標(biāo)題: Titlebook: Artificial Intelligence and Soft Computing; 21st International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2023 [打印本頁(yè)] 作者: Garfield 時(shí)間: 2025-3-21 19:37
書(shū)目名稱Artificial Intelligence and Soft Computing影響因子(影響力)
書(shū)目名稱Artificial Intelligence and Soft Computing影響因子(影響力)學(xué)科排名
書(shū)目名稱Artificial Intelligence and Soft Computing網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱Artificial Intelligence and Soft Computing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱Artificial Intelligence and Soft Computing被引頻次
書(shū)目名稱Artificial Intelligence and Soft Computing被引頻次學(xué)科排名
書(shū)目名稱Artificial Intelligence and Soft Computing年度引用
書(shū)目名稱Artificial Intelligence and Soft Computing年度引用學(xué)科排名
書(shū)目名稱Artificial Intelligence and Soft Computing讀者反饋
書(shū)目名稱Artificial Intelligence and Soft Computing讀者反饋學(xué)科排名
作者: 不可思議 時(shí)間: 2025-3-21 21:22
978-3-031-23479-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: FOR 時(shí)間: 2025-3-22 03:38 作者: 使成整體 時(shí)間: 2025-3-22 06:58
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162316.jpg作者: STELL 時(shí)間: 2025-3-22 11:49
Tae Sung Lee M.D.,Jihyuck Lee M.D.sformer architecture developed for CV is the Vision Transformer (ViT) [.]. ViT models have been used to solve numerous tasks in the CV area. One interesting task is the pose estimation of a human subject. We present our modified ViT model, . (UNsupervised TRAnsformer for Pose Estimation), that can r作者: innovation 時(shí)間: 2025-3-22 13:43
Seungil Chung M.D., Ph.D.,Sanghoon Parkances in content-aware image resizing method such as seam carving allow an image to be resized while the critical content is retained. In this paper, we propose identifying the source camera from seam inserted images using blocks as small as 20 . 20. In particular, the correlation is computed betwee作者: Anthology 時(shí)間: 2025-3-22 17:39 作者: hereditary 時(shí)間: 2025-3-22 23:39
Disfigurement due to Port Wine Stains,ecise detection and localization of follicles on the scalp and still poses a significant challenge for the computer vision and pattern recognition systems. We have proposed an automated vision system for follicles detection based on the classification of digitized microscopic scalp images using an e作者: palliative-care 時(shí)間: 2025-3-23 05:24 作者: Root494 時(shí)間: 2025-3-23 05:51
Video-Based Facial Kinship Verification,e real ones to train Computer Vision methods. Autonomous driving research could largely benefit from this as its neural network-based perception systems need a large amount of labeled training data. However, the sim-to-real texture swapping is a demanding challenge because of the large gap between t作者: 泛濫 時(shí)間: 2025-3-23 12:01 作者: Sciatica 時(shí)間: 2025-3-23 17:27
Benedikt M. Schwaiger,Chieh-Han John Tzou Both algorithms have nice theoretical guarantees, but are not able to handle data streams, which have to be processed instance by instance. We propose a novel approach to handle stream classification problems via an adaption of the CVM, which is also able to handle multiclass classification problem作者: lymphoma 時(shí)間: 2025-3-23 18:06 作者: 連系 時(shí)間: 2025-3-24 00:23 作者: BLA 時(shí)間: 2025-3-24 03:06 作者: Pander 時(shí)間: 2025-3-24 07:34
Facial Paralysis and Facial Reanimationrovides tools and techniques for analyzing and enhancing business processes. However, these processes are usually dynamic and can change because of new regulations, emergencies, or other reasons; and these changes are named concept or process drifts. Detecting drifts allows managers to improve the p作者: 使顯得不重要 時(shí)間: 2025-3-24 11:30 作者: 設(shè)施 時(shí)間: 2025-3-24 17:46 作者: 勾引 時(shí)間: 2025-3-24 21:18
Facial Plastic and Reconstructive Surgerycular manifestations are often associated with brain symptoms. To date, computational intelligence has not been used to study the relationship between eye movements and brain disorders. We propose a support vector machine (SVM) based machine learning solution to identify, five disorders related to t作者: overreach 時(shí)間: 2025-3-25 02:01 作者: 非秘密 時(shí)間: 2025-3-25 04:57
Unsupervised Pose Estimation by?Means of?an?Innovative Vision Transformersformer architecture developed for CV is the Vision Transformer (ViT) [.]. ViT models have been used to solve numerous tasks in the CV area. One interesting task is the pose estimation of a human subject. We present our modified ViT model, . (UNsupervised TRAnsformer for Pose Estimation), that can r作者: 噱頭 時(shí)間: 2025-3-25 10:30 作者: 花費(fèi) 時(shí)間: 2025-3-25 15:05 作者: BLA 時(shí)間: 2025-3-25 19:37 作者: Comprise 時(shí)間: 2025-3-25 22:11 作者: habitat 時(shí)間: 2025-3-26 03:09
Semantically Consistent Sim-to-Real Image Translation with?Neural Networkse real ones to train Computer Vision methods. Autonomous driving research could largely benefit from this as its neural network-based perception systems need a large amount of labeled training data. However, the sim-to-real texture swapping is a demanding challenge because of the large gap between t作者: gangrene 時(shí)間: 2025-3-26 04:24 作者: Expressly 時(shí)間: 2025-3-26 08:52
A Streaming Approach to?the?Core Vector Machine Both algorithms have nice theoretical guarantees, but are not able to handle data streams, which have to be processed instance by instance. We propose a novel approach to handle stream classification problems via an adaption of the CVM, which is also able to handle multiclass classification problem作者: d-limonene 時(shí)間: 2025-3-26 14:37
Identifying Cannabis Use Risk Through Social Media Based on?Deep Learning Methods process of classifying online posts to identify cannabis use problems and their associated risks as early as possible. We annotated 11,008 online posts, which we used to build robust classification models. We tested classical and deep learning classifiers. Different CNN- and RNN-based models proved作者: Mets552 時(shí)間: 2025-3-26 17:27 作者: Heterodoxy 時(shí)間: 2025-3-26 23:44
K-Medoids-Surv: A Patients Risk Stratification Algorithm Considering Censored Datat of censored data there may exist several sub-populations with various risk profiles or survival distributions, for which regular survival analysis approaches do not take into consideration. Consequently, there is a need for discovering such sub-populations with unambiguous risk profiles and surviv作者: FLASK 時(shí)間: 2025-3-27 01:36
A Benchmark of?Process Drift Detection Tools: Experimental Protocol and?Statistical Analysisrovides tools and techniques for analyzing and enhancing business processes. However, these processes are usually dynamic and can change because of new regulations, emergencies, or other reasons; and these changes are named concept or process drifts. Detecting drifts allows managers to improve the p作者: LURE 時(shí)間: 2025-3-27 09:08 作者: ornithology 時(shí)間: 2025-3-27 11:15
Tourism Stock Prices, Systemic Risk and Tourism Growth: A Kalman Filter with Prior Update DSGE-VAR Mlicies and monitor them. One of the objectives of creating these models is to explain and understand financial fluctuations through a consistent theoretical framework. In the tourism sector, stock price and systemic risk are key financial variables in the international transmission of business cycle作者: 結(jié)果 時(shí)間: 2025-3-27 14:12 作者: 管理員 時(shí)間: 2025-3-27 21:49
Assessment of?Semi-supervised Approaches Applied to?Convolutional Neural Networkss kind of network demands a great volume of labeled samples to reach a good convergence during the training process. However, in real scenarios labeled samples are scarce because the labeling process is costly and time consuming. Moreover, it is highly susceptible to errors when accomplished by huma作者: hieroglyphic 時(shí)間: 2025-3-27 22:40 作者: 步履蹣跚 時(shí)間: 2025-3-28 02:31
A Benchmark of?Process Drift Detection Tools: Experimental Protocol and?Statistical Analysisificant differences in the accuracy between the tools when performed using distinct parameter configurations. The findings indicate that the parameter configuration affects the accuracy of the detected drifts and the dataset configuration. Another contribution of this paper is the designed experimen作者: monogamy 時(shí)間: 2025-3-28 07:14 作者: fluoroscopy 時(shí)間: 2025-3-28 11:30
Tourism Stock Prices, Systemic Risk and Tourism Growth: A Kalman Filter with Prior Update DSGE-VAR Mncrease the robustness of DSGE and VAR models built for small samples and with irregular data. Our results indicate that BKPU improves the estimation of these models in two aspects. Firstly, the accuracy levels of the computing of the Markov Chain Monte Carlo model are increased, and secondly, the c作者: nominal 時(shí)間: 2025-3-28 16:18
An Expert System to?Detect and?Classify CNS Disorders Based on?Eye Test Data Using SVM and?Nature-In features set for a particular disorder, a solution based on particle swarm optimization is proposed. We trained the SVM models using the generated synthetic data and tested with the real data. The proposed system based on SVMs with linear, polynomial, and RBF kernels were able to identify the stage作者: Nonflammable 時(shí)間: 2025-3-28 22:15 作者: Classify 時(shí)間: 2025-3-28 23:12 作者: DEAF 時(shí)間: 2025-3-29 03:08 作者: 過(guò)剩 時(shí)間: 2025-3-29 08:45 作者: adroit 時(shí)間: 2025-3-29 12:45
Analgesia and Conscious Sedationncrease the robustness of DSGE and VAR models built for small samples and with irregular data. Our results indicate that BKPU improves the estimation of these models in two aspects. Firstly, the accuracy levels of the computing of the Markov Chain Monte Carlo model are increased, and secondly, the c作者: 廚房里面 時(shí)間: 2025-3-29 18:13 作者: hemorrhage 時(shí)間: 2025-3-29 22:09 作者: Sinus-Node 時(shí)間: 2025-3-30 02:32
Conference proceedings 2023igence and Soft Computing, ICAISC 2022, held in Zakopane, Poland, during June 19–23, 2022..The 69 revised full papers presented in these proceedings were carefully reviewed and?selected from 161 submissions. The papers are organized in the following topical?sections:.Volume I:.Neural networks and th作者: Infinitesimal 時(shí)間: 2025-3-30 07:14
0302-9743 ial Intelligence and Soft Computing, ICAISC 2022, held in Zakopane, Poland, during June 19–23, 2022..The 69 revised full papers presented in these proceedings were carefully reviewed and?selected from 161 submissions. The papers are organized in the following topical?sections:.Volume I:.Neural netwo作者: DUCE 時(shí)間: 2025-3-30 12:13
https://doi.org/10.1007/978-3-030-50784-8nloaded backgrounds depicting hospital and office conditions. During experiments, the precision of recognizing individual gesture classes was measured. Experiments were carried out that showed the performance time of the gesture recognizing in images using a GPU card.作者: ANT 時(shí)間: 2025-3-30 14:36 作者: staging 時(shí)間: 2025-3-30 18:07
0302-9743 ntelligence in modeling and simulation..Volume II:.Computer vision, image and speech analysis; data mining; various problems of artificial intelligence; bioinformatics, biometrics and medical applications..978-3-031-23479-8978-3-031-23480-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: hemorrhage 時(shí)間: 2025-3-30 21:09 作者: 眉毛 時(shí)間: 2025-3-31 01:04 作者: 充滿人 時(shí)間: 2025-3-31 07:05
