Wavelet-Driven Multi-Band Feature Fusion for RGB-T Salient Object Detection by Jianxun Zhao, Xin Wen, Yu He, Xiaowei Yang, Kechen Song

“…First, input features are passed through the channel-wise criss-cross module (CCM) for cross-modal information fusion, adaptively adjusting the importance of features to generate rich fusion information. …”
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DDoS-MSCT: A DDoS Attack Detection Method Based on Multiscale Convolution and Transformer by Bangli Wang, Yuxuan Jiang, You Liao, Zhen Li

“…The DDoS-MSCT architecture introduces the DDoS-MSCT block, which consists of a local feature extraction module (LFEM) and a global feature extraction module (GFEM). …”
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An improved hybrid policy optimization method for economic-preference dispatch considering cross time-scales collaboration by Qianli Zhang, Hao Tang, Duanchao Li

“…In this paper, we present an improved DRL algorithm, called distributed partial-modulation proximal policy optimization (DPMPPO), to address this issue. …”
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SE-Enhancer: Low-Resource Machine Translation Based on Enhanced SimCSE and Layer Fusion by Dongsheng Wang, Qile Bo, Fei Wang, Liming Wang, Kun Tang

“…We first introduced an embed-fusion module to integrate word embeddings and sentence embeddings, thereby enriching the feature representation of source sentences. …”
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Axial-UNet++ Power Line Detection Network Based on Gated Axial Attention Mechanism by Ding Hu, Zihao Zheng, Yafei Liu, Chengkang Liu, Xiaoguo Zhang

“…Firstly, to tackle the issue of long-range dependencies in images and low sample quantity, a gated axial attention mechanism is introduced to expand the receptive field and improve the capture of relative positional biases in small datasets, thereby proposing a novel feature extraction module termed axial-channel local normalization module. …”
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Gradient pooling distillation network for lightweight single image super-resolution reconstruction by Zhiyong Hong, GuanJie Liang, Liping Xiong

“…Furthermore, we introduce the Feature Channel Attention module to accurately filter and strengthen pixel features crucial for recovering high-resolution images. …”
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A novel ensemble model for fall detection: leveraging CNN and BiLSTM with channel and temporal attention by Sarita Sahni, Sweta Jain, Sri Khetwat Saritha

“…The channel attention module uncovers interrelationships between variables. …”
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Two-Branch Filtering Generative Network Based on Transformer for Image Inpainting by Feihan Cao, Qifeng Zhu, Yasheng Chang, Min Sun

“…We specifically incorporate Dual Kernel Filtering Module (DKFM) into an encoder-decoder network. This module utilizes predictive filtering constructed from convolutions to leverage local interactions, while simultaneously employing a transformer architecture with kernels from the predictive network to capture global correlations. …”
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Tilting Pad Thrust Bearing Fault Diagnosis Based on Acoustic Emission Signal and Modified Multi-Feature Fusion Convolutional Neural Network by Meijiao Mao, Zhiwen Jiang, Zhifei Tan, Wenqiang Xiao, Guangchao Du

“…Subsequently, the squeeze-and-excitation (SE) module was employed to reallocate the weights of each channel and fuse the features of multi-channel signals. …”
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A High-Speed Finger Vein Recognition Network with Multi-Scale Convolutional Attention by Ziyun Zhang, Peng Liu, Chen Su, Shoufeng Tong

“…Existing research primarily focuses on improving recognition accuracy; however, this often comes at the cost of increased model complexity, which, in turn, affects recognition efficiency, making it difficult to balance accuracy and speed in practical applications. To address this issue, this paper proposes a high-accuracy and high-efficiency finger vein recognition model called Faster Multi-Scale Finger Vein Recognition Network (FMFVNet), which optimizes recognition speed through the FasterNet Block module while ensuring recognition accuracy with the Multi-Scale Convolutional Attention (MSCA) module. …”
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Two-Dimensional Coherent Polarization–Direction-of-Arrival Estimation Based on Sequence-Embedding Fusion Transformer by Zihan Wu, Jun Wang, Zhiquan Zhou

“…Additionally, an SEF module was proposed to fuse the spatial-polarization domain features from different dimensions. …”
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Plant Disease Detection and Classification Using Deep Learning Methods: A Comparison Study by Pei-Wern Chin, Kok-Why Ng, Naveen Palanichamy

“…The presence issue of inaccurate plant disease detection persists under real field conditions and most deep learning (DL) techniques still struggle to achieve real-time performance. …”
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Temperature Control During Storage of Raw Materials in the Process of Biodiesel Fuel Production by Anzhelika M. Eremeeva, Yury V. Ilyushin

“…In the modern conditions of the growing consumer market for environmentally friendly industries, the issue of optimizing resource-intensive and energy-intensive technological chains is acute. …”
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Application of network-based virtual instrument technology for remote inspection of vehicle by SHAO Yong-hua, BAO Yi-dan, WANG Li-da

“…A development module of network-based virtual instrument technology intended to be used for inspecting the performance of vehicle was presented. …”
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Branch error reduction criterion-based signal recursive decomposition and its application to wind power generation forecasting. by Fen Xiao, Siyu Yang, Xiao Li, Junhong Ni

“…Due to the ability of sidestepping mode aliasing and endpoint effects, variational mode decomposition (VMD) is usually used as the forecasting module of a hybrid model in time-series forecasting. …”
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MASFF-Net: Multiazimuth Scattering Feature Fusion Network for SAR Target Recognition by Huiqiang Zhang, Wei Wang, Jie Deng, Yue Guo, Shengqi Liu, Jun Zhang

“…Subsequently, we propose a hierarchical multiscale feature extraction module to explore the global semantic and local detail features of the target. …”
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EPLC-Pose: A Lightweight Student Posture Recognition Network Under Panoramic Classroom by Yanhong Ji, Yibo Jin, Zuxuan Wang, Suyan Tan

“…The network’s backbone and neck components have been enhanced by replacing the traditional C2F module with the innovative C-UIB module. Due to the advanced design of the C-UIB module, the number of parameters has been significantly reduced. …”
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A Reparameterization Feature Redundancy Extract Network for Unmanned Aerial Vehicles Detection by Shijie Zhang, Xu Yang, Chao Geng, Xinyang Li

“…We further enhance the adaptive nature of the Adown module by incorporating an adaptive spatial attention mechanism. …”
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A Spatial–Frequency Combined Transformer for Cloud Removal of Optical Remote Sensing Images by Fulian Zhao, Chenlong Ding, Xin Li, Runliang Xia, Caifeng Wu, Xin Lyu

“…The core of SFCRFormer is the spatial–frequency combined Transformer (SFCT) block, which implements cross-domain feature reinforcement through a dual-branch spatial attention (DBSA) module and frequency self-attention (FreSA) module to effectively capture global context information. …”
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OMSF2: optimizing multi-scale feature fusion learning for pneumoconiosis staging diagnosis through data specificity augmentation by Xueting Ren, Surong Chu, Guohua Ji, Zijuan Zhao, Juanjuan Zhao, Yan Qiang, Yangyang Wei, Yan Wang

“…However, they struggle with insufficient perception of small targets and gradient inconsistency in medical image detection tasks, hindering the full utilization of multi-scale features. To address these issues, we propose an Optimized Multi-Scale Feature Fusion learning framework, OMSF2, which includes the following components: (1) Data specificity augmentation module is introduced to capture intrinsic data representations and introduce diversity by learning morphological variations and lesion locations. (2) Multi-scale feature learning module is utilized that refines micro-feature localization guided by heatmaps, enabling full extraction of multi-directional features of subtle diffuse targets. (3) Multi-scale feature fusion module is employed that facilitates the fusion of high-level and low-level features to better understand subtle differences between disease stages. …”
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