標(biāo)題: Titlebook: Algorithms in Ambient Intelligence; Wim F. J. Verhaegh,Emile Aarts,Jan Korst Book 2004 Springer Science+Business Media Dordrecht 2004 Audi [打印本頁(yè)] 作者: hypothyroidism 時(shí)間: 2025-3-21 18:38
書目名稱Algorithms in Ambient Intelligence影響因子(影響力)
書目名稱Algorithms in Ambient Intelligence影響因子(影響力)學(xué)科排名
書目名稱Algorithms in Ambient Intelligence網(wǎng)絡(luò)公開度
書目名稱Algorithms in Ambient Intelligence網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Algorithms in Ambient Intelligence被引頻次
書目名稱Algorithms in Ambient Intelligence被引頻次學(xué)科排名
書目名稱Algorithms in Ambient Intelligence年度引用
書目名稱Algorithms in Ambient Intelligence年度引用學(xué)科排名
書目名稱Algorithms in Ambient Intelligence讀者反饋
書目名稱Algorithms in Ambient Intelligence讀者反饋學(xué)科排名
作者: 不知疲倦 時(shí)間: 2025-3-22 00:01
From Stereotypes to Personal Profiles Via Viewer FeedbackOne of the thorny problems facing a recommender system is that of a .: how does one capture the user preferences quickly and effectively and provide user-specific personalization? To address the cold start problem, we propose a stereotype-enabled personalization framework that transforms a user’s TV作者: cinder 時(shí)間: 2025-3-22 01:52
Cubyhum: Algorithms for Query by Humming database of known melodies. In short, it tries to detect the pitches in a sung melody and compares these pitches with symbolic representations of the known melodies. Melodies that are similar to the sung pitches are retrieved. Approximate pattern matching in the melody comparison process compensate作者: ICLE 時(shí)間: 2025-3-22 08:29
Personalized Multimedia Summarizationtial part of intelligent behavior of the consumer devices..We introduce the notion of video summarization, and provide definitions of the different flavors of summaries: Video skim, highlights, and structured multimedia summary. We present different features and methods for automatic video content a作者: 人類的發(fā)源 時(shí)間: 2025-3-22 10:51 作者: Hyperplasia 時(shí)間: 2025-3-22 14:43 作者: 愛好 時(shí)間: 2025-3-22 20:22 作者: Palpable 時(shí)間: 2025-3-23 00:23 作者: FOLD 時(shí)間: 2025-3-23 05:16
Exchange Clustering and Em Algorithm for Phrase Classification in Telephony Applicationsialogue applications. The presented algorithms are based on exchange clustering with a word-error like criterion and on the expectation-maximization algorithm, respectively, and work on annotated training texts. The methods are applied to the Philips TABA corpus of train timetable enquiries, and the作者: 柳樹；枯黃 時(shí)間: 2025-3-23 09:11 作者: 擦掉 時(shí)間: 2025-3-23 10:36 作者: Afflict 時(shí)間: 2025-3-23 14:05
Methods to Optimally Trade Bandwidth Against Buffer Size for a VBR Streamow to minimize the required buffer size given the available bandwidth [Feng, 1997] and how to minimize the required bandwidth given the available buffer size [Salehi et al., 1998]. Instead of taking either bandwidth or buffer size fixed, we assume both to be decision variables with given cost coeffi作者: 羅盤 時(shí)間: 2025-3-23 19:56
Dynamic Control of Scalable Media Processing Applicationsse realtime requirements can be met by means of a worst-case resource allocation, but this is often not cost-effective. To assign resources closer to the average-case load situation, scalable media processing may be applied. A scalable media processing application allows a trade-off between the reso作者: CANE 時(shí)間: 2025-3-24 00:55 作者: Morose 時(shí)間: 2025-3-24 02:45 作者: CLAIM 時(shí)間: 2025-3-24 09:22 作者: 小溪 時(shí)間: 2025-3-24 12:04
https://doi.org/10.1007/978-3-662-06553-2framework. This paper presents the algorithms for pitch detection, note onset detection, quantisation, melody encoding and approximate pattern matching as they have been implemented in the CubyHum software system.作者: 配置 時(shí)間: 2025-3-24 16:06
Cubyhum: Algorithms for Query by Hummingframework. This paper presents the algorithms for pitch detection, note onset detection, quantisation, melody encoding and approximate pattern matching as they have been implemented in the CubyHum software system.作者: 繁殖 時(shí)間: 2025-3-24 19:22 作者: Ostrich 時(shí)間: 2025-3-25 02:04
https://doi.org/10.1007/978-3-662-37015-5ndard Gaussian framework for classification, results show that the temporal behavior of features is important for automatic audio classification. In addition, classification is better, on average, if based on features from models of auditory perception rather than on standard features.作者: oblique 時(shí)間: 2025-3-25 03:45
Beispiele mit rein turbulentem Austausch, the study of programs that form hypotheses that are ‘probably approximately correct’(PAC-learning),with high probability. We also survey a number of meta-learning techniques such as bagging and adaptive boosting, which can improve the performance of machine learning algorithms substantially.作者: 外露 時(shí)間: 2025-3-25 10:29 作者: Ganglion-Cyst 時(shí)間: 2025-3-25 15:44 作者: 牲畜欄 時(shí)間: 2025-3-25 15:51
https://doi.org/10.1007/978-3-663-06968-3lgorithm, respectively, and work on annotated training texts. The methods are applied to the Philips TABA corpus of train timetable enquiries, and the resulting error rates of the semantic tags are computed from a reference assignment.作者: 無(wú)關(guān)緊要 時(shí)間: 2025-3-25 22:43
https://doi.org/10.1007/978-3-642-92237-4o/video..In this chapter we present the three algorithms behind Philips’ fingerprinting technology, i.e., the fingerprint extraction algorithms (both for audio and for video) and the database search algorithm.作者: CRATE 時(shí)間: 2025-3-26 01:31 作者: 災(zāi)禍 時(shí)間: 2025-3-26 06:42 作者: 肉體 時(shí)間: 2025-3-26 11:18
Exchange Clustering and Em Algorithm for Phrase Classification in Telephony Applicationslgorithm, respectively, and work on annotated training texts. The methods are applied to the Philips TABA corpus of train timetable enquiries, and the resulting error rates of the semantic tags are computed from a reference assignment.作者: 細(xì)菌等 時(shí)間: 2025-3-26 14:25
Algorithms for Audio and Video Fingerprintingo/video..In this chapter we present the three algorithms behind Philips’ fingerprinting technology, i.e., the fingerprint extraction algorithms (both for audio and for video) and the database search algorithm.作者: dapper 時(shí)間: 2025-3-26 17:53
Saving Energy in Portable Multimedia Storageeffort requests can be interleaved with real-time requests, in such a way that they interfere as little as possible with the energy saving strategies..We provide computational results to give an indication of the energy savings that can be expected from these strategies.作者: 一起平行 時(shí)間: 2025-3-26 21:13 作者: 鉆孔 時(shí)間: 2025-3-27 04:47
Features for Audio Classificationndard Gaussian framework for classification, results show that the temporal behavior of features is important for automatic audio classification. In addition, classification is better, on average, if based on features from models of auditory perception rather than on standard features.作者: 提名 時(shí)間: 2025-3-27 07:20 作者: octogenarian 時(shí)間: 2025-3-27 09:38 作者: 大門在匯總 時(shí)間: 2025-3-27 15:11 作者: 我要沮喪 時(shí)間: 2025-3-27 18:10 作者: Perennial長(zhǎng)期的 時(shí)間: 2025-3-28 00:47 作者: 新奇 時(shí)間: 2025-3-28 03:15
From Stereotypes to Personal Profiles Via Viewer Feedbackh a different set of stereotypes applied to all the users. The best performance is in the range of 11% error. This performance compares favorably with the best we have got to date on recommenders trained on user-specific data.作者: confederacy 時(shí)間: 2025-3-28 06:25 作者: Accord 時(shí)間: 2025-3-28 13:52 作者: 能得到 時(shí)間: 2025-3-28 17:08 作者: BRAWL 時(shí)間: 2025-3-28 21:44
Book 2004ioned at the inter- section of computer science, discrete mathematics, and artificial intelligence, contains a large variety of interesting topics including machine learning, con- tent management, vision, speech, data mining, content augmentation, profiling, contextual awareness, feature extraction, resource management, security, and privacy.作者: harmony 時(shí)間: 2025-3-28 22:55 作者: agitate 時(shí)間: 2025-3-29 03:08 作者: faddish 時(shí)間: 2025-3-29 10:17
Algorithms in Ambient IntelligenceIn this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.作者: 群島 時(shí)間: 2025-3-29 11:56 作者: 協(xié)議 時(shí)間: 2025-3-29 19:39 作者: 薄荷醇 時(shí)間: 2025-3-29 21:38 作者: START 時(shí)間: 2025-3-30 02:09 作者: 我不死扛 時(shí)間: 2025-3-30 06:16
https://doi.org/10.1007/978-3-662-37015-5nd crowd noise. The feature sets include low-level signal properties, mel-frequency spectral coefficients, and two new sets based on perceptual models of hearing. The temporal behavior of the features is analyzed and parameterized and these parameters are included as additional features. Using a sta作者: mydriatic 時(shí)間: 2025-3-30 10:50
Der W?rme- und K?lteschutz in der Industriecient access to this increasing amount of available content, sometimes referred to as the content bottleneck. We focus on the special case of spoken audio content and demonstrate how partly erroneous document information (e.g. from automatic speech recognizer transcripts) may be consistently incorpo作者: 宏偉 時(shí)間: 2025-3-30 12:30
Beispiele mit rein turbulentem Austausch,asks over time. In this tutorial, we outline some issues in machine learning that pertain to ambient and computational intelligence. As an example, we consider programs that are faced with the learning of tasks or concepts which are impossible to learn exactly in finitely bounded time. This leads to作者: 極深 時(shí)間: 2025-3-30 16:41
Beispiele mit rein turbulentem Austausch,st natural modalities for man-machine interaction. Numerous applications in the context of Ambient Intelligence — whether referring to a single input modality or combining different ones — involve some pattern classification task. Experience shows that for building successful and reliable real life 作者: Genteel 時(shí)間: 2025-3-30 20:54
https://doi.org/10.1007/978-3-663-06968-3ialogue applications. The presented algorithms are based on exchange clustering with a word-error like criterion and on the expectation-maximization algorithm, respectively, and work on annotated training texts. The methods are applied to the Philips TABA corpus of train timetable enquiries, and the作者: 沉思的魚 時(shí)間: 2025-3-31 04:42
https://doi.org/10.1007/978-3-642-92237-4-vectors representing the most essential perceptual characteristics, and comparison of these fingerprints with pre-computed fingerprints of known audio/video..In this chapter we present the three algorithms behind Philips’ fingerprinting technology, i.e., the fingerprint extraction algorithms (both 作者: Coterminous 時(shí)間: 2025-3-31 06:30 作者: 搖晃 時(shí)間: 2025-3-31 11:02 作者: Clinch 時(shí)間: 2025-3-31 14:47
,Verwertung der W?rme zu Heizzwecken,se realtime requirements can be met by means of a worst-case resource allocation, but this is often not cost-effective. To assign resources closer to the average-case load situation, scalable media processing may be applied. A scalable media processing application allows a trade-off between the reso
