標(biāo)題: Titlebook: Intelligent Information Processing XII; 13th IFIP TC 12 Inte Zhongzhi Shi,Jim Torresen,Shengxiang Yang Conference proceedings 2024 IFIP Int [打印本頁] 作者: controllers 時(shí)間: 2025-3-21 16:25
書目名稱Intelligent Information Processing XII影響因子(影響力)
書目名稱Intelligent Information Processing XII影響因子(影響力)學(xué)科排名
書目名稱Intelligent Information Processing XII網(wǎng)絡(luò)公開度
書目名稱Intelligent Information Processing XII網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Intelligent Information Processing XII被引頻次
書目名稱Intelligent Information Processing XII被引頻次學(xué)科排名
書目名稱Intelligent Information Processing XII年度引用
書目名稱Intelligent Information Processing XII年度引用學(xué)科排名
書目名稱Intelligent Information Processing XII讀者反饋
書目名稱Intelligent Information Processing XII讀者反饋學(xué)科排名
作者: creatine-kinase 時(shí)間: 2025-3-21 20:33 作者: cluster 時(shí)間: 2025-3-22 03:27 作者: 艦旗 時(shí)間: 2025-3-22 07:21 作者: 消耗 時(shí)間: 2025-3-22 09:31
Stephen S. Aremu,Aboozar Taherkhani,Chang Liu,Shengxiang Yang作者: motivate 時(shí)間: 2025-3-22 15:09 作者: 儲(chǔ)備 時(shí)間: 2025-3-22 19:34
Recognition of Signal Modulation Pattern Based on Multi-task Self-supervised Learningssential signal characteristics through contrastive learning to obtain a robust pre-trained model. We then fine-tune the model with a small account of labeled modulation samples to better adapt it to downstream tasks. Experimental results indicate that in scenarios with limited sample availability, 作者: 混亂生活 時(shí)間: 2025-3-23 00:04
Utilizing Attention for?Continuous Human Action Recognition Based on?Multimodal Fusion of?Visual andttention mechanism into inertial 2D CNN, and perform decision level fusion on it. Experimental verification was conducted on the C-MHAD public dataset. The experiment shows that the proposed VIANet outperforms previous baseline in multi-modal human action recognition.作者: Talkative 時(shí)間: 2025-3-23 03:30 作者: Negligible 時(shí)間: 2025-3-23 07:03
CAPPIMU: A Composite Activities Dataset for?Human Activity Recognition Utilizing Plantar Pressure anrmation for activity recognition tasks. Moreover, we conduct a thorough examination of the classification effects exerted by plantar pressure and inertial data from various locations on the recognition of activities, utilizing a selection of widely-recognized deep learning models. The experimental r作者: 嘮叨 時(shí)間: 2025-3-23 12:45
Open-Set Sensor Human Activity Recognition Based on?Reciprocal Time Seriesg space. The constructed boundary space, formed by the reciprocal time series, facilitates the effective learning of inherent generalization features from a large number of unknown samples through multi-class interaction, ultimately reducing the open-set risk. Extensive experiments on three public s作者: 解凍 時(shí)間: 2025-3-23 16:20
A Concept-Based Local Interpretable Model-Agnostic Explanation Approach for?Deep Neural Networks in?hod. Comparative experiments have been conducted between ConceptLIME and LIME to validate the effectiveness of ConceptLIME. The experimental results indicate that ConceptLIME outperforms LIME regarding predictive performance on both the perturbation dataset and the explained instances. Moreover, the作者: 依法逮捕 時(shí)間: 2025-3-23 20:18 作者: enflame 時(shí)間: 2025-3-24 01:47
Hand Gesture Recognition Using a Multi-modal Deep Neural Network inputs, i.e., video and time-series inputs, to improve accuracy. The performances of the baseline models are then compared to the multimodal classifier. Since the multimodal classifier is based on the initial models, it naturally inherits the benefits of both baseline architectures and provides a h作者: 紳士 時(shí)間: 2025-3-24 02:29
en ist auf Grund von geringen Patientenzahlen für die gro?en Unternehmen wirtschaftlich nicht attraktiv. Partnerschaften mit Gro?unternehmen, Biotechfirmen und gleichen Partnern k?nnen dem Mittelstand helfen, sich seine Nischen noch besser einzurichten. Wie weit er für diese Politik geeignet ist, ka作者: 服從 時(shí)間: 2025-3-24 10:07 作者: 變化 時(shí)間: 2025-3-24 11:39 作者: 鑲嵌細(xì)工 時(shí)間: 2025-3-24 15:54
Saneet Fulsunder,Saidu Umar,Aboozar Taherkhani,Chang Liu,Shengxiang Yang Mitbestimmung abh?ngige Variable herangezogen. Das Investitionsverhalten umfasst neben dem Aspekt des Zeithorizonts der Unternehmensstrategie auch die Frage, inwiefern die Unternehmensstruktur von den institutionellen Bedingungen eines Produktionsregimes beeinflusst wird.作者: 云狀 時(shí)間: 2025-3-24 19:12 作者: 喃喃而言 時(shí)間: 2025-3-25 02:35
Dependency-Type Weighted Graph Convolutional Network on?End-to-End Aspect-Based Sentiment Analysisype-weighted matrix to combine the dependency-type message, and DTW-GCN could fuse the dependency-type message and word embedding vectors. Experiments conducted on three benchmark datasets verify the effectiveness of our model.作者: 明智的人 時(shí)間: 2025-3-25 06:50
Conference proceedings 2024ing;?Natural Language Processing;?Neural and Evolutionary Computing;?Recommendation and Social Computing;?Business Intelligence and Risk Control; and?Pattern Recognition..Volume II: Image Understanding..作者: 運(yùn)動(dòng)性 時(shí)間: 2025-3-25 08:00 作者: 美麗的寫 時(shí)間: 2025-3-25 11:41
Conference proceedings 2024t Information Processing XII, IIP 2024, held in Shenzhen, China, during May 3–6, 2024.?.The?49?full papers and?5 short papers?presented in these proceedings were carefully reviewed and selected from?58?submissions.?.The papers are organized in the following topical sections:?.Volume I: Machine Learn作者: META 時(shí)間: 2025-3-25 17:59
Graph Convolutional Networks for Predicting Mechanical Characteristics of 3D Lattice Structuresethodology reduces preprocessing by leveraging GCNs to directly process 3D geometrics in graph form. The experimental results show the efficiency of our proposed method in predicting 3D lattice structures.作者: HIKE 時(shí)間: 2025-3-25 22:00 作者: FOLLY 時(shí)間: 2025-3-26 01:18 作者: decode 時(shí)間: 2025-3-26 06:15 作者: 客觀 時(shí)間: 2025-3-26 10:38 作者: 借喻 時(shí)間: 2025-3-26 13:51
https://doi.org/10.1007/978-3-031-57919-6Computer Science; Informatics; Conference Proceedings; Research; Applications作者: 同謀 時(shí)間: 2025-3-26 18:49 作者: LUT 時(shí)間: 2025-3-26 22:03 作者: Fissure 時(shí)間: 2025-3-27 02:21
Intelligent Information Processing XII978-3-031-57919-6Series ISSN 1868-4238 Series E-ISSN 1868-422X 作者: 幸福愉悅感 時(shí)間: 2025-3-27 06:54
Early Anomaly Detection in?Hydraulic Pumps Based on?LSTM Traffic Prediction ModelConsequently, devising predictive methods for the main pump flow is crucial for early anomaly detection and efficient maintenance. This paper introduces a predictive method for hydraulic pump flow based on Long Short-Term Memory networks (LSTM), known for their robust handling of temporal data. Util作者: modest 時(shí)間: 2025-3-27 09:37
Dynamic Parameter Estimation for?Mixtures of?Plackett-Luce Modelsenario, rank data often updates in real-time, e.g., when users perform operations, such as submitting or withdrawing rankings. This dynamic nature of rank data poses challenges for applying traditional algorithms. To address this issue, we propose parameter estimation algorithms tailored for structu作者: bile648 時(shí)間: 2025-3-27 16:50 作者: 他日關(guān)稅重重 時(shí)間: 2025-3-27 19:19 作者: CLOWN 時(shí)間: 2025-3-27 22:44
Utilizing Attention for?Continuous Human Action Recognition Based on?Multimodal Fusion of?Visual anderaction, action perception, and other fields. Currently, most of the work has achieved significant results by utilizing both visual and inertial sensor data, as well as deep learning methods. This method of integrating multimodal information makes the system more robust and adaptable to different e作者: 原告 時(shí)間: 2025-3-28 03:26 作者: ciliary-body 時(shí)間: 2025-3-28 09:25
CAPPIMU: A Composite Activities Dataset for?Human Activity Recognition Utilizing Plantar Pressure an However, the current public datasets for composite activities are limited in the variety of activities and the number of subjects they include, which hinders a thorough and complete assessment of activity identification methodologies. Regarding these problems, this paper proposes a publicly availab作者: CURL 時(shí)間: 2025-3-28 13:12 作者: emulsify 時(shí)間: 2025-3-28 17:30 作者: reaching 時(shí)間: 2025-3-28 19:56
A Deep Neural Network-Based Segmentation Method for Multimodal Brain Tumor Imageson models and sufficient high-quality well-labeled training samples, but it is difficult for existing segmentation methods to meet these requirements. In this paper, we propose a segmentation method, which involves a GAN-nested model and an improved UNet. The GAN-nested model is used to automaticall作者: Tidious 時(shí)間: 2025-3-28 22:55 作者: 禁令 時(shí)間: 2025-3-29 06:58 作者: periodontitis 時(shí)間: 2025-3-29 09:11 作者: ANTIC 時(shí)間: 2025-3-29 14:08
Hand Gesture Recognition Using a Multi-modal Deep Neural Networkled systems have existed for some time, they either use additional specialized imaging equipment, require unreasonable computing resources, or are simply not accurate enough to be a viable alternative. In this work, a reliable method of recognizing gestures is proposed. The built model correctly cla作者: 豪華 時(shí)間: 2025-3-29 18:50
; in Deutschland erzielen die 10 gr??ten Pharmaunternehmen einen kumulierten Marktanteil von knapp 30%, mehr als 1.000 Anbieter teilen sich die restlichen 70% des Markts. Die mittelst?ndischen Pharmaunternehmen sind in Deutschland traditionell besonders stark vertreten, haben aber meist eine deutlic作者: Neuralgia 時(shí)間: 2025-3-29 21:33
; in Deutschland erzielen die 10 gr??ten Pharmaunternehmen einen kumulierten Marktanteil von knapp 30%, mehr als 1.000 Anbieter teilen sich die restlichen 70% des Markts. Die mittelst?ndischen Pharmaunternehmen sind in Deutschland traditionell besonders stark vertreten, haben aber meist eine deutlic作者: 多產(chǎn)子 時(shí)間: 2025-3-30 03:28
Yongru Chen,Wenxian Zheng,Xiaying Bai,Qiqi Bao,Wenming Yang,Guijin Wang,Qingmin Liaoen spiegeln sich gem?? Michael Porter vielf?ltige Interessen der Unternehmensakteure und die verschiedenen Auspr?gungen von Kapitalm?rkten wider:.Hall und Soskice bilden die Strategie von Unternehmen, die von den jeweiligen institutionellen Auspr?gungen eines Produktionsregimes gepr?gt wird, in erst作者: 大量 時(shí)間: 2025-3-30 04:24 作者: 連系 時(shí)間: 2025-3-30 09:59
