派博傳思國際中心

標題: Titlebook: Digital Multimedia Communications; 20th International F Guangtao Zhai,Jun Zhou,Xiaokang Yang Conference proceedings 2024 The Editor(s) (if [打印本頁]

作者: 新石器時代    時間: 2025-3-21 16:53
書目名稱Digital Multimedia Communications影響因子(影響力)




書目名稱Digital Multimedia Communications影響因子(影響力)學科排名




書目名稱Digital Multimedia Communications網(wǎng)絡公開度




書目名稱Digital Multimedia Communications網(wǎng)絡公開度學科排名




書目名稱Digital Multimedia Communications被引頻次




書目名稱Digital Multimedia Communications被引頻次學科排名




書目名稱Digital Multimedia Communications年度引用




書目名稱Digital Multimedia Communications年度引用學科排名




書目名稱Digital Multimedia Communications讀者反饋




書目名稱Digital Multimedia Communications讀者反饋學科排名





作者: 羊齒    時間: 2025-3-22 00:10

作者: BIAS    時間: 2025-3-22 02:03
Communications in Computer and Information Sciencehttp://image.papertrans.cn/e/image/284724.jpg
作者: Foment    時間: 2025-3-22 07:10

作者: 巡回    時間: 2025-3-22 10:47

作者: 不吉祥的女人    時間: 2025-3-22 13:00

作者: 不吉祥的女人    時間: 2025-3-22 19:58

作者: Congregate    時間: 2025-3-22 22:35

作者: Pessary    時間: 2025-3-23 03:16
R-Loops and Mitochondrial DNA Metabolism,spread, and source location can be obtained. Considering the popularity of video surveillance systems, smoke segmentation is of great significance. This paper uses an efficient boosted light-weighted network for smoke semantic segmentation with only 0.53M network parameters. Firstly, we propose a no
作者: 分散    時間: 2025-3-23 07:02

作者: Tremor    時間: 2025-3-23 11:34
https://doi.org/10.1007/978-3-642-11460-1ur-dimensional spatial data. However, the restriction of sensor resolution results in a trade-off between angular and spatial resolution, which hinders our ability to simultaneously acquire light field with high spatial and angular resolution. In this paper, we focus on the sparse light field recons
作者: 連詞    時間: 2025-3-23 16:48

作者: 學術討論會    時間: 2025-3-23 20:28
Bertrand Beckert,Beno?t Masquidateness in each separate training task. To date, the average accuracy and forgetting rate are the two most popular metrics for continual learning evaluation. However, these two metrics only care about the overall increment of mistaken samples when a model updated by the new task is applied to the old
作者: Alveoli    時間: 2025-3-24 00:40
Vivian Bellofatto,Jennifer B. Palencharsual confounding factors and language confounding factors in images and annotations of datasets, by computing co-occurrence probabilities between objects and between words. These methods can effectively deconfound the visual and language confounders simultaneously. However, the impact of language pr
作者: 幾何學家    時間: 2025-3-24 03:49
Introduction: The Sage of Love,tion. To accurately model the complexity of rumor propagation dynamics in real social media and effectively ameliorate the effects of rumors on society, a new rumor propagation model named V-SEIR is proposed in this paper. The proposed V-SEIR model considers the node heterogeneity, individual behavi
作者: 輕快走過    時間: 2025-3-24 06:38
Enrique A. Thomann,Edward C. Waymireindispensable component across various fields. Traditional recommendation systems typically rely on either user historical preferences or item similarity for generating suggestions. However, cross-domain recommendation systems transcend these traditional boundaries by harnessing not only user histor
作者: 百靈鳥    時間: 2025-3-24 12:54

作者: 關節(jié)炎    時間: 2025-3-24 16:56

作者: Intuitive    時間: 2025-3-24 20:43
ble information about user concerns and preferences in specific domains. However, there has been limited research exploring the user-related information contained in such conversational data for constructing individual user knowledge graphs. We propose a method for learning to construct a personal k
作者: 健談    時間: 2025-3-25 03:00

作者: apiary    時間: 2025-3-25 07:12
Digital Multimedia Communications978-981-97-3623-2Series ISSN 1865-0929 Series E-ISSN 1865-0937
作者: oxidize    時間: 2025-3-25 08:45
Contemporary Statistical Methods,ns. The experimental validation demonstrates that our method obtains promising objective performance and consistent visual results across various real-world underwater images compared to other eight UIE methods. Our example code and datasets are publicly available at ..
作者: deceive    時間: 2025-3-25 13:41
Daten importieren und exportieren,hensively integrate the information from RGB modal, are then employed to reconstruct high-resolution depth maps. In other words, The asymmetry is reflected in the fact that we only explicitly update the depth features. The effectiveness of our approach is demonstrated through quantitative and qualit
作者: Gerontology    時間: 2025-3-25 16:17
,Hilfsmittel für die Inferenzstatistik,ourier channel attention super-resolution network (WFCASR) to enhance the residual block by incorporating the wide activation mechanism and FCA. Results in the development of. By integrating the FCA block and the wide activation mechanism into our network, the high-frequency information can be effec
作者: 領先    時間: 2025-3-25 22:56
R-Loops and Mitochondrial DNA Metabolism, a novel Attention-guided Coupled Feature Fusion Module (ACFFM) that introduces Self-Refinement Coefficients (SRCs) generated from cross-layer fusion to weight the original layer images. This two-stage fusion approach effectively utilizes information from different scales to alleviate the impact of
作者: 整頓    時間: 2025-3-26 03:55

作者: OFF    時間: 2025-3-26 04:32

作者: 危險    時間: 2025-3-26 11:19

作者: ALIAS    時間: 2025-3-26 12:56

作者: 追蹤    時間: 2025-3-26 17:42
Introduction: The Sage of Love,echanism, to capture the individual behaviors. The empirical analysis reveals the dynamic behavior and complexity of rumor propagation. The V-SEIR model is evaluated in different network topologies and the impact of each metric parameter is verified. By comparing the V-SEIR model with the classic pr
作者: EXPEL    時間: 2025-3-26 21:41

作者: 戰(zhàn)役    時間: 2025-3-27 04:53
https://doi.org/10.1007/978-1-4613-1755-5of class-imbalance, we propose a balanced loss function, in which the loss of each category is weighted by a factor determined by both the actual sample size and effective sample size of this category. Experimental results on three benchmark ME databases demonstrate the superiority of our approach o
作者: 形狀    時間: 2025-3-27 08:15

作者: 在前面    時間: 2025-3-27 10:55
the reinforcement learning policy network. We conduct experiments on the ConvRef dataset, consisting of 11k naturally occurring dialogues, and compare our method with state-of-the-art baselines. The results demonstrate that our approach effectively generates more accurate inference paths from user-a
作者: 不妥協(xié)    時間: 2025-3-27 15:52
ction fostering greater public absorption of historical and cultural content, thus expanding the potential applications of digital humans. In conclusion, digital human technology is poised to offer a novel and efficient technological means for cultural communication, injecting new possibilities into
作者: Slit-Lamp    時間: 2025-3-27 18:33
RAUNE-Net: A Residual and?Attention-Driven Underwater Image Enhancement Methodns. The experimental validation demonstrates that our method obtains promising objective performance and consistent visual results across various real-world underwater images compared to other eight UIE methods. Our example code and datasets are publicly available at ..
作者: tendinitis    時間: 2025-3-27 22:35
Depth Map Super-Resolution via?Asymmetrically Guided Feature Selection and?Spatial Affine Transformahensively integrate the information from RGB modal, are then employed to reconstruct high-resolution depth maps. In other words, The asymmetry is reflected in the fact that we only explicitly update the depth features. The effectiveness of our approach is demonstrated through quantitative and qualit
作者: 向外供接觸    時間: 2025-3-28 05:28
Wide Activation Fourier Channel Attention Network for Super-Resolutionourier channel attention super-resolution network (WFCASR) to enhance the residual block by incorporating the wide activation mechanism and FCA. Results in the development of. By integrating the FCA block and the wide activation mechanism into our network, the high-frequency information can be effec
作者: STAT    時間: 2025-3-28 06:46
LightNet+: Boosted Light-Weighted Network for Smoke Semantic Segmentation a novel Attention-guided Coupled Feature Fusion Module (ACFFM) that introduces Self-Refinement Coefficients (SRCs) generated from cross-layer fusion to weight the original layer images. This two-stage fusion approach effectively utilizes information from different scales to alleviate the impact of
作者: 狗窩    時間: 2025-3-28 13:50

作者: 武器    時間: 2025-3-28 18:20
Coding Prior-Driven JPEG Image Artifact RemovalIn addition, we introduce the Degradation-Aware Dynamic Adjustment Block(DADA Block), which has better nonlinear expression capabilities and can dynamically adjusts the model based on estimated quality factors. Through this improvement we further enhancing its performance in handling JPEG images wit
作者: 運動吧    時間: 2025-3-28 20:31
Where to?Forget: A New Attention Stability Metric for?Continual Learning Evaluationmodels producing consistent changes in terms of RoI and classification accuracy. Experiments show that our evaluation metric offers new insight for analyzing the forgetting characteristics of different continual learning algorithms.
作者: SEEK    時間: 2025-3-28 23:26

作者: Integrate    時間: 2025-3-29 04:30
Modeling and?Analysis of?Rumor Propagation Dynamics in?Social Mediaechanism, to capture the individual behaviors. The empirical analysis reveals the dynamic behavior and complexity of rumor propagation. The V-SEIR model is evaluated in different network topologies and the impact of each metric parameter is verified. By comparing the V-SEIR model with the classic pr
作者: ADORE    時間: 2025-3-29 09:07
Bridging Recommendations Across Domains: An Overview of?Cross-Domain Recommendationesearch directions. In an age where demand for more accurate and personalized recommendations continues to surge in our data-driven world, cross-domain recommendation systems are poised to play a pivotal role in shaping the future of information and content consumption.
作者: glisten    時間: 2025-3-29 12:01
Sequence Modeling Based Data Augmentation for?Micro-expression Recognitionof class-imbalance, we propose a balanced loss function, in which the loss of each category is weighted by a factor determined by both the actual sample size and effective sample size of this category. Experimental results on three benchmark ME databases demonstrate the superiority of our approach o
作者: 破裂    時間: 2025-3-29 19:13
Dual Transformer with Gated-Attention Fusion for News Disaster Image Captioning DNICC19k dataset show that our model has achieved state-of-the-art performance. It is capable of extracting refined visual information and generating more accurate and specific descriptions of disaster news images without relying on additional prior knowledge.
作者: Condense    時間: 2025-3-29 21:06
Constructing Personal Knowledge Graph from?Conversation via?Deep Reinforcement Learningthe reinforcement learning policy network. We conduct experiments on the ConvRef dataset, consisting of 11k naturally occurring dialogues, and compare our method with state-of-the-art baselines. The results demonstrate that our approach effectively generates more accurate inference paths from user-a
作者: Adulate    時間: 2025-3-30 01:20
Exploring the Efficacy of Interactive Digital Humans in Cultural Communicationction fostering greater public absorption of historical and cultural content, thus expanding the potential applications of digital humans. In conclusion, digital human technology is poised to offer a novel and efficient technological means for cultural communication, injecting new possibilities into
作者: 費解    時間: 2025-3-30 06:48

作者: 滲入    時間: 2025-3-30 08:20
SpringerBriefs in Molecular Scienceriments involving eight segmentation tasks like human divers, we demonstrate that AquaSAM outperforms the default SAM model especially at hard tasks like coral reefs. AquaSAM achieves an average Dice Similarity Coefficient (DSC) of 7.13 (%) improvement and an average of 8.27 (%) on mIoU improvement in underwater segmentation tasks.
作者: cinder    時間: 2025-3-30 16:11
AquaSAM: Underwater Image Foreground Segmentationriments involving eight segmentation tasks like human divers, we demonstrate that AquaSAM outperforms the default SAM model especially at hard tasks like coral reefs. AquaSAM achieves an average Dice Similarity Coefficient (DSC) of 7.13 (%) improvement and an average of 8.27 (%) on mIoU improvement in underwater segmentation tasks.
作者: Concomitant    時間: 2025-3-30 16:52
Daten importieren und exportieren, ability. Experiments on the public dataset GDXray demonstrate that the proposed method performs better than other models, with an F1-score of 0.85 and a mIoU of 0.75. Additionally, the proposed model’s simple structure allows for faster referencing and hardware space savings, making it suitable for practical industrial applications.
作者: 交響樂    時間: 2025-3-30 21:58
https://doi.org/10.1007/978-1-4614-2364-5real-world and synthesized datasets demonstrate the method’s advantages and robustness. By addressing texture restoration and blur removal, LDFN offers a promising approach for enhancing low-light image quality.
作者: entreat    時間: 2025-3-31 02:28
Welding Defect Detection Using X-Ray Images Based on?Deep Segmentation Network ability. Experiments on the public dataset GDXray demonstrate that the proposed method performs better than other models, with an F1-score of 0.85 and a mIoU of 0.75. Additionally, the proposed model’s simple structure allows for faster referencing and hardware space savings, making it suitable for practical industrial applications.
作者: 要塞    時間: 2025-3-31 08:38
Local Dynamic Filter Network for?Low-Light Enhancement and?Deblurringreal-world and synthesized datasets demonstrate the method’s advantages and robustness. By addressing texture restoration and blur removal, LDFN offers a promising approach for enhancing low-light image quality.
作者: GET    時間: 2025-3-31 10:40
Conference proceedings 2024pical sections as follows:..CCIS 2066: Image Processing,?Media Computing,?Metaverse and Virtual Reality, and Multimedia Communication...CCIS 2067:?Quality Assessment,?Source Coding, and Application of AI..




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