標題: Titlebook: Intelligence Science and Big Data Engineering. Big Data and Machine Learning; 9th International Co Zhen Cui,Jinshan Pan,Jian Yang Conferenc [打印本頁] 作者: estrange 時間: 2025-3-21 20:06
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning影響因子(影響力)
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning影響因子(影響力)學科排名
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning網(wǎng)絡(luò)公開度
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning網(wǎng)絡(luò)公開度學科排名
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning被引頻次
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning被引頻次學科排名
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning年度引用
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning年度引用學科排名
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning讀者反饋
書目名稱Intelligence Science and Big Data Engineering. Big Data and Machine Learning讀者反饋學科排名
作者: 低三下四之人 時間: 2025-3-21 20:29
978-3-030-36203-4Springer Nature Switzerland AG 2019作者: 騷動 時間: 2025-3-22 02:18
Intelligence Science and Big Data Engineering. Big Data and Machine Learning978-3-030-36204-1Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: MAG 時間: 2025-3-22 07:59
https://doi.org/10.1007/978-3-030-36204-1artificial intelligence; computational linguistics; computer networks; computer vision; data mining; face作者: 遺忘 時間: 2025-3-22 11:50 作者: HALL 時間: 2025-3-22 13:02
Computational Decomposition of Style for Controllable and Enhanced Style Transfer,thod, we derive a simple, effective computational module, which can be embedded into state-of-the-art style transfer algorithms. Experiments demonstrate the effectiveness of our method on not only painting style transfer but also other possible applications such as picture-to-sketch problems.作者: 多產(chǎn)子 時間: 2025-3-22 20:04
Laplacian Welsch Regularization for Robust Semi-supervised Dictionary Learning,atic (HQ) optimization algorithm to solve the model efficiently. Experimental results on various real-world datasets show that LWR performs robustly to outliers and achieves the top-level results when compared with the existing algorithms.作者: notion 時間: 2025-3-22 21:15 作者: 不可救藥 時間: 2025-3-23 03:50 作者: 光滑 時間: 2025-3-23 08:20
Mining Meta-association Rules for Different Types of Traffic Accidents,eta-rule set with universal applicability. Eventually, all traffic databases are excavated again with different thresholds to get association rules, and meta-rules are integrated into association rules to obtain the universal association rules in the form of a cell group. The proposed method is test作者: Adjourn 時間: 2025-3-23 14:03
Epileptic Seizure Prediction Based on Convolutional Recurrent Neural Network with Multi-Timescale,?s and 3?s. Experiments are done to validate the performance of the proposed model on the dataset of CHB-MIT, and a promising result of 94.8% accuracy, 91.7% sensitivity, and 97.7% specificity are achieved.作者: sphincter 時間: 2025-3-23 20:42
Syntactic Analysis of Power Grid Emergency Pre-plans Based on Transfer Learning,ransfer learning method to introduce annotating datasets in the open field and combining with the data in the field of power grid to training model. In this way, the semantic relation of power grid domain is introduced into the syntactic analysis of the pre-plans, and we can further complete the inf作者: 蘆筍 時間: 2025-3-23 22:10 作者: Dorsal-Kyphosis 時間: 2025-3-24 05:47
Wei-min Wang,Rong-rong Gu,Shou-fu Fu,Dong-sheng Wang作者: RALES 時間: 2025-3-24 08:30
r einen Gruppe von Wirtschaftssubjekten entspricht stets so etwas wie eine . einer anderen Gruppe von Wirtschaftssubjekten. Zins erscheint nun als Lohn für denjenigen, der ein Tauschgut zu einem Zeitpunkt zur Verfügung stellt, zu dem der Tauschgutempf?nger noch nicht dafür bezahlen kann oder will. Z作者: Herd-Immunity 時間: 2025-3-24 13:05 作者: Ingenuity 時間: 2025-3-24 16:15
Minchao Li,Shikui Tu,Lei Xur einen Gruppe von Wirtschaftssubjekten entspricht stets so etwas wie eine . einer anderen Gruppe von Wirtschaftssubjekten. Zins erscheint nun als Lohn für denjenigen, der ein Tauschgut zu einem Zeitpunkt zur Verfügung stellt, zu dem der Tauschgutempf?nger noch nicht dafür bezahlen kann oder will. Z作者: contradict 時間: 2025-3-24 20:09 作者: cardiac-arrest 時間: 2025-3-25 01:17 作者: DUCE 時間: 2025-3-25 07:09
Tieke He,Yu Li,Zhipeng Zou,Qing Wuzu gering, als da? sie eine ausreichende Polsterwirkung ausüben k?nnten, ebensowenig wie der Dampf die pl?tzliche Drucksteigerung verhindern kann, da er unter der Einwirkung des Sto?druckes sehr rasch kondensiert. Infolge des unelastischen Zusammenpralls mit der Wand entstehen einmal st?rende Ger?us作者: 天空 時間: 2025-3-25 10:26 作者: 偏見 時間: 2025-3-25 13:38
He Shi,Qun Yang,Bo Wang,Shaohan Liu,Kai Zhouzu gering, als da? sie eine ausreichende Polsterwirkung ausüben k?nnten, ebensowenig wie der Dampf die pl?tzliche Drucksteigerung verhindern kann, da er unter der Einwirkung des Sto?druckes sehr rasch kondensiert. Infolge des unelastischen Zusammenpralls mit der Wand entstehen einmal st?rende Ger?us作者: 小丑 時間: 2025-3-25 19:45
Kai Zhou,Qun Yang,XiuSong Sun,ShaoHan Liu,JinJun LuDieser liefert aber, wie Abb. 201a zeigt, nur für die Teilkan?le an der Nabe und am ?u?eren Umfang Komponenten in den kreiszylindrischen Flutfl?chen der axialen Str?mung. Er besitzt also nicht die bei der Radialschaufel S. 104 besprochene Bedeutung für die Minderleistung durch die endliche Schaufelz作者: 巨頭 時間: 2025-3-25 21:11 作者: 新星 時間: 2025-3-26 01:09
Zhenxing Xu,Junyi Zhang,Daoqiang Zhang,Hanyu Weihtet, bezeichnet werden, flüssige oder gasf?rmige K?rper aus einem Raum mit niederer Spannung in einen Raum mit h?herer Spannung zu bef?rdern. Der zu überwindende Druckunterschied, ausgedrückt in Meter Flüssigkeitss?ule, stellt die F?rderh?he der Pumpe dar.作者: BRAWL 時間: 2025-3-26 07:28 作者: 為現(xiàn)場 時間: 2025-3-26 10:52
Non-local MMDenseNet with Cross-Band Features for Audio Source Separation,t audio sources features. Besides, the proposed model can also capture cross-band features, which are used to recover the missing information around bands’ borders. The proposed model outperforms state-of-the-art results on the widely-used MIR-1K and DSD100 datasets by taking advantages of global information and bands’ border information.作者: 設(shè)施 時間: 2025-3-26 16:25
L2R-QA: An Open-Domain Question Answering Framework, from both LSTM and learning to rank model, which lead to a more precise understanding of questions, as well as the paragraphs. We conduct an extensive set of experiments to evaluate the efficacy of our proposed framework, which proves to be superior.作者: Ingratiate 時間: 2025-3-26 17:08
0302-9743 gineering, IScIDE 2019, held in Nanjing, China, in October 2019...The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics?including inf作者: Intervention 時間: 2025-3-26 22:14
Data Augmentation for Deep Learning of Judgment Documents,ansforming the original data. We use three methods for data augmentation on different scales of original data in solving the crime prediction problem based on the description of the cases, and find that the effects of data augmentation are different for different models and different fundamental data quantities.作者: 土產(chǎn) 時間: 2025-3-27 04:58
Conference proceedings 2019heoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning...?.作者: semiskilled 時間: 2025-3-27 09:00
0302-9743 computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning...?.978-3-030-36203-4978-3-030-36204-1Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: allergy 時間: 2025-3-27 13:16 作者: 是貪求 時間: 2025-3-27 17:16 作者: Obvious 時間: 2025-3-27 20:47 作者: 抵押貸款 時間: 2025-3-27 23:27
Revisit Lmser from a Deep Learning Perspective,everal Lmser functions with experiments on image recognition, reconstruction, association recall, and so on. Experiments demonstrate that Lmser indeed works as indicated in the original paper, and it has promising performance in various applications.作者: Decrepit 時間: 2025-3-28 02:07
A New Network Traffic Identification Base on Deep Factorization Machine,s and high-order feature crosses are fused and give the classified result. We validate our method on Moore dataset which is widely used in network traffic research. Our results demonstrate that DeepFM model not only have a strong ability of network traffic identification but also can reveal some inherent correlation between the attributes.作者: insipid 時間: 2025-3-28 07:35 作者: 空洞 時間: 2025-3-28 14:05 作者: occurrence 時間: 2025-3-28 17:19 作者: 小臼 時間: 2025-3-28 21:11
Minmin Lin,Zhisen Wei,Baoxing Chen,Wenjie Zhang,Jingmin Yangin Naturalzins sein, der unter Umst?nden einem realen Tauschgut von vornherein schon aufgeschlagen wird: Zu einem künftigen Zeitpunkt wird eben etwas mehr Weizen für einen bereits jetzt gebrauchten oder ausgelieferten Sack Dünger berappt als bei sofortiger Weizen-Bezahlung. Der Zins kann also auch a作者: landmark 時間: 2025-3-29 01:51
Minchao Li,Shikui Tu,Lei Xuin Naturalzins sein, der unter Umst?nden einem realen Tauschgut von vornherein schon aufgeschlagen wird: Zu einem künftigen Zeitpunkt wird eben etwas mehr Weizen für einen bereits jetzt gebrauchten oder ausgelieferten Sack Dünger berappt als bei sofortiger Weizen-Bezahlung. Der Zins kann also auch a作者: 感激小女 時間: 2025-3-29 06:13 作者: 有限 時間: 2025-3-29 08:56 作者: 顛簸地移動 時間: 2025-3-29 11:29 作者: 技術(shù) 時間: 2025-3-29 18:09 作者: indemnify 時間: 2025-3-29 22:59 作者: 攀登 時間: 2025-3-30 01:15
Kai Zhou,Qun Yang,XiuSong Sun,ShaoHan Liu,JinJun Lui (Abb. 3). Da also .. = .. = ., so bekommt die Hauptgleichung die vereinfachte Form . wo .. die bei unendlicher Schaufelzahl vorhandene Schaufelarbeit bedeutet. Das zugeh?rige Geschwindigkeitsdiagramm zeigt Abb. 201. Die rein axiale Str?mung, d. h. die Beibehaltung des Abstandes von der Achse ist a作者: 他很靈活 時間: 2025-3-30 07:50
Wenjin Huang,Shikui Tu,Lei Xuispielsweise der Lasthebemaschinen. Ihre Wirkungsweise ist aber eine ganz andere, weil Flüssigkeiten sich in Rohrleitungen jeder beliebigen Form unter verh?ltnism??ig geringem Kraftaufwand fortbewegen lassen. In die betreffende Rohrleitung, die den Ausgangspunkt mit dem Bestimmungsort verbindet, wir作者: 相信 時間: 2025-3-30 11:33
Zhenxing Xu,Junyi Zhang,Daoqiang Zhang,Hanyu Weiispielsweise der Lasthebemaschinen. Ihre Wirkungsweise ist aber eine ganz andere, weil Flüssigkeiten sich in Rohrleitungen jeder beliebigen Form unter verh?ltnism??ig geringem Kraftaufwand fortbewegen lassen. In die betreffende Rohrleitung, die den Ausgangspunkt mit dem Bestimmungsort verbindet, wir作者: 背叛者 時間: 2025-3-30 12:50 作者: 字的誤用 時間: 2025-3-30 17:00
Computational Decomposition of Style for Controllable and Enhanced Style Transfer,sly controllable transfer is still a challenging task. This paper provides a computational decomposition of the style into basic factors, which aim to be factorized, interpretable representations of the artistic styles. We propose to decompose the style by not only spectrum based methods including F作者: Haphazard 時間: 2025-3-31 00:04 作者: falsehood 時間: 2025-3-31 03:58
Non-local MMDenseNet with Cross-Band Features for Audio Source Separation, proposes a novel Non-Local Multi-scale Multi-band DenseNet model termed as NLMMDenseNet for audio source separation by jointly exploring the long-term dependencies and recovering the missing information around bands’ borders. Specifically, to well leverage the long-term dependencies among the audio作者: Incumbent 時間: 2025-3-31 07:47 作者: 卜聞 時間: 2025-3-31 12:24 作者: Phagocytes 時間: 2025-3-31 14:29
Mining Meta-association Rules for Different Types of Traffic Accidents,ors and hidden patterns in traffic accidents. However, there are still potential links between different accident attributes that have not been revealed, with poor universality of association rules obtained by current methods. In order to overcome the limitations of current methods, this paper propo作者: 現(xiàn)暈光 時間: 2025-3-31 21:21
Reliable Domain Adaptation with Classifiers Competition,t by minimizing joint distribution divergence and obtaining the pseudo target labels via source classifier. However, those methods ignore that the source classifier always misclassifies partial target data and the prediction bias seriously deteriorates adaptation performance. It remains an open issu作者: 慷慨不好 時間: 2025-4-1 01:05 作者: gruelling 時間: 2025-4-1 02:06
DeepTF: Accurate Prediction of Transcription Factor Binding Sites by Combining Multi-scale Convolutnd drug design. Recently, deep-learning based methods have been widely used in the prediction of TFBS. In this work, we propose a novel deep-learning model, called Combination of Multi-Scale Convolutional Network and Long Short-Term Memory Network (MCNN-LSTM), which utilizes multi-scale convolution 作者: expansive 時間: 2025-4-1 08:32 作者: 摘要 時間: 2025-4-1 12:20 作者: B-cell 時間: 2025-4-1 17:27 作者: Orgasm 時間: 2025-4-1 19:54
Syntactic Analysis of Power Grid Emergency Pre-plans Based on Transfer Learning,nts in the pre-plans, then they can learn from the experience of previous relevant situations, it is necessary to extract the information of the pre-plans and extract its key information. Therefore, deep learning method with strong generalization ability and learning ability and continuous improveme作者: orthopedist 時間: 2025-4-2 00:17
Improved CTC-Attention Based End-to-End Speech Recognition on Air Traffic Control,In this paper, we improved the architecture of joint CTC-attention based encoder-decoder model for Mandarin speech recognition on Air Traffic Control speech recognition task. Our improved system include a Vggblstm based encoder, an attention LSTM based decoder decoded with CTC mechanism and a LSTM b作者: Explosive 時間: 2025-4-2 05:17
Revisit Lmser from a Deep Learning Perspective,-encoder (AE) by folding the architecture with respect to the central coding layer and thus leading to the features of Duality in Connection Weight (DCW) and Duality in Paired Neurons (DPN), as well as jointly supervised and unsupervised learning which is called Duality in Supervision Paradigm (DSP)
