標(biāo)題: Titlebook: Deep Learning: Fundamentals, Theory and Applications; Kaizhu Huang,Amir Hussain,Rui Zhang Book 2019 Springer Nature Switzerland AG 2019 Ne [打印本頁] 作者: 輕佻 時(shí)間: 2025-3-21 19:40
書目名稱Deep Learning: Fundamentals, Theory and Applications影響因子(影響力)
書目名稱Deep Learning: Fundamentals, Theory and Applications影響因子(影響力)學(xué)科排名
書目名稱Deep Learning: Fundamentals, Theory and Applications網(wǎng)絡(luò)公開度
書目名稱Deep Learning: Fundamentals, Theory and Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Deep Learning: Fundamentals, Theory and Applications被引頻次
書目名稱Deep Learning: Fundamentals, Theory and Applications被引頻次學(xué)科排名
書目名稱Deep Learning: Fundamentals, Theory and Applications年度引用
書目名稱Deep Learning: Fundamentals, Theory and Applications年度引用學(xué)科排名
書目名稱Deep Learning: Fundamentals, Theory and Applications讀者反饋
書目名稱Deep Learning: Fundamentals, Theory and Applications讀者反饋學(xué)科排名
作者: braggadocio 時(shí)間: 2025-3-21 22:29
https://doi.org/10.1007/978-3-030-06073-2Neural networks; Deep representation; Learning; Optimization; Artificial intelligence; Cognitively-inspir作者: 易改變 時(shí)間: 2025-3-22 01:52
Springer Nature Switzerland AG 2019作者: 逗留 時(shí)間: 2025-3-22 04:45 作者: 白楊 時(shí)間: 2025-3-22 09:35
Politische Kultur und Sprache im Umbruchtraining data. The other is how to effectively encode both the current signal segment and the contextual dependency. Both needs many human efforts. Motivated to relieve such issues, this chapter presents a systematic investigation on architecture design strategies for recurrent neural networks in tw作者: Indurate 時(shí)間: 2025-3-22 14:09 作者: Indurate 時(shí)間: 2025-3-22 17:34
Anpassung der ostdeutschen Wirtschaftgence and computer science. Deep learning technologies have been well developed and applied in this area. However, the literature still lacks a succinct survey, which would allow readers to get a quick understanding of (1) how the deep learning technologies apply to NLP and (2) what the promising ap作者: 失望昨天 時(shí)間: 2025-3-23 00:06
Amerikanisierung vs. Modernisierung as humans do. It becomes a necessity in the Internet age and big data era. From fundamental research to sophisticated applications, natural language processing includes many tasks, such as lexical analysis, syntactic and semantic parsing, discourse analysis, text classification, sentiment analysis,作者: Host142 時(shí)間: 2025-3-23 01:34 作者: scrape 時(shí)間: 2025-3-23 06:12
Kaizhu Huang,Amir Hussain,Rui ZhangProvides thorough background of deep learning.Introduces widely-used learning architectures and algorithms.Includes new theory and applications of deep learning作者: 檔案 時(shí)間: 2025-3-23 13:01
Cognitive Computation Trendshttp://image.papertrans.cn/d/image/264645.jpg作者: MURKY 時(shí)間: 2025-3-23 16:17
https://doi.org/10.1007/978-3-663-05625-6 surface temperature prediction. We believe that these two pieces of work are interesting to the researchers in both the machine learning and the ocean science areas, and many machine learning algorithms will be adopted in the ocean science applications.作者: 等級(jí)的上升 時(shí)間: 2025-3-23 18:20 作者: chalice 時(shí)間: 2025-3-23 22:20
2524-5341 ons of deep learning.The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets作者: HARP 時(shí)間: 2025-3-24 02:30 作者: 我的巨大 時(shí)間: 2025-3-24 07:24 作者: Kindle 時(shí)間: 2025-3-24 12:58
Deep RNN Architecture: Design and Evaluation,training data. The other is how to effectively encode both the current signal segment and the contextual dependency. Both needs many human efforts. Motivated to relieve such issues, this chapter presents a systematic investigation on architecture design strategies for recurrent neural networks in tw作者: 土坯 時(shí)間: 2025-3-24 17:57
Deep Learning Based Handwritten Chinese Character and Text Recognition,xt recognition (HCTR). In HCCR, we integrate the traditional normalization-cooperated direction-decomposed feature map (directMap) with the deep convolutional neural network, and under this framework, we can eliminate the needs for data augmentation and model ensemble, which are widely used in other作者: EXPEL 時(shí)間: 2025-3-24 19:47 作者: interference 時(shí)間: 2025-3-25 01:06
Deep Learning for Natural Language Processing, as humans do. It becomes a necessity in the Internet age and big data era. From fundamental research to sophisticated applications, natural language processing includes many tasks, such as lexical analysis, syntactic and semantic parsing, discourse analysis, text classification, sentiment analysis,作者: coltish 時(shí)間: 2025-3-25 07:10
Oceanic Data Analysis with Deep Learning Models,o extract effective information from these raw data becomes an urgent problem in the research of ocean science. In this chapter, we review the data representation learning algorithms, which try to learn effective features from raw data and deliver high prediction accuracy for the unseen data. Partic作者: 他很靈活 時(shí)間: 2025-3-25 07:41
Introduction to Deep Density Models with Latent Variables,ore efficient (sometimes exponentially) than shallow architectures. The performance is evaluated between two shallow models, and two deep models separately on both density estimation and clustering. Furthermore, the deep models are also compared with their shallow counterparts.作者: 特征 時(shí)間: 2025-3-25 12:53 作者: nutrition 時(shí)間: 2025-3-25 16:27
Deep Learning Based Handwritten Chinese Character and Text Recognition, n-gram LMs (BLMs), two types of character-level neural network LMs (NNLMs), namely, feedforward neural network LMs (FNNLMs) and recurrent neural network LMs (RNNLMs) are applied. Both FNNLMs and RNNLMs are combined with BLMs to construct hybrid LMs. To further improve the performance of HCTR, we al作者: 使成波狀 時(shí)間: 2025-3-25 21:26 作者: etidronate 時(shí)間: 2025-3-26 01:49
Deep Learning for Natural Language Processing,onditional Random Fields (Lafferty et al., Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of ICML, 2001) are dominant methods for natural language processing (Manning and Schütze, Foundations of statistical natural language processing. MIT 作者: 使混合 時(shí)間: 2025-3-26 04:29 作者: obscurity 時(shí)間: 2025-3-26 11:30
Politische Kultur und Sprache im Umbruch hybrid unit is used to encode the long contextual trajectories, which comprise of a BLSTM (bidirectional Long Short-Term Memory) layer and a FFS (feed forward subsampling) layer. Secondly, the CTC (Connectionist Temporal Classification) objective function makes it possible to train the model withou作者: 系列 時(shí)間: 2025-3-26 12:41
Anpassung der ostdeutschen Wirtschaft n-gram LMs (BLMs), two types of character-level neural network LMs (NNLMs), namely, feedforward neural network LMs (FNNLMs) and recurrent neural network LMs (RNNLMs) are applied. Both FNNLMs and RNNLMs are combined with BLMs to construct hybrid LMs. To further improve the performance of HCTR, we al作者: 虛情假意 時(shí)間: 2025-3-26 19:39 作者: 天文臺(tái) 時(shí)間: 2025-3-26 22:33 作者: clarify 時(shí)間: 2025-3-27 04:31
Deep Learning: Fundamentals, Theory and Applications作者: Guaff豪情痛飲 時(shí)間: 2025-3-27 07:13
Book 2019 also present the challenges and envision new perspectives which may lead to further breakthroughs in this field.. .This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in stud作者: 深陷 時(shí)間: 2025-3-27 12:46 作者: OTHER 時(shí)間: 2025-3-27 16:57
Gerhard Sielhorst,Manuela Wilhelm for this next day and a half. I welcome you not only as the Dean of the Division and the Medical School but on behalf of the University as well. I know that each of the audience here will gain much from the presentations, and I’m convinced that even the participants will learn something from each o作者: Connotation 時(shí)間: 2025-3-27 18:44
Angelo Compareeit sich die Fragen datenm??ig erfassen lassen) in den Mittelpunkt gestellt, um dem Leser die M?glichkeit zu geben, eigene Beobachtungen anzustellen und sein Wissen durch eigene Arbeit zu vertiefen; - zum anderen werden die Daten - wo immer m?glich - in ihrer zeitlichen Entwicklung der letzten 25 bis 35 Jahre978-3-8100-0346-1978-3-322-85626-5作者: 只有 時(shí)間: 2025-3-28 00:26
,Die Wirkung natürlicher und künstlicher Kohlens?ureb?der sowie der Hochfrequenzbehandlung bei Herzk26 Kurven die erste ausführliche Beschreibung der physiologischen und pathologischen Grundlagen meiner Methode der ?plethysmographischen Arbeitskurve“ und ihrer Anwendung bei Herzkranken ver?ffentlicht. Inzwischen sind meine Angaben von mehreren Klinikern nachgeprüft und best?tigt worden. (L. Dünner
