Stock movement prediction with multimodal stable fusion via gated cross-attention mechanism by Chang Zong, Jian Wan, Lucia Cascone, Hang Zhou

“…The MSGCA framework consists of three integral components: (1) a trimodal encoding module, responsible for processing indicator sequences, dynamic documents, and a relational graph, and standardizing their feature representations; (2) a cross-feature fusion module, where primary and consistent features guide the multimodal fusion of the three modalities via a pair of gated cross-attention networks; and (3) a prediction module, which refines the fused features through temporal and dimensional reduction to execute precise movement forecasting. …”
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Label-Guided Data Augmentation for Chinese Named Entity Recognition by Miao Jiang, Honghui Chen

“…The LGDA model consists of three key components: a data augmentation module, a label semantic fusion module, and an optimized loss function. …”
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Multilevel Feature Interaction Network for Remote Sensing Images Semantic Segmentation by Hongkun Chen, Huilan Luo

“…Furthermore, to mitigate the semantic dilution issues caused by upsampling, a semantic-guided fusion module is introduced to enhance the propagation of rich semantic information among features. …”
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Optimization of TCN-BiLSTM for dissolved oxygen prediction based on improved sparrow search algorithm by Pei Shi, Mingjie Tang, Quan Wang, Xiaofei Ma

“…However, current DO prediction models often struggle with issues such as noise in the water quality data and insufficient feature extraction. …”
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HSF-YOLO: A Multi-Scale and Gradient-Aware Network for Small Object Detection in Remote Sensing Images by Fujun Wang, Xing Wang

“…Specifically, we introduce three tailored modules: Hybrid Atrous Enhanced Convolution (HAEC), a Spatial–Interactive–Shuffle attention module (C2f_SIS), and a Focal Gradient Refinement Loss (FGR-Loss). …”
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GESC-YOLO: Improved Lightweight Printed Circuit Board Defect Detection Based Algorithm by Xiangqiang Kong, Guangmin Liu, Yanchen Gao

“…First, a new lightweight module, C2f-GE, is designed to replace the C2f module of the backbone network, which effectively reduces the computational parameters, and at the same time increases the number of channels of the feature map to enhance the feature extraction capability of the model. …”
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Neural Network for Underwater Fish Image Segmentation Using an Enhanced Feature Pyramid Convolutional Architecture by Guang Yang, Junyi Yang, Wenyao Fan, Donghe Yang

“…However, typical underwater fish images often suffer from issues such as color distortion, low contrast, and blurriness, primarily due to the complex and dynamic nature of the marine environment. …”
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An improved EAE-DETR model for defect detection of server motherboard by Jian Chi, Mingke Zhang, Puhon Zhang, Guowang Niu, Zhihao Zheng

“…Lastly, we constructed the EUCB-SC upsampling module, which integrates depth convolution and channel shuffling strategies to enhance feature reconstruction efficiency. …”
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A Latent Multi-Scale Residual Transformer Approach for Cross-Modal Medical Image Synthesis by Xinmiao Zhu, Yang Li

“…Additionally, a multi-level information fusion (MIF) module is integrated into the encoder-decoder and latent feature space, consisting of a dual-scale selective fusion (DSF) module that adaptively aggregates multi-scale information to generate target modality images. …”
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Wind Farm Meteorological Prediction Model Based on Frequency Domain Feature Extraction Fusion Mechanism by Yichen Liao, Ziqi Gao, Xufeng Li

“…Specifically, this study addresses the issue of long-term dependency in the model by incorporating the Frequency Enhanced Attention module. …”
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Marine object detection in forward-looking sonar images via semantic-spatial feature enhancement by Zhen Wang, Zhen Wang, Jianxin Guo, Shanwen Zhang, Nan Xu

“…Furthermore, we adopt the Wise-IoUv3 loss function to mitigate the issue of class imbalance within marine sonar datasets and stabilize the model training process. …”
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Performance Analysis of Air Gap Membrane Distillation Process Enhanced with Air Injection for Water Desalination by Jonathan Ibarra-Bahena, Ulises Dehesa-Carrasco, Rogelio Servando Villalobos-Hernández, Sofía Garrido-Hoyos, Wilfrido Rivera

“…Water scarcity is a global issue, and desalination is an alternative to providing fresh water. …”
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Few-Shot Metric Learning with Time-Frequency Fusion for Specific Emitter Identification by Shiyuan Mu, Yong Zu, Shuai Chen, Shuyuan Yang, Zhixi Feng, Junyi Zhang

“…However, collecting and annotating substantial data for novel or unknown radiation sources is not only time-consuming but also cost-intensive. To address this issue, this paper proposes a few-shot (FS) metric learning-based time-frequency fusion network. …”
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Collaborative Filtering Recommendation-Based Random Negative Sampling and Graph Attention by Weiqiang Li, Xianghui Li, Xiaowen Liu, Xinhuan Chen, Ming Ma

“…In the loss optimization module, a random negative sampling strategy is incorporated as an auxiliary loss to mitigate the problem of imbalanced sample classes during training. …”
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Retrieval of Passive Seismic Virtual Source Data Under Non-Ideal Illumination Conditions Based on Enhanced U-Net by Wensha Huang, Pan Zhang, Binghui Zhao, Donghao Zhang, Liguo Han

“…By integrating a feature fusion module into U-Net, multi-scale sampling information is leveraged to improve the network’s ability to capture detailed PVS data features. …”
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IncSAR: A Dual Fusion Incremental Learning Framework for SAR Target Recognition by George Karantaidis, Athanasios Pantsios, Ioannis Kompatsiaris, Symeon Papadopoulos

“…The challenge of catastrophic forgetting, where models lose past knowledge when adapting to new tasks, remains a critical issue. In this paper, we introduce IncSAR, an incremental learning framework designed to tackle catastrophic forgetting in SAR target recognition. …”
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Food insecurity amongst Canadian children with food allergy during the COVID-19 pandemic by Zoe Harbottle, Jakob Pettersson, Michael A. Golding, Marina Jonsson, Leslie E. Roos, Jennifer L. P. Protudjer

“…We call on researchers and policy makers to attend to this important issue.…”
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Wavelet Guided Visual State Space Model and Patch Resampling Enhanced U-Shaped Structure for Skin Lesion Segmentation by Shuwan Feng, Xiaowei Chen, Shengzhi Li

“…By employing discrete wavelet transform, this module decomposes features into low and high-frequency components. …”
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EMCFormer: Equalized Multimodal Cues Fusion Transformer for Remote Sensing Visible-Infrared Object Detection Under Long-Tailed Distribution by Zian Wang, Xianghui Liao, Jin Yuan, Chen Lu, Zhiyong Li

“…However, visible-infrared remote sensing data often exhibits long-tail distribution characteristics, where some categories have sparse samples, resulting in insufficient training and poor detection performance for tail categories. To address this issue, this paper proposes an “Equalized Multi-modal Cues Fusion Transformer” (EMCFormer), incorporating an innovative “Multi-modal Heterogeneous Cues Aggregation” (MHCA) module and “Equalized-Adaptive Focal Loss” (EAFL). …”
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Residual channel attention based sample adaptation few-shot learning for hyperspectral image classification by Yuefeng Zhao, Jingqi Sun, Nannan Hu, Chengmin Zai, Yanwei Han

“…Furthermore, a new Random-based Feature Recalibration Module (RFRM) is proposed to reassign the feature weights via random matrix, which fully explore feature weight relationships to guide the sample adaptation process. …”
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