標題: Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Wei Chen,Yijie Pan Conference proceedings [打印本頁] 作者: fundoplication 時間: 2025-3-21 16:17
書目名稱Advanced Intelligent Computing Technology and Applications影響因子(影響力)
書目名稱Advanced Intelligent Computing Technology and Applications影響因子(影響力)學(xué)科排名
書目名稱Advanced Intelligent Computing Technology and Applications網(wǎng)絡(luò)公開度
書目名稱Advanced Intelligent Computing Technology and Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Advanced Intelligent Computing Technology and Applications被引頻次
書目名稱Advanced Intelligent Computing Technology and Applications被引頻次學(xué)科排名
書目名稱Advanced Intelligent Computing Technology and Applications年度引用
書目名稱Advanced Intelligent Computing Technology and Applications年度引用學(xué)科排名
書目名稱Advanced Intelligent Computing Technology and Applications讀者反饋
書目名稱Advanced Intelligent Computing Technology and Applications讀者反饋學(xué)科排名
作者: 黃瓜 時間: 2025-3-21 21:59
MAPNet: A Multi-scale Attention Pooling Network for Ultrasound Medical Image Segmentationnt autonomous feature extraction capability and good feature representation ability. Traditional convolutional neural networks usually use standard convolutional layers to extract features. However, in medical image segmentation, a pixel may correspond to multiple different scale structures, such as作者: Acumen 時間: 2025-3-22 02:47 作者: 欲望小妹 時間: 2025-3-22 05:16
MOD-YOLO: Improved YOLOv5 Based on Multi-softmax and Omni-Dimensional Dynamic Convolution for Multi- of bridge defect categories often occurs simultaneously, it is difficult for target detection methods targeting a single label to achieve accurate bridge defect detection. This paper proposes a bridge defect detection scheme YOLOv5 based on multi-softmax and omni-dimensional dynamic convolution (MO作者: 空氣傳播 時間: 2025-3-22 11:26
Color Image Steganography Based on Two-Channel Preprocessing and U-Net Networkrocess where secret information may be stolen. With the increasing application of the U-Net network, a novel image steganography technique based on the U-Net structure is designed. The special two-channel preprocessing network is designed to fuse image features, and the SENet attention mechanism has作者: Axon895 時間: 2025-3-22 16:32
Application of a Hybrid Particle Image Velocimetry Method Based on Window Function in the Field of Te initial velocity field generated based on cross-correlation algorithm in mixed particle image velocimetry methods. This can result in inaccurate offset images generated, leading to errors in generating the final fine velocity field using optical flow method. This article adds a window function to 作者: 綠州 時間: 2025-3-22 17:03 作者: Gum-Disease 時間: 2025-3-23 01:12
Refinement Correction Network for Scene Text Detectionliability of text detection. To this end, existing models primarily employ deep convolutional networks to extract semantic information from images. However, the multiple convolutions and downsampling operations in network lead to varying degrees of defects in shallow and deep features. To address th作者: 救護車 時間: 2025-3-23 01:40 作者: 蔓藤圖飾 時間: 2025-3-23 06:34
Unsupervised Extremely Low-Light Image Enhancement with a Laplacian Pyramid Network. To overcome these two problems, we propose an unsupervised Extremely Low-light image enhancement via a Laplacian Pyramid Network (ELLPN). Concretely, concerning the first quandary, we propose to enforce semantic content and style constraints in the low-frequency components of the image’s Laplacian作者: dry-eye 時間: 2025-3-23 11:29
A Multimodal Fake News Detection Model with Self-supervised Unimodal Label Generations and often ignore the semantic differences between single modalities, which limited the performance. To deal with the above problem, this paper proposes a multimodal fake news detection model (AFUG), which fully pays attention to the semantic correlation between each modal information by designing 作者: 最高點 時間: 2025-3-23 13:58 作者: 卡死偷電 時間: 2025-3-23 20:31 作者: HAUNT 時間: 2025-3-23 23:32
Palmprint Recognition Using SC-LNMF Model in Gabor Domainmain of 2D-Gabor wavelet is mainly discussed in this paper. And to extract more texture features of palmprint images, a modified 2D-Gabor kernel function is also used here. It is known that the common LNMF method can successfully extract an image’s local feature, but it does not consider the sparse 作者: 遠足 時間: 2025-3-24 04:06
SkinDiff: A Novel Data Synthesis Method Based on Latent Diffusion Model for Skin Lesion Segmentationng manual annotation. To address this issue, this paper proposes SkinDiff, a novel framework for training data expansion. Derived from the Latent Diffusion Model, we utilize two steps, the Generating Foreground and the Outpainting Background techniques, to synthesize high-fidelity labeled image samp作者: 離開就切除 時間: 2025-3-24 09:12 作者: COMA 時間: 2025-3-24 11:35
Context-Aware Relative Distinctive Feature Learning for Person Re-identificationtion tasks. Predominantly, current research concentrates on two aspects: fine-grained feature learning and hard example mining. However, these approaches present noticeable shortcomings. The method of fine-grained feature learning does not sufficiently account for the relativity of distinct features作者: intimate 時間: 2025-3-24 15:12 作者: affinity 時間: 2025-3-24 20:02 作者: Transfusion 時間: 2025-3-25 01:40
Das Einzelelektron im Kristall,d crack segmentation network that insert a SER at each scale of the encoder and decoder. Finally, by comparing proposed model with six established segmentation algorithms on two public crack datasets, DeepCrack and MSCI, our model achieves higher segmentation accuracy with extremely low parameters and FLOPs.作者: Irritate 時間: 2025-3-25 06:59
Wie man effektiver faktorisiert,. By modeling high-level features in multiple dimensions, a Clue Feature Correction Module (CFCM) is designed to enhance the semantic relevance of high-level features in spatial and channel positions. Experiments on four benchmark datasets validate the superiority of the proposed model over current technologies.作者: enmesh 時間: 2025-3-25 10:29 作者: Nonthreatening 時間: 2025-3-25 14:06 作者: 歌唱隊 時間: 2025-3-25 16:40
Refinement Correction Network for Scene Text Detection. By modeling high-level features in multiple dimensions, a Clue Feature Correction Module (CFCM) is designed to enhance the semantic relevance of high-level features in spatial and channel positions. Experiments on four benchmark datasets validate the superiority of the proposed model over current technologies.作者: 撤退 時間: 2025-3-25 23:30
Weight Uncertainty Network for Low-Light Image Enhancementhe Retinex theory. Our method is trained under various brightness conditions and can generalize well to unknown brightness conditions. Extensive quantitative and qualitative experiments demonstrate that our method can achieve competitive performance against state-of-the-art solutions on different datasets.作者: ROOF 時間: 2025-3-26 02:19
Conference proceedings 2024ons. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology...?.作者: 織物 時間: 2025-3-26 04:26
,Der konstruktive Entwicklungsproze?,mance, achieving an accuracy rate of 95.451% and a recall rate of 99.101%. In addition, we integrate blockchain technology with IPFS to utilize their advantages in information protection to provide innovative solutions for image copyright protection.作者: prostatitis 時間: 2025-3-26 11:29 作者: 法律 時間: 2025-3-26 15:41
https://doi.org/10.1007/978-3-662-66283-0o focus on samples with highly differentiated modal information, we design an adaptive weight adjustment strategy to guide the model’s learning of unimodal information. Extensive experiments on two datasets demonstrate the effectiveness of our AFUG.作者: slipped-disk 時間: 2025-3-26 20:42 作者: 遣返回國 時間: 2025-3-26 21:53 作者: 悠然 時間: 2025-3-27 01:57 作者: Kernel 時間: 2025-3-27 09:11 作者: 處理 時間: 2025-3-27 11:21
A Multimodal Fake News Detection Model with Self-supervised Unimodal Label Generationo focus on samples with highly differentiated modal information, we design an adaptive weight adjustment strategy to guide the model’s learning of unimodal information. Extensive experiments on two datasets demonstrate the effectiveness of our AFUG.作者: 移植 時間: 2025-3-27 15:55 作者: 偽造者 時間: 2025-3-27 18:43
SkinDiff: A Novel Data Synthesis Method Based on Latent Diffusion Model for Skin Lesion Segmentationesponding masks, and then the Outpainting Background technique fills in the normal skin around the lesions to obtain full images. Experimental results show that expanding the skin lesion dataset using the proposed method can significantly improve the performance of the segmentation model.作者: emission 時間: 2025-3-27 22:32
Conference proceedings 2024 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...This year, the conference concentrated mainly on the theories作者: 提名 時間: 2025-3-28 04:10
MOD-YOLO: Improved YOLOv5 Based on Multi-softmax and Omni-Dimensional Dynamic Convolution for Multi-D-YOLO), which combines the proposed multi-softmax classification loss function with omni-dimensional dynamic convolution (ODConv). MOD-YOLO is evaluated on codebrim dataset and achieves the highest performance compared to existing SOTA models such as YOLO series and transformer-based series.作者: Nibble 時間: 2025-3-28 09:41 作者: 茁壯成長 時間: 2025-3-28 13:53 作者: chronicle 時間: 2025-3-28 15:59
Die Aufgaben der Kostenrechnung,etter focus on and utilize feature information at different scales, and achieves effective skip connections. The proposed model is evaluated on two different medical image segmentation datasets, and the results show that our model has achieved better performance in terms of accuracy.作者: 指數(shù) 時間: 2025-3-28 19:30 作者: 縮短 時間: 2025-3-29 02:56
https://doi.org/10.1007/978-3-322-84098-1to recover the secret image. The experimental outcomes indicate that the proposed model increases the visual effect of images, with cover images PSNR and SSIM reaching 40.36 dB and 98.18%, respectively. Therefore, the model can effectively hide images during information transmission and prevent atta作者: Cumbersome 時間: 2025-3-29 05:37 作者: 小畫像 時間: 2025-3-29 08:08
Grundlagen der Lebensmittelmikrobiologie, reconstruction is performed using an inverse wavelet transformation. Experimental results demonstrate that the proposed algorithm not only effectively suppresses complex noise in images and enhances the contrast of clinical pulmonary CT images but also preserves the natural appearance of images an作者: 不舒服 時間: 2025-3-29 12:23
Grundlagen der Lebensmittelmikrobiologien the first stage, we introduce a novel two-decoder architecture with collaborative learning to preliminarily decouple blur features and mitigate the learning complexity of the network. In the second stage, we propose a coupled learning module (CLM) and a feature enhancement block (FEB) to constrain作者: 榮幸 時間: 2025-3-29 18:49 作者: Collected 時間: 2025-3-29 22:17 作者: Mosaic 時間: 2025-3-30 01:47 作者: 構(gòu)成 時間: 2025-3-30 08:03
MAPNet: A Multi-scale Attention Pooling Network for Ultrasound Medical Image Segmentationetter focus on and utilize feature information at different scales, and achieves effective skip connections. The proposed model is evaluated on two different medical image segmentation datasets, and the results show that our model has achieved better performance in terms of accuracy.作者: 令人苦惱 時間: 2025-3-30 12:16
Fusion of Saliency and Edge Map for Multi-operator Image Retargeting Algorithmnd structural details of the original image while removing the minimum energy seams, thus avoiding image artifacts and distortions. To prevent excessive seam carving from distorting the image, we protect the main structure of the image by combining the seam carving and scaling algorithms and adaptiv作者: 甜得發(fā)膩 時間: 2025-3-30 15:04
Color Image Steganography Based on Two-Channel Preprocessing and U-Net Networkto recover the secret image. The experimental outcomes indicate that the proposed model increases the visual effect of images, with cover images PSNR and SSIM reaching 40.36 dB and 98.18%, respectively. Therefore, the model can effectively hide images during information transmission and prevent atta作者: 哎呦 時間: 2025-3-30 19:46
Application of a Hybrid Particle Image Velocimetry Method Based on Window Function in the Field of Teffectiveness of the method proposed in this paper. The results confirm that the method proposed in this article has a significant effect on turbulent particle images, and is always more accurate in generating the initial velocity field of turbulence than based on cross-correlation algorithms. It ca作者: palette 時間: 2025-3-30 20:59 作者: Frequency 時間: 2025-3-31 01:26
A Two-Stage Coupled Learning Network for Image Deblurringn the first stage, we introduce a novel two-decoder architecture with collaborative learning to preliminarily decouple blur features and mitigate the learning complexity of the network. In the second stage, we propose a coupled learning module (CLM) and a feature enhancement block (FEB) to constrain作者: 慷慨援助 時間: 2025-3-31 06:49 作者: laxative 時間: 2025-3-31 11:44 作者: 存心 時間: 2025-3-31 17:14
Image Captioning with Masked Diffusion Modelive experiments and ablation studies on the MSCOCO benchmark. The experimental results demonstrate that our masked diffusion model combined with the CLIP model achieves highly competitive performance in caption generation tasks. Not only does it significantly improve generation speed, but it also yi作者: HAUNT 時間: 2025-3-31 19:55 作者: Eeg332 時間: 2025-3-31 22:49
https://doi.org/10.1007/978-981-97-5603-2Evolutionary Computing and Learning; Swarm Intelligence and Optimization; Neural Networks; Signal Proce
