TW-YOLO: An Innovative Blood Cell Detection Model Based on Multi-Scale Feature Fusion by Dingming Zhang, Yangcheng Bu, Qiaohong Chen, Shengbo Cai, Yichi Zhang

“…At the same time, utilizing the feature pyramid architecture of YOLO (You Only Look Once), we enhanced the fusion of features at different scales by incorporating the CBAM (Convolutional Block Attention Module) in the detection head and the EMA (Efficient Multi-Scale Attention) module in the neck, thereby improving the recognition ability of blood cells. …”
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Scene Text Detection Based on Multi-scale Feature Extraction and Bidirectional Feature Fusion by LIAN Zhe, YIN Yanjun, ZHI Min, XU Qiaozhi

“…However, single-scale convolution methods are usually difficult to take into account the feature representation of text targets with different shapes and scales. …”
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Security application of intrusion detection model based on deep learning in english online education by Xue Li, Yugui Zhang

“…This model uses one dimensional convolution to construct a multi scale convolution structure to extract network data feature information of different scales. …”
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A lightweight hyperspectral image multi-layer feature fusion classification method based on spatial and channel reconstruction. by Yuping Yin, Haodong Zhu, Lin Wei

“…Hyperspectral Image (HSI) classification tasks are usually impacted by Convolutional Neural Networks (CNN). Specifically, the majority of models using traditional convolutions for HSI classification tasks extract redundant information due to the convolution layer, which makes the subsequent network structure produce a large number of parameters and complex computations, so as to limit their classification effectiveness, particularly in situations with constraints on computational power and storage capacity. …”
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An Efficient CNN for Hand X-Ray Overall Scoring of Rheumatoid Arthritis by Zijian Wang, Jian Liu, Zongyun Gu, Chuanfu Li

“…The depthwise separable (Dwise) convolution technique is used based on ResNet-50 due to the high resolution of hand X-rays. …”
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Attention-mechanism-based tracking method for intelligent Internet of vehicles by Xu Kang, Bin Song, Jie Guo, Xiaojiang Du, Mohsen Guizani

“…Beyond the traditional Global Positioning System sensor, the image sensor can capture different kinds of vehicles, analyze their driving situation, and can interact with them. …”
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Health condition prediction method of the computer numerical control machine tool parts by ensembling digital twins and improved LSTM networks by Chen Guo, Yin Haifang

“…The proposed model is predicated on a convolutional neural network and a long and short-term memory network, the purpose of which is to extract the feature data of CNC machine tool parts. …”
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A deep learning-based algorithm for the detection of personal protective equipment. by Bo Tong, Guan Li, Xiangli Bu, Yang Wang, Xingchen Yu

“…To address this issue, this paper proposes an improved model based on YOLOv8n.By enriching feature diversity and enhancing the model's adaptability to geometric transformations, the detection accuracy is improved.A Multi-Scale Group Convolution Module (MSGP) was designed to extract multi-level features using different convolution kernels. …”
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MA-YOLO: A Pest Target Detection Algorithm with Multi-Scale Fusion and Attention Mechanism by Yongzong Lu, Pengfei Liu, Chong Tan

“…Agricultural pest detection is critical for crop protection and food security, yet existing methods suffer from low computational efficiency and poor generalization due to imbalanced data distribution, minimal inter-class variations among pest categories, and significant intra-class differences. To address the high computational complexity and inadequate feature representation in traditional convolutional networks, this study proposes MA-YOLO, an agricultural pest detection model based on multi-scale fusion and attention mechanisms. …”
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Dense-TNT: Efficient Vehicle Type Classification Neural Network Using Satellite Imagery by Ruikang Luo, Yaofeng Song, Longfei Ye, Rong Su

“…Vehicle data for three regions under four different weather conditions were deployed to evaluate the recognition capability. …”
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Pedestrian Detection in Fisheye Images Based on Improved YOLOv8 Algorithm by ZHU Yumin, SUN Guangling, MIAO Fei

“…The feature information of different scales is extracted through DWConv with different convolution kernels, and the CA and SA modules are combined to enhance the model’s feature expression ability. …”
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Caricature Face Photo Facial Attribute Similarity Generator by Muhammad Irfan Khan, Muhammad Kashif Hanif, Ramzan Talib

“…Furthermore, the ratio between different facial features was computed using different vertical and horizontal distances. …”
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End-to-End CNN conceptual model for a biometric authentication mechanism for ATM machines by Karthikeyan Velayuthapandian, Natchiyar Murugan, Saranya Paramasivan

“…The proposed system, which is based on biometrics and deep convolutional neural networks, can effectively resolve the problems associated with conventional ATM cards and PINs. …”
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Cotton Weed-YOLO: A Lightweight and Highly Accurate Cotton Weed Identification Model for Precision Agriculture by Jinghuan Hu, He Gong, Shijun Li, Ye Mu, Ying Guo, Yu Sun, Tianli Hu, Yu Bao

“…The Receptive Field Enhancement (RFE) module is proposed to enable the feature pyramid network to adapt to the feature information of different receptive fields. A Scale-Invariant Shared Convolutional Detection (SSCD) head is proposed to fully utilize the advantages of shared convolution and significantly reduce the number of parameters in the detection head. …”
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Adversarial sample generation algorithm for vertical federated learning by Xiaolin CHEN, Daoguang ZAN, Bingchao WU, Bei GUAN, Yongji WANG

“…To adapt to the scenario characteristics of vertical federated learning (VFL) applications regarding high communication cost, fast model iteration, and decentralized data storage, a generalized adversarial sample generation algorithm named VFL-GASG was proposed.Specifically, an adversarial sample generation framework was constructed for the VFL architecture.A white-box adversarial attack in the VFL was implemented by extending the centralized machine learning adversarial sample generation algorithm with different policies such as L-BFGS, FGSM, and C＆amp;W.By introducing deep convolutional generative adversarial network (DCGAN), an adversarial sample generation algorithm named VFL-GASG was designed to address the problem of universality in the generation of adversarial perturbations.Hidden layer vectors were utilized as local prior knowledge to train the adversarial perturbation generation model, and through a series of convolution-deconvolution network layers, finely crafted adversarial perturbations were produced.Experiments show that VFL-GASG can maintain a high attack success while achieving a higher generation efficiency, robustness, and generalization ability than the baseline algorithm, and further verify the impact of relevant settings for adversarial attacks.…”
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Packet-level labeling method for fine-grained multi-webpage browsing behavior recognition by GU Yue, CHEN Li, LI Dan, GAO Kaihui

“…This method combined one-dimensional convolutional neural networks with multi-head attention mechanisms to learn both local and global temporal correlation features between different packets within the same webpage. …”
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Integrating deformable CNN and attention mechanism into multi-scale graph neural network for few-shot image classification by Yongmin Liu, Fengjiao Xiao, Xinying Zheng, Weihao Deng, Haizhi Ma, Xinyao Su, Lei Wu

“…The algorithm first utilizes different convolution kernels in CNN to extract multi-scale local feature information, and then based on the global feature extraction ability of attention mechanism, parallel processing of channel and spatial attention mechanism is used to extract multidimensional global feature information. …”
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LMSOE-Net: lightweight multi-scale small object enhancement network for UAV aerial images by Zhixing Ma, Peidong Luo, Xiaole Shen

“…We further optimize the model by incorporating shared convolution with detail-enhancement capabilities in the detection head, which improves the detection of small objects across different scales. …”
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SMANet: A Model Combining SincNet, Multi-Branch Spatial—Temporal CNN, and Attention Mechanism for Motor Imagery BCI by Danjie Wang, Qingguo Wei

“…Firstly, Sinc convolution is utilized as a band-pass filter bank for data filtering; Second, pointwise convolution facilitates the effective integration of feature information across different frequency ranges, thereby enhancing the overall feature expression capability; Next, the resulting data are fed into the MBSTCNN to learn a deep feature representation. …”
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LBNet: A Lightweight Bilateral Network for Semantic Segmentation of Martian Rock by Pengfei Wei, Zezhou Sun, He Tian

“…In the deep semantic information branch, channel split convolution (CSConv) is adopted to extract features by adopting different convolution kernels on different channel, reducing the similarity between different feature maps and increasing feature maps diversity. …”
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