標(biāo)題: Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Zhanjun Si,Wei Chen Conference proceedings [打印本頁(yè)] 作者: graphic 時(shí)間: 2025-3-21 18:45
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications影響因子(影響力)
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications被引頻次
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications被引頻次學(xué)科排名
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications年度引用
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications年度引用學(xué)科排名
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications讀者反饋
書(shū)目名稱(chēng)Advanced Intelligent Computing Technology and Applications讀者反饋學(xué)科排名
作者: Harness 時(shí)間: 2025-3-21 23:42 作者: GEON 時(shí)間: 2025-3-22 00:36
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/167163.jpg作者: VEIL 時(shí)間: 2025-3-22 07:28 作者: urethritis 時(shí)間: 2025-3-22 11:54
978-981-97-5677-3The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor作者: Carcinogen 時(shí)間: 2025-3-22 13:04
Versicherungsformen der Praxis,ing external knowledge from knowledge bases (KBs), such as extracting entity concepts and evidence within articles, significantly enhances rumor detection performance. However, two limitations still exist: 1)When extracting entity concepts from KBs, entity ambiguity may introduce inappropriate conce作者: Iniquitous 時(shí)間: 2025-3-22 20:32 作者: 摘要 時(shí)間: 2025-3-22 22:11 作者: 媽媽不開(kāi)心 時(shí)間: 2025-3-23 04:54 作者: 滴注 時(shí)間: 2025-3-23 09:03
,Regelungstechnische Verh?ltnisse,ed, traditional detection methods hinder effective disease management. We introduce USST, a novel cassava leaf disease detection approach to address this challenge. USST employs a synergistic combination of two attention mechanisms for enhanced feature learning: optimized self-guided attention (SGA)作者: LITHE 時(shí)間: 2025-3-23 12:02
,Regelungstechnische Verh?ltnisse,ng support for the prevention and treatment of echinococcosis. Echinococcosis, a zoonotic disease, is caused by the larval stage of tapeworms. It is of significant importance in terms of prevention, control strategies, and reducing the impact of the disease. In recent years, the study of RNA, genes,作者: Countermand 時(shí)間: 2025-3-23 14:53
,Wahrnehmen, Beschreiben und Erkl?ren,till difficult to accurately handle curling games, because the continuous state and action space of curling lead to the loss of position information during discretization. In this paper, we have designed a new curling agent based on curling rules. A Curling Location Extraction Policy-Value Network (作者: 手工藝品 時(shí)間: 2025-3-23 19:26 作者: micronized 時(shí)間: 2025-3-24 01:37
Logistiknetzwerkplanung und Transportketten,tly outputting denormalized results may lead to over-smooth predictions. These denormalized predictions suffer from the bias of amplitude scale and occasionally deviate far from actual ground truth. To alleviate this issue, we propose a novel time series forecasting model, Friformer, which compensat作者: SPURN 時(shí)間: 2025-3-24 05:02
,L?sungen zu den übungsaufgaben,g models based on deep learning tend to encounter issues during the feature extraction phase, such as disappearing features, substantial computational loads in feature fusion, and there exist disparities when fusing features of different levels, resulting in models with low robustness. Therefore, th作者: Archipelago 時(shí)間: 2025-3-24 07:29 作者: 從容 時(shí)間: 2025-3-24 14:00
https://doi.org/10.1007/978-3-658-18593-0ments across various domains. However, most deep learning models often fail to consider the multi-resolution characteristics of time series data, which may lead to information loss issues. In this paper, we explore the utilization of information from raw time series data at various resolutions and p作者: Parallel 時(shí)間: 2025-3-24 18:50
https://doi.org/10.1007/978-3-658-10746-8se challenges, we propose a Spatio-Temporal Feature Fusion Model based on Transformer and a Global Feature Mining Module. The aim is to overcome the high resource consumption issue of the Transformer model when processing large-scale traffic data, as well as its potential shortcomings in capturing s作者: Default 時(shí)間: 2025-3-24 21:29
https://doi.org/10.1007/978-3-658-10746-8nificantly impact the recommendation performance of online courses. To address this problem, this paper proposes a feature decomposition multi-task online course recommendation model that integrates the multi-head self-attention mechanism and autoencoder (FDMA). This model adopts a feature decomposi作者: 評(píng)論性 時(shí)間: 2025-3-25 00:19
https://doi.org/10.1007/978-3-658-10746-8ssible time, this paper proposes an improved evacuation model. We analyze the crowd evacuation efficiency of different classroom layouts based on this model and propose a layout strategy. First, this paper improves the static field calculation method of the evacuation model and proposes a fast stati作者: AGGER 時(shí)間: 2025-3-25 04:51 作者: 我要威脅 時(shí)間: 2025-3-25 10:32
,?ffentliche Meinung und Markenführung,m a single perspective, lacking a comprehensive analysis of multiple dimensions such as problems, learners, and knowledge points, which fails to effectively reflect the complexity and diversity of the learning process, resulting in inadequate predictive performance and interpretability, a graph neur作者: epinephrine 時(shí)間: 2025-3-25 14:56
https://doi.org/10.1007/978-3-663-02526-9l human continue to expand, which puts forward higher requirements for the intelligent interaction capability of digital human. This paper presents a study on the large language model (LLM) based intelligent interaction method for digital human and its web applications. Based on the digital human mo作者: 眉毛 時(shí)間: 2025-3-25 19:30
The Degree of Symmetry of Fuzzy Relationsvided. Furthermore, for continuous t-norm, a symmetric fuzzy relation that closely approximates a given fuzzy relation is constructed. Some algorithm is designed to realize this approximation. Finally, similar results for some left-continuous t-norm are given.作者: 舉止粗野的人 時(shí)間: 2025-3-25 22:00 作者: GRAVE 時(shí)間: 2025-3-26 03:20
,L?sungen zu den übungsaufgaben, (SFM) is proposed, aiming to effectively combine information from different levels of features. Finally, through comparison experiments with other models, the effectiveness of our method is proven. The ISSF model achieved Intersection over Union (IoU) scores of 72.17% and 80.26% on IRSTD-1K and NUAA-SIRST datasets respectively.作者: 歌劇等 時(shí)間: 2025-3-26 04:37 作者: 情節(jié)劇 時(shí)間: 2025-3-26 09:28
https://doi.org/10.1007/978-3-663-02526-9 online consultant. From the validation, the proposed digital human could present intelligent and natural answers by both voice and text, effectively realizing the intelligent interaction based on LLM and guaranteeing good experience in web application scenario.作者: 切掉 時(shí)間: 2025-3-26 14:39
Enhance Volatility of Denormalized Predictions in Time Series Forecasting introduce a variable token-based attention mechanism to enhance the prediction of future trends. Through comprehensive experiments on seven benchmark datasets, our proposed method reduces the forecasting error by about 11% compared with state-of-the-art baselines.作者: 流動(dòng)才波動(dòng) 時(shí)間: 2025-3-26 20:13 作者: Integrate 時(shí)間: 2025-3-26 23:31 作者: 即席演說(shuō) 時(shí)間: 2025-3-27 03:55
Large Language Model Based Intelligent Interaction for Digital Human online consultant. From the validation, the proposed digital human could present intelligent and natural answers by both voice and text, effectively realizing the intelligent interaction based on LLM and guaranteeing good experience in web application scenario.作者: Pigeon 時(shí)間: 2025-3-27 07:36 作者: 單純 時(shí)間: 2025-3-27 10:42
0302-9743 82 - the refereed proceedings of the 20th International Conference on Intelligent Computing, ICIC 2024, held in Tianjin, China, during August 5-8, 2024...The total of 863 regular papers were carefully reviewed and selected from 2189 submissions...The intelligent computing annual conference primarily作者: 叫喊 時(shí)間: 2025-3-27 16:17 作者: PAN 時(shí)間: 2025-3-27 19:18 作者: cavity 時(shí)間: 2025-3-28 00:06
https://doi.org/10.1007/978-3-658-10746-8tegration of temporal and spatial correlations, and revealing the interconnections between global and local features. Through extensive experiments on five real-world traffic datasets, the research results demonstrate a significant improvement in prediction accuracy of our proposed method compared to existing models.作者: 獨(dú)行者 時(shí)間: 2025-3-28 02:19 作者: Tailor 時(shí)間: 2025-3-28 10:08
SF-MCTS: Score Feedback Monte Carlo Tree Search for Digital Curling in Continuous State Space-MCTS) has been proposed to enhance the value function. It can solve the problem of discretization of action space and improve the decision-making capabilities of digital curling algorithms. Our method has demonstrated superior performance compared to existing models in experiments.作者: AVANT 時(shí)間: 2025-3-28 11:24
FOKHic: A Framework of ,-mer Based Hierarchical Classificationis, and attention fusion, FOKHic is capable of accomplishing rapid classification of metagenomic viral sequences. Benchmarked on the ICTV virus database, FOKHic exhibits overwhelming performance in terms of ., ., ., and . compared to currently popular virus-oriented tools. FOKHic is available at ..作者: Transfusion 時(shí)間: 2025-3-28 14:43
Spatio-temporal Fusion of Transformer and Global Feature Mining for Traffic Flow Predictiontegration of temporal and spatial correlations, and revealing the interconnections between global and local features. Through extensive experiments on five real-world traffic datasets, the research results demonstrate a significant improvement in prediction accuracy of our proposed method compared to existing models.作者: Preserve 時(shí)間: 2025-3-28 20:41
Evaluating Effect of Classroom Interior Layouts on Crowd Evacuation Efficiency Using Improved Evacuaectiveness of the evacuation model. Finally, based on the evacuation test results of 10 classroom layouts, we evaluated the effectiveness of these 10 layouts and analyzed them and put forward classroom interior layout suggestions, such as expanding classroom exits and increasing classroom wall passages.作者: 方便 時(shí)間: 2025-3-29 02:34 作者: 殺死 時(shí)間: 2025-3-29 05:07 作者: 壟斷 時(shí)間: 2025-3-29 11:17
The Degree of Symmetry of Fuzzy Relationsvided. Furthermore, for continuous t-norm, a symmetric fuzzy relation that closely approximates a given fuzzy relation is constructed. Some algorithm is designed to realize this approximation. Finally, similar results for some left-continuous t-norm are given.作者: 方便 時(shí)間: 2025-3-29 14:07
LegalGPT: Legal Chain of Thought for the Legal Large Language Model Multi-agent Frameworkabilities these models have demonstrated in complex reasoning and zero-shot learning (ZSL). By introducing a multi-intelligence framework based on Large Scale Legal Language Modeling, the research aims to improve the efficiency and performance of the models across a wide range of functions including作者: LARK 時(shí)間: 2025-3-29 17:26
Leverage Diagnosis Intensity in Medication Recommendationses and personalize the proposed treatment. The majority of those systems prioritize medication recommendations based on the current diagnoses of the patient’s electronic health record (EHR) without considering diagnosis intensity. Thus, they fail to capture the intensity of the patient’s condition, 作者: BROW 時(shí)間: 2025-3-29 21:21
USST: Utilizing SimAM and SGA Techniques to Cassava Leaf Diseases Classification in Real Cultivationed, traditional detection methods hinder effective disease management. We introduce USST, a novel cassava leaf disease detection approach to address this challenge. USST employs a synergistic combination of two attention mechanisms for enhanced feature learning: optimized self-guided attention (SGA)作者: Monolithic 時(shí)間: 2025-3-30 03:08
An Entity Alignment Model for Echinococcosis Knowledge Graphng support for the prevention and treatment of echinococcosis. Echinococcosis, a zoonotic disease, is caused by the larval stage of tapeworms. It is of significant importance in terms of prevention, control strategies, and reducing the impact of the disease. In recent years, the study of RNA, genes,作者: Accolade 時(shí)間: 2025-3-30 04:28 作者: 值得贊賞 時(shí)間: 2025-3-30 11:21 作者: 容易做 時(shí)間: 2025-3-30 15:44 作者: 充滿裝飾 時(shí)間: 2025-3-30 18:43 作者: inspired 時(shí)間: 2025-3-30 22:58
An Improved Label Propagation Algorithm Based on Motif and Critical Node for Community Detectionthod which has the advantage of nearly linear time complexity. However, it usually random selects nodes to update the direct neighbor label, which leads to the inaccurate community structure and instability. To solve these issues, we introduce network motif and critical node to assign weights to the作者: 香料 時(shí)間: 2025-3-31 04:30 作者: Rotator-Cuff 時(shí)間: 2025-3-31 08:00 作者: 機(jī)警 時(shí)間: 2025-3-31 10:30 作者: CAGE 時(shí)間: 2025-3-31 15:58 作者: 裂隙 時(shí)間: 2025-3-31 21:35 作者: TSH582 時(shí)間: 2025-4-1 01:23 作者: 粗野 時(shí)間: 2025-4-1 02:03
Large Language Model Based Intelligent Interaction for Digital Humanl human continue to expand, which puts forward higher requirements for the intelligent interaction capability of digital human. This paper presents a study on the large language model (LLM) based intelligent interaction method for digital human and its web applications. Based on the digital human mo作者: 蘑菇 時(shí)間: 2025-4-1 08:30 作者: 鉗子 時(shí)間: 2025-4-1 12:52 作者: Uncultured 時(shí)間: 2025-4-1 15:58
LLM-Driven External Knowledge Integration Network for Rumor Detectiondence to enhance rumor detection. Firstly, CHKIN employs LLM to extract entities and their concepts. In this process, LLM considers contextual content, alleviating issues associated with the ambiguity of entity concepts. Secondly, CHKIN employs LLM, unlike use KBs, to gather evidence. LLM‘s training
