The Cultural Value Validity of Digital Media Art Based on Deep Learning Network Model by Yuan Ruan

“…In order to solve this problem, this paper proposes a deep learning neural network model based on a dual-core compression activation module. The convolution kernels of different sizes in one module are used to extract the overall features and local details of the image, and another module is used to achieve the main goal. …”
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Restoration of a blurred photographic image of a moving object obtained at the resolution limit by V. B. Fedorov, S. G. Kharlamov, A. I. Starikovskiy

“…The proposed method for restoring a blurred photographic image of a moving object differs from traditional approaches in that the discrete convolution equation, to which the problem of restoring a blurred image is reduced, is obtained by approximating the corresponding integral equation based on the Kotelnikov interpolation series rather than on the traditional basis of the quadrature formula. …”
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Statistical Inference for Stochastic Differential Equations with Small Noises by Liang Shen, Qingsong Xu

“…The asymptotic distribution of the estimator is shown to be the convolution of a stable distribution and a normal distribution, which is completely different from the classical cases.…”
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Prediction of Mechanical Strength Based on Deep Learning Using the Scanning Electron Image of Microscopic Cemented Paste Backfill by Xuebin Qin, Shifu Cui, Lang Liu, Pai Wang, Mei Wang, Jie Xin

“…In addition, the difference between the measured and predicted values is calculated and the mean and variance of the error are analyzed. …”
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Approximate Crank–Nicolson Algorithm with Higher-Order PML Implementation for Plasma Simulation in Open Region Problems by Liqiang Niu, Yongjun Xie, Jie Gao, Peiyu Wu, Haolin Jiang

“…More precisely, the proposed implementation is based on the CN Direct-Splitting (CNDS) procedure for the finite-difference time-domain (FDTD) unmagnetized plasma simulation. …”
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A recognition model for winter peach fruits based on improved ResNet and multi-scale feature fusion by Yan Li, Chunping Li, Tingting Zhu, Shurong Zhang, Li Liu, Zhanpeng Guan

“…The GhostConv module further improves detection accuracy by reducing the number of convolution kernels. Additionally, the BiFPN structure strengthens the model’s ability to detect objects of different sizes by fusing multi-scale feature information. …”
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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 Novel Pseudo-Siamese Fusion Network for Enhancing Semantic Segmentation of Building Areas in Synthetic Aperture Radar Images by Mengguang Liao, Longcheng Huang, Shaoning Li

“…The experimental results of the SAR images from regions with different geographical characteristics demonstrate that the proposed PSANet outperforms several recent State-of-the-Art methods.…”
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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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Mechanical Properties Test and Strength Prediction on Basalt Fiber Reinforced Recycled Concrete by Min Huang, Yuru Zhao, Haonan Wang, Shihao Lin

“…In order to study the mechanical properties of basalt fiber reinforced recycled concrete (BFRRC), nine groups of tests are designed with three different replacement rates of recycled aggregates (40%, 70%, and 100%) and volume fraction of basalt fibers (0.1%, 0.2%, and 0.3%). …”
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MFA-net: Object detection for complex X-ray cargo and baggage security imagery. by Thanaporn Viriyasaranon, Seung-Hoon Chae, Jang-Hwan Choi

“…First, the multiscale dilated convolutional module converts the standard convolution of the detector backbone to a conditional convolution by aggregating the features from multiple dilated convolutions using dynamic feature selection to overcome the object-scale variant issue. …”
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Real-Time Optical Spectrum Fourier Transform With Time–Bandwidth Product Compression by Hao Sun, Xinyi Zhu, Wei Li, Ninghua Zhu, Ming Li

“…In addition, since the dispersive delay line could be programmable with high resolution, this technique is adaptable for different optical spectra and realizable for a reconfigurable TBP compression ratio. …”
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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

“…There was no statistical difference between the average scores given by two experienced radiologists and predicted scores from our model.…”
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Spatiotemporal Feature Enhancement for Lip-Reading: A Survey by Yinuo Ma, Xiao Sun

“…And each spatiotemporal feature enhancement method was divided into different subclasses based on the differences in the architecture structure, feature attributes, and application types. …”
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Intelligent Control System of Unmanned Vehicle Based on CAN Controller by Jinhua Wu, Yunfei Jiang, Fang Deng

“…In order to enable the driverless vehicle formation controller to automatically control the driving of the fleet, an intelligent driverless vehicle control system based on the CAN controller is proposed. Expansion convolution of different expansion rates is used to obtain multi-scale target information and to fuse the feature information at different scales during upsampling to enrich the semantic information. …”
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Research on herd sheep facial recognition based on multi-dimensional feature information fusion technology in complex environment by Fu Zhang, Fu Zhang, Xiaopeng Zhao, Shunqing Wang, Yubo Qiu, Sanling Fu, Yakun Zhang

“…For multi-part detection network, The YOLOv5s path aggregation network was modified by incorporating a multi-link convolution fusion block (MCFB) to enhance fine-grained feature extraction across objects of different sizes. …”
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Eisenstein Series Identities Involving the Borweins' Cubic Theta Functions by Ernest X. W. Xia, Olivia X. M. Yao

“…As applications, we evaluate some convolution sums. These evaluations are different from the formulas given by Alaca et al.…”
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Dual scale light weight cross attention transformer for skin lesion classification. by Dhirendra Prasad Yadav, Bhisham Sharma, Shivank Chauhan, Julian L Webber, Abolfazl Mehbodniya

“…The attention from different scales improved the spatial features by focusing on the different parts of the skin lesion. …”
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EEG–fNIRS signal integration for motor imagery classification using deep learning and evidence theory by Mohammed E. Seno, Niladri Maiti, Maulik Patel, Mihirkumar M. Patel, Kalpesh B. Chaudhary, Ashish Pasaya, Babacar Toure

“…For fNIRS signals, spatial convolution across all channels is employed to explore activation differences among brain regions, and parallel temporal convolution combined with a gated recurrent unit (GRU) captures richer temporal dynamics of the hemodynamic response. …”
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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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