Cross-language dissemination of Chinese classical literature using multimodal deep learning and artificial intelligence by Yulan Bai, Songhua Lei

“…Moreover, incorporating the decoder’s visual module notably boosts performance, with BLEU and METEOR scores on the En-Ge Test2017 task improving by 2.55% and 2.33%, respectively. …”
Get full text

MSLKSTNet: Multi-Scale Large Kernel Spatiotemporal Prediction Neural Network for Air Temperature Prediction by Feng Gao, Jiaen Fei, Yuankang Ye, Chang Liu

Get full text

A Self-Supervised Specific Emitter Identification Method Based on Contrastive Asymmetric Masked Learning by Dong Wang, Yonghui Huang, Tianshu Cui, Yan Zhu

Get full text

Predicting microbe-disease associations via graph neural network and contrastive learning by Cong Jiang, Cong Jiang, Junxuan Feng, Junxuan Feng, Bingshen Shan, Bingshen Shan, Qiyue Chen, Jian Yang, Jian Yang, Gang Wang, Gang Wang, Xiaogang Peng, Xiaozheng Li, Xiaozheng Li

Get full text

Hybrid transformer and convolution iteratively optimized pyramid network for brain large deformation image registration by Xinxin Cui, Yuee Zhou, Caihong Wei, Guodong Suo, Fengqing Jin, Jianlan Yang

“…Secondly, the Swin-Transformer module is combined with the convolution iterative strategy, and each layer of the decoder is carefully designed according to the semantic information characteristics of different decoding layers. …”
Get full text

Triple-attentions based salient object detector for strip steel surface defects by Li Zhang, Xirui Li, Yange Sun, Huaping Guo

“…Based on the TA, a novel detector, called TADet, for the detection of steel strip surface defects is proposed, which is an encoder-decoder network: the decoder uses the proposed TA refines/fuses the multiscale rough features generated by the encoder (backbone network) from the three distinct perspectives (branches) and then integrates the purified feature maps from the three branches. …”
Get full text

A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification by Lilu Wang, Yongqi Li, Haiyuan Liu, Taihui Liu

“…Additionally, an adaptive feature pruning module is introduced to dynamically select critical features based on their importance, reducing redundancy and enhancing model accuracy by 6%. The decoder innovatively fuses two different types of features and leverages BiGRU to compensate for the limitations of the attention mechanism in capturing degradation features, resulting in a 7% accuracy improvement. …”
Get full text

Inversion of Magnetic Anomaly Based on Cross Attention Transformer by Juntao Lei, Jieru Chi, Shandong Li

“…Our method employs a hierarchical encoder-decoder network constructed with Transformer Blocks and introduces three key innovations: 1) We propose a Transformer Block based on cross-attention mechanism. …”
Get full text

DoubleNet: A Method for Generating Navigation Lines of Unstructured Soil Roads in a Vineyard Based on CNN and Transformer by Xuezhi Cui, Licheng Zhu, Bo Zhao, Ruixue Wang, Zhenhao Han, Kunlei Lu, Xuguang Feng, Jipeng Ni, Xiaoyi Cui

“…This research introduces DoubleNet, an innovative deep-learning model designed to generate navigation lines for such conditions. …”
Get full text

Swin-ReshoUnet: A Seismic Profile Signal Reconstruction Method Integrating Hierarchical Convolution, ORCA Attention, and Residual Channel Attention Mechanism by Jie Rao, Mingju Chen, Xiaofei Song, Chen Xie, Xueyang Duan, Xiao Hu, Senyuan Li, Xingyue Zhang

“…The encoder uses a hierarchical convolution module to build a multi-scale feature pyramid, enhancing cross-scale geological signal representation. The decoder replaces traditional self-attention with ORCA attention to enable global context modeling with lower computational cost. …”
Get full text

Water Body Extraction Method Based on ConvNeXt and Dual Feature Extraction Branch by ZHOU Ke, CHANG Ranran, XU Xizhi, MIAO Ru, ZHANG Guangyu, WANG Jiaqian

Get full text

SAM-Based Efficient Feature Integration Network for Remote Sensing Change Detection: A Case Study on Macao Sea Reclamation by Junqing Huang, Junqi Bao, Min Xia, Xiaochen Yuan

Get full text

AttenCRF-U: Joint Detection of Sleep-Disordered Breathing and Leg Movements in OSA Patients by Qiuyue Li, Kewei Li, Cong Fu, Yiyuan Zhang, Huan Yu, Chen Chen, Wei Chen

Get full text

The analysis of interactive furniture design system based on artificial intelligence by Xiaohong Jiang

“…Compared to other deep learning architectures (e.g., encoder-decoder networks), GAN excels in generating realistic and creative furniture design solutions. …”
Get full text

Architectural Synergies in Bi-Modal and Bi-Contrastive Learning by Yujia Gu, Brian Liu, Tianlong Zhang, Xinye Sha, Shiyong Chen

“…This paper introduces an innovative architecture known as the Zero-shot Unified Image-Text (ZsU-IT) framework, which synthesizes pre-training objectives into a cohesive Unicode-decoder structure. …”
Get full text

An enhanced deep learning-based feature extraction framework for moving object detection by Upasana Panigrahi, Prabodh Kumar Sahoo, Manoj Kumar Panda, Aswini Kumar Samantaray, Ganapati Panda

“…This article introduces an innovative Moving Object Detection Algorithm (MODA) for detecting moving objects for benchmark CD-Net 2014, WallFlower, Star, STERE, DUTS, NLPR, NJU2K, and SIP datasets. …”
Get full text

3D-SCUMamba: An Abdominal Tumor Segmentation Model by Juwita, Ghulam Mubashar Hassan, Amitava Datta

“…In this article, we propose 3D-SCUMamba, an innovative architecture strategically integrating State Space Modeling-Based deep learning (Mamba) within the bottleneck of the encoder-decoder structure to overcome the limitations of existing segmentation networks. …”
Get full text

MAMNet: Lightweight Multi-Attention Collaborative Network for Fine-Grained Cropland Extraction from Gaofen-2 Remote Sensing Imagery by Jiayong Wu, Xue Ding, Jinliang Wang, Jiya Pan

“…To address the issues of high computational complexity and boundary feature loss encountered when extracting farmland information from high-resolution remote sensing images, this study proposes an innovative CNN–Transformer hybrid network, MAMNet. This framework integrates a lightweight encoder, a global–local Transformer decoder, and a bidirectional attention architecture to achieve efficient and accurate farmland information extraction. …”
Get full text

LCCDMamba: Visual State Space Model for Land Cover Change Detection of VHR Remote Sensing Images by Junqing Huang, Xiaochen Yuan, Chan-Tong Lam, Yapeng Wang, Min Xia

Get full text

DANNET: deep attention neural network for efficient ear identification in biometrics by Deepthy Mary Alex, Kalpana Chowdary M., Hanan Abdullah Mengash, Venkata Dasu M., Natalia Kryvinska, Chinna Babu J., Ajmeera Kiran

“…This innovative approach leverages the strengths of encoder-decoder architectures and attention mechanisms to enhance the precision and reliability of ear detection and segmentation. …”
Get full text