標(biāo)題: Titlebook: Artificial Intelligence and Soft Computing; 18th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2019 [打印本頁] 作者: Goiter 時間: 2025-3-21 19:10
書目名稱Artificial Intelligence and Soft Computing影響因子(影響力)
書目名稱Artificial Intelligence and Soft Computing影響因子(影響力)學(xué)科排名
書目名稱Artificial Intelligence and Soft Computing網(wǎng)絡(luò)公開度
書目名稱Artificial Intelligence and Soft Computing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Intelligence and Soft Computing被引頻次
書目名稱Artificial Intelligence and Soft Computing被引頻次學(xué)科排名
書目名稱Artificial Intelligence and Soft Computing年度引用
書目名稱Artificial Intelligence and Soft Computing年度引用學(xué)科排名
書目名稱Artificial Intelligence and Soft Computing讀者反饋
書目名稱Artificial Intelligence and Soft Computing讀者反饋學(xué)科排名
作者: Mangle 時間: 2025-3-21 21:12
On Learning and Convergence of RBF Networks in Regression Estimation and Classificationl risk minimization. Mean square convergence of . error is investigated using the machine learning tools such as VC dimension and covering numbers. RBF network estimates are applied in nonlinear function learning and classification.作者: 時代 時間: 2025-3-22 02:11 作者: 相同 時間: 2025-3-22 05:49
Aufbau und Aufgaben der Gerichtsbarkeit the top of the Givens algorithm. First, the classic variant of the Givens method is briefly described. The main section of the article contains a detailed description of the proposed retry worst samples, skip best samples, and the Givens epoch update optimization techniques. The paper concludes with the simulation results and an overall summary.作者: 苦澀 時間: 2025-3-22 10:29
Aufbau und Aufgaben der Gerichtsbarkeitl risk minimization. Mean square convergence of . error is investigated using the machine learning tools such as VC dimension and covering numbers. RBF network estimates are applied in nonlinear function learning and classification.作者: 引導(dǎo) 時間: 2025-3-22 16:38 作者: 倫理學(xué) 時間: 2025-3-22 20:18
978-3-030-20911-7Springer Nature Switzerland AG 2019作者: 松馳 時間: 2025-3-22 22:24
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162307.jpg作者: 冒煙 時間: 2025-3-23 02:22
Das anwaltliche Aufforderungsschreibenraits from images captured automatically. Wheat is one of the three major crops in the world with a total demand expected to exceed 850 million tons by 2050. In this paper we attempt estimation of wheat spikelets from high-definition RGB infield images using a fully convolutional model. We propose a作者: offense 時間: 2025-3-23 09:03 作者: 凝結(jié)劑 時間: 2025-3-23 12:33 作者: patriot 時間: 2025-3-23 15:17
Die Vergleichsgebühren gem?? § 23 BRAGO We propose a named entity recognition framework composed of knowledge-based feature extractors and a deep learning model including contextual word embeddings, long short-term memory (LSTM) layers and conditional random fields (CRF) inference layer. We use an entity linking module to integrate our s作者: 他一致 時間: 2025-3-23 19:58 作者: 去世 時間: 2025-3-24 01:53 作者: Little 時間: 2025-3-24 05:35 作者: indecipherable 時間: 2025-3-24 08:27
Der Instanzenzug im Zivilprozesssure a public information and the compliance to given regulations, a resilient environmental sensor network is necessary. This paper presents a machine learning approach which utilizes low-cost platforms to build a resilient sensor network. In particular, malfunctions are compensated by learning vir作者: 一瞥 時間: 2025-3-24 13:26
Aufbau und Aufgaben der Gerichtsbarkeitents have been conducted using Atari 2600’s Asterix in the Profit Sharing using Convolutional Neural Networks, and it is known that a better score can be obtained than Deep Q-Network. However, experiments have not been conducted on games other than Asterix, and sufficient consideration has not been 作者: PARA 時間: 2025-3-24 15:50
Der Instanzenzug im Zivilprozessm, the amount of researched solutions drops by a large margin, which is further increased with the added requirement of very limited knowledge about the controlled system. These conditions make the problem significantly more complicated, often rendering classic approaches suboptimal or unusable, req作者: 藐視 時間: 2025-3-24 22:31 作者: 死亡率 時間: 2025-3-25 01:11
Der Instanzenzug im Zivilprozessanalysis algorithms, there are new possibilities of using registered actions of many users in logs. In this paper, we present a way to detect anomalies in URL logs using sequential pattern mining algorithms. We analyse the registered URL request sequences of the public institution website in order t作者: LIKEN 時間: 2025-3-25 04:53 作者: Glycogen 時間: 2025-3-25 11:26 作者: 敲竹杠 時間: 2025-3-25 11:43 作者: 沙發(fā) 時間: 2025-3-25 18:15 作者: 做作 時間: 2025-3-25 23:46 作者: Tractable 時間: 2025-3-26 02:03
,Fliesenarbeiten in Treppenh?usern,atistical language identification approaches are effective but need a long text to perform well. To address this problem, we propose the neural model based on the Long Short-Term Memory Neural Network augmented with the Attention Mechanism. The evaluation of the proposed method incorporates tests on作者: GULP 時間: 2025-3-26 07:59
SpikeletFCN: Counting Spikelets from Infield Wheat Crop Images Using Fully Convolutional Networksraits from images captured automatically. Wheat is one of the three major crops in the world with a total demand expected to exceed 850 million tons by 2050. In this paper we attempt estimation of wheat spikelets from high-definition RGB infield images using a fully convolutional model. We propose a作者: MORT 時間: 2025-3-26 12:03 作者: Abrupt 時間: 2025-3-26 15:08 作者: 愛好 時間: 2025-3-26 17:16
Combining Neural and Knowledge-Based Approaches to Named Entity Recognition in Polish We propose a named entity recognition framework composed of knowledge-based feature extractors and a deep learning model including contextual word embeddings, long short-term memory (LSTM) layers and conditional random fields (CRF) inference layer. We use an entity linking module to integrate our s作者: 額外的事 時間: 2025-3-27 00:00
Sensitivity Analysis of the Neural Networks Randomized Learningmeters that are learned are the output weights. Parameters of hidden neurons are generated randomly once and need not to be adjusted. The key issue in randomized learning algorithms is to generate parameters in a right way to ensure good approximation and generalization properties of the network. Re作者: 航海太平洋 時間: 2025-3-27 03:05 作者: 空中 時間: 2025-3-27 07:43
Smart Well Data Generation via Boundary-Seeking Deep Convolutional Generative Adversarial Networksion. Alas, this comes with a great increase in computational time, encumbering the optimization process. With the growing adoption rate for smart wells in oil field development projects, these optimizations are indispensable as to justify the investment on the technology and maximize financial retur作者: 整體 時間: 2025-3-27 12:17 作者: 大廳 時間: 2025-3-27 16:28
Study of Learning Ability in Profit Sharing Using Convolutional Neural Networkents have been conducted using Atari 2600’s Asterix in the Profit Sharing using Convolutional Neural Networks, and it is known that a better score can be obtained than Deep Q-Network. However, experiments have not been conducted on games other than Asterix, and sufficient consideration has not been 作者: synovial-joint 時間: 2025-3-27 18:10 作者: 承認(rèn) 時間: 2025-3-27 23:59 作者: Blanch 時間: 2025-3-28 02:46
Sequential Data Mining of Network Traffic in URL Logsanalysis algorithms, there are new possibilities of using registered actions of many users in logs. In this paper, we present a way to detect anomalies in URL logs using sequential pattern mining algorithms. We analyse the registered URL request sequences of the public institution website in order t作者: 是限制 時間: 2025-3-28 06:49 作者: 招募 時間: 2025-3-28 14:23 作者: Wallow 時間: 2025-3-28 16:31 作者: 仇恨 時間: 2025-3-28 19:08 作者: integral 時間: 2025-3-29 00:00
Application of Spiking Neural Networks to Fashion Classification The main difference between them and previous generation networks is that they are based on spiking neurons. This approach leads us to the need of using specific ways of coding inputs and outputs as well as original methods of learning. The paper considers evaluation of such a network with a Fashio作者: frivolous 時間: 2025-3-29 05:52 作者: Aprope 時間: 2025-3-29 10:16
0302-9743 ics, biometrics, and medical applications; data mining; various problems of artificial intelligence; agent systems, robotics and control..978-3-030-20911-7978-3-030-20912-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 俗艷 時間: 2025-3-29 15:12 作者: Guileless 時間: 2025-3-29 16:00
Der Instanzenzug im Zivilprozessnt of calculations inside the control loop - which with proper tuning have no negative impact on the controller’s performance. The proposed approach outperforms the multi-input Proportional-Derivative (PD) controller preoptimized using a genetic algorithm.作者: Arrhythmia 時間: 2025-3-29 23:33 作者: Preamble 時間: 2025-3-30 00:28
Smart Well Data Generation via Boundary-Seeking Deep Convolutional Generative Adversarial Networksd to diversify existing data as to improve lacking datasets, and data privacy, as the generated data, while next to real, can be shared without the original, protected model. A case study was done in an industry-recognized benchmark model, and the results completely support the use of the proposed m作者: 河流 時間: 2025-3-30 05:44
Neural Net Model Predictive Controller for Adaptive Active Vibration Suppression of an Unknown Systent of calculations inside the control loop - which with proper tuning have no negative impact on the controller’s performance. The proposed approach outperforms the multi-input Proportional-Derivative (PD) controller preoptimized using a genetic algorithm.作者: 全部 時間: 2025-3-30 09:06
Dense Multi-focus Fusion Net: A Deep Unsupervised Convolutional Network for Multi-focus Image Fusioncess variable size images during testing and validation. Experimental results on various test images validate that our proposed method achieves state-of-the-art performance in both subjective and objective evaluation metrics.作者: Compassionate 時間: 2025-3-30 13:15
Das anwaltliche Aufforderungsschreiben) of 53.0, 71.2 respectively on 15 real field images. We produce visualisations which show the good fit of our model to the task. We also concluded that both transfer learning and segmentation lead to a very positive impact for CNN-based models, reducing error by up?to 89%, when extracting key traits such as wheat spikelet counts.作者: laceration 時間: 2025-3-30 19:03 作者: 芳香一點 時間: 2025-3-30 23:50
Aufbau und Aufgaben der Gerichtsbarkeitrk. By comparing the results with the results in Deep Q-Network, we confirmed that this method can acquire higher score than the Deep Q-Network in some games. The common feature of these games is that the number of actions and the number of states are relatively large.作者: 彈藥 時間: 2025-3-31 02:28
Die Vergleichsgebühren gem?? § 23 BRAGOh searches sequentially for the most reliable subset of observations and finally performs outlier deletion. The novel approach is investigated in numerical experiments and is also applied to robustify a multilayer perceptron. The results on data containing outliers reveal the improved performance compared to conventional approaches.作者: Mettle 時間: 2025-3-31 07:14 作者: Transfusion 時間: 2025-3-31 11:35 作者: 很是迷惑 時間: 2025-3-31 15:18
SpikeletFCN: Counting Spikelets from Infield Wheat Crop Images Using Fully Convolutional Networks) of 53.0, 71.2 respectively on 15 real field images. We produce visualisations which show the good fit of our model to the task. We also concluded that both transfer learning and segmentation lead to a very positive impact for CNN-based models, reducing error by up?to 89%, when extracting key traits such as wheat spikelet counts.作者: Perennial長期的 時間: 2025-3-31 18:39 作者: 咯咯笑 時間: 2025-4-1 00:57 作者: 羽毛長成 時間: 2025-4-1 03:32
Robust Training of Radial Basis Function Neural Networksh searches sequentially for the most reliable subset of observations and finally performs outlier deletion. The novel approach is investigated in numerical experiments and is also applied to robustify a multilayer perceptron. The results on data containing outliers reveal the improved performance compared to conventional approaches.作者: 不斷的變動 時間: 2025-4-1 09:24 作者: 連累 時間: 2025-4-1 11:08
Microscopic Sample Segmentation by Fully Convolutional Network for Parasite Detectionsparency look similar, and some of parasites eggs might be unintentionally omitted. The presented method based on fully convolutional network allows processing the entire space of the sample and assigning a class to each pixel of the image. Our model was trained to classify parasite eggs and distinguish them from adjacent or overlapped pollution.
