEG." In Brain Informatics, 39–48. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70772-3_4.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Sun, Jin, Christopher Thorpe, Nianhua Xie, Jingyi Yu, and Haibin Ling. "Object Category Classification Using Occluding Contours." In Advances in Visual Computing, 296–305. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17289-2_29.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Ullman, Shimon, and Boris Epshtein. "Visual Classification by a Hierarchy of Extended Fragments." In Toward Category-Level Object Recognition, 321–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11957959_17.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Park, Sun, Sang-Ho Park, Ju-Hong Lee, and Jung-Sik Lee. "E-mail Classification Agent Using Category Generation and Dynamic Category Hierarchy." In Lecture Notes in Computer Science, 207–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-30583-5_22.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Li, Yuncong, Cunxiang Yin, Sheng-hua Zhong, Huiqiang Zhong, Jinchang Luo, Siqi Xu, and Xiaohui Wu. "Better Queries for Aspect-Category Sentiment Classification." In Lecture Notes in Computer Science, 347–58. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63031-7_25.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Sun, Aixin, Ee-Peng Lim, and Wee-Keong Ng. "Personalized Classification for Keyword-Based Category Profiles." In Research and Advanced Technology for Digital Libraries, 61–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45747-x_5.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Alemzadeh, Milad, Richard Khoury, and Fakhri Karray. "Exploring Wikipedia’s Category Graph for Query Classification." In Autonomous and Intelligent Systems, 222–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21538-4_22.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Тези доповідей конференцій з теми "Category classification"

1

Fukumoto, Fumiyo, and Yoshimi Suzuki. "Correcting category errors in text classification." In the 20th international conference. Morristown, NJ, USA: Association for Computational Linguistics, 2004. http://dx.doi.org/10.3115/1220355.1220480.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

DIKRANJAN, DIKRAN, WALTER THOLEN, and STEPHEN WATSON. "CLASSIFICATION OF CLOSURE OPERATORS FOR CATEGORIES OF TOPOLOGICAL SPACES." In Proceedings of the North-West European Category Seminar. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812702418_0007.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Yu, Yang, Wei-Yang Qu, Nan Li, and Zimin Guo. "Open Category Classification by Adversarial Sample Generation." 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.2017/469.

Повний текст джерела
Анотація:
In real-world classification tasks, it is difficult to collect training samples from all possible categories of the environment. Therefore, when an instance of an unseen class appears in the prediction stage, a robust classifier should be able to tell that it is from an unseen class, instead of classifying it to be any known category. In this paper, adopting the idea of adversarial learning, we propose the ASG framework for open-category classification. ASG generates positive and negative samples of seen categories in the unsupervised manner via an adversarial learning strategy. With the generated samples, ASG then learns to tell seen from unseen in the supervised manner. Experiments performed on several datasets show the effectiveness of ASG.
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Rousu, Juho, Craig Saunders, Sandor Szedmak, and John Shawe-Taylor. "Learning hierarchical multi-category text classification models." In the 22nd international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1102351.1102445.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Jiménez, Rodrigo Sánchez. "Category labelling for automatic classification scheme generation." In BCS IRSG Symposium: Future Directions in Information Access 2007. BCS Learning & Development, 2007. http://dx.doi.org/10.14236/ewic/fdia2007.18.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Saigal, Pooja, and Reshma Khemchandani. "Nonparallel hyperplane classifiers for multi-category classification." In 2015 IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (WCI). IEEE, 2015. http://dx.doi.org/10.1109/wci.2015.7495510.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Ito, Yasuhiro, Kazuki Saruta, Yuki Terata, and Kazutoki Takeda. "Category classification with ROIs using object detector." In 2009 43rd Annual Conference on Information Sciences and Systems (CISS). IEEE, 2009. http://dx.doi.org/10.1109/ciss.2009.5054805.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Gao, Xin, Zhengye Zhu, Xu Chu, Yasha Wang, Wenjie Ruan, and Junfeng Zhao. "Enhancing Robust Text Classification via Category Description." In 2022 IEEE International Conference on Data Mining (ICDM). IEEE, 2022. http://dx.doi.org/10.1109/icdm54844.2022.00025.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Zhang, Wei, Liguo Duan, and Junjie Chen. "Study on Chinese question classification based on SVM multi-category classification." In Fourth International Conference on Machine Vision (ICMV 11), edited by Zhu Zeng and Yuting Li. SPIE, 2012. http://dx.doi.org/10.1117/12.923769.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Ziegler, Thomas, Judith Butepage, Michael C. Welle, Anastasiia Varava, Tonci Novkovic, and Danica Kragic. "Fashion Landmark Detection and Category Classification for Robotics." In 2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2020. http://dx.doi.org/10.1109/icarsc49921.2020.9096071.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Звіти організацій з теми "Category classification"

1

Klatko, Trevor, Bismark Agbelie, Samuel Labi, Jon Fricker, and Kumares Sinha. Estimation and Prediction of Statewide Vehicle Miles Traveled (VMT) by Highway Category and Vehicle Classification. Purdue University, March 2017. http://dx.doi.org/10.5703/1288284316349.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Idakwo, Gabriel, Sundar Thangapandian, Joseph Luttrell, Zhaoxian Zhou, Chaoyang Zhang, and Ping Gong. Deep learning-based structure-activity relationship modeling for multi-category toxicity classification : a case study of 10K Tox21 chemicals with high-throughput cell-based androgen receptor bioassay data. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41302.

Повний текст джерела
Анотація:
Deep learning (DL) has attracted the attention of computational toxicologists as it offers a potentially greater power for in silico predictive toxicology than existing shallow learning algorithms. However, contradicting reports have been documented. To further explore the advantages of DL over shallow learning, we conducted this case study using two cell-based androgen receptor (AR) activity datasets with 10K chemicals generated from the Tox21 program. A nested double-loop cross-validation approach was adopted along with a stratified sampling strategy for partitioning chemicals of multiple AR activity classes (i.e., agonist, antagonist, inactive, and inconclusive) at the same distribution rates amongst the training, validation and test subsets. Deep neural networks (DNN) and random forest (RF), representing deep and shallow learning algorithms, respectively, were chosen to carry out structure-activity relationship-based chemical toxicity prediction. Results suggest that DNN significantly outperformed RF (p < 0.001, ANOVA) by 22–27% for four metrics (precision, recall, F-measure, and AUPRC) and by 11% for another (AUROC). Further in-depth analyses of chemical scaffolding shed insights on structural alerts for AR agonists/antagonists and inactive/inconclusive compounds, which may aid in future drug discovery and improvement of toxicity prediction modeling.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Panchenko, Liubov F., Tetiana A. Vakaliuk, and Kateryna V. Vlasenko. Augmented reality books: concepts, typology, tools. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4414.

Повний текст джерела
Анотація:
The article discussed the usage of augmented reality books in educational process. The object of research is augmented reality books. The subject of the study is the concepts and classification of augmented reality books; digital story making tools that emphasize child-teacher co-operation; difficulties in augmented reality using. The methods of research are: the analysis of publications about the issue; the analysis of digital tools capabilities; systematization and generalization of research information. In the article the facet classification for augmented books is proposed; the main facets are: reality- virtuality continuum, type of augmented materials, device types, type of interaction, spatial space of book, book’s category. Content for a module of a specialty course about augmented reality books for the system of professional training and retraining for educators in postgraduate education is discussed. Some samples of tasks for educators are presented: audio augmented book about world’s books monuments; analysis augmented reality examples in the textbook of the New Ukrainian school (subject name, topic, didactic tasks, quality of implementation, directions of expansion etc.), search and analysis augmented books according to the professional interests of the educators; discussion how augmented reality can help to improve student motivation with accent to attention, relevance, confidence and satisfaction; group work about design and creation a fragment of own textbook with augmented reality.
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Edwards, Mervyn, Matthias Seidl, and Alix Edwards. GB LSAV Approval Scheme: Non-ADS requirements D7.1. TRL, June 2022. http://dx.doi.org/10.58446/dxiy5599.

Повний текст джерела
Анотація:
The UK government are committed to bringing forward legislation to allow the safe and secure deployment of self-driving vehicles. As part of the CAVPASS programme, TRL was commissioned to propose approaches to vehicle classification, and suitable technical requirements for aspects not related to the Automated Driving System (ADS). These included crashworthiness, occupant protection, protection of vulnerable Road Users (VRUs), and the lighting, braking and steering systems. The focus of this study was on Low-Speed Automated Vehicles (LSAVs). It involved selection and adaptation of existing pre- and post-deployment regulation to enable it to be applied to LSAVs. A main part was the adaptation of the technical regulations for M- and N-category vehicles, laid down in Great Britain’s Road Vehicles (Approval) Regulations 2020 (SI 2020 No. 818), which implements retained Regulation (EU) 2018/858. The study proposed the introduction of two new vehicle categories (for LSAVs with and without occupants, respectively) to allow approval of designs not compatible with the M- and N-category definitions, such as passenger shuttles with six seats and space for standing passengers, or goods vehicles without any seats. Technical clarifications for regulations were developed relating to references to the driver or driver’s seat, controls, warnings and tell-tales and relating to bi-directional vehicles in general. The study further found that a general permission to carry standing passengers in light vehicles could present unreasonable risks to occupants in braking maneuvers or collisions, but that it could be safe in some Operational Design Domains (ODDs). A concept was proposed which offers manufacturers a choice between two Crashworthiness Approval Levels (CALs). The less demanding CAL allows standing passengers but restricts the subsequent ODD of the vehicles. In summary, the study proposed a novel approach to link approval regulations to the vehicle’s ODD and a set of technical requirements for non-ADS-related aspects of passenger- and goods-carrying LSAVs, which could help enable the approval of new vehicle concepts.
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Henderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Mojave Desert Inventory & Monitoring Network. National Park Service, December 2021. http://dx.doi.org/10.36967/nrr-2289952.

Повний текст джерела
Анотація:
A fundamental responsibility of the National Park Service (NPS) is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources and the factors or activities that may threaten or influence their stability and preservation. There are several different categories of geologic or stratigraphic units (supergroup, group, formation, member, bed) that represent a hierarchical system of classification. The mapping of stratigraphic units involves the evaluation of lithologies, bedding properties, thickness, geographic distribution, and other factors. Mappable geologic units may be described and named through a rigorously defined process that is standardized and codified by the professional geologic community (North American Commission on Stratigraphic Nomenclature 2005). In most instances when a new geologic unit such as a formation is described and named in the scientific literature, a specific and well-exposed section or exposure area of the unit is designated as the type section or other category of stratotype (see “Definitions” below). The type section is an important reference exposure for a named geologic unit which presents a relatively complete and representative example for this unit. Geologic stratotypes are important both historically and scientifically, and should be available for other researchers to evaluate in the future.. The inventory of all geologic stratotypes throughout the 423 units of the NPS is an important effort in documenting these locations in order that NPS staff recognize and protect these areas for future studies. The focus adopted for completing the baseline inventories throughout the NPS was centered on the 32 inventory and monitoring networks (I&M) established during the late 1990s. The I&M networks are clusters of parks within a defined geographic area based on the ecoregions of North America (Fenneman 1946; Bailey 1976; Omernik 1987). These networks share similar physical resources (e.g., geology, hydrology, climate), biological resources (e.g., flora, fauna), and ecological characteristics. Specialists familiar with the resources and ecological parameters of the network, and associated parks, work with park staff to support network-level activities such as inventory, monitoring, research, and data management. Adopting a network-based approach to inventories worked well when the NPS undertook paleontological resource inventories for the 32 I&M networks. The planning team from the NPS Geologic Resources Division who proposed and designed this inventory selected the Greater Yellowstone Inventory & Monitoring Network (GRYN) as the pilot network for initiating this project. Through the research undertaken to identify the geologic stratotypes within the parks of the GRYN methodologies for data mining and reporting on these resources were established. Methodologies and reporting adopted for the GRYN have been used in the development of this report for the Mojave Desert Inventory & Monitoring Network (MOJN). The goal of this project is to consolidate information pertaining to geologic type sections that occur within NPS-administered areas, in order that this information is available throughout the NPS to inform park managers and to promote the preservation and protection of these important geologic landmarks and geologic heritage resources. The review of stratotype occurrences for the MOJN shows there are currently no designated stratotypes for Joshua Tree National Park (JOTR) or Manzanar National Historic Site (MANZ); Death Valley...
Стилі APA, Harvard, Vancouver, ISO та ін.
Також вас можуть зацікавити розширені добірки на тему "Category classification" для конкретних типів джерел:
Статті в журналах Дисертації Книги
Ми пропонуємо знижки на всі преміум-плани для авторів, чиї праці увійшли до тематичних добірок літератури. Зв'яжіться з нами, щоб отримати унікальний промокод!

До бібліографії