Semiconductor Wafer Defect Recognition Based on Improved Coordinate Attention Mechanism by Hao He, Yuanjie Wei, Xionghao Lin, Minmin Zhu, Haizhong Zhang

“…With improvements in computing power, computer vision based on convolutional neural networks has demonstrated notable advantages in defect recognition. …”
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MSAmix-Net: Diabetic Retinopathy Classification by Jianyun Gao, Shu Li, Yiwen Chen, Rongwu Xiang

“…With the development of deep learning, various automatic diagnosis models for DR have been proposed. Most models are based on convolutional neural networks, but due to the small size of convolution kernels in shallow networks, the receptive field is limited, preventing the capture of global information. …”
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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

“…Compared to traditional methods, deep learning-driven approaches exhibit superiority in the aspect of stability and efficiency. Currently, most segmentation methods use a single neural network to encode SAR images, then decode them through interpolation or transpose convolution operations, and finally obtain the segmented building area images using a loss function. …”
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YOLO-RDM: A high accuracy and efficient algorithm for magnetic tile surface defect detection with practical applications. by Wei Niu, Cheng Lv, Enxu Zhang, Zhongbin Wei

“…By using a lightweight convolution method, we replace the traditional convolution in the original network, thereby improving the feature extraction ability of the model and achieving lightweight processing. …”
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A Lightweight Semantic- and Graph-Guided Network for Advanced Optical Remote Sensing Image Salient Object Detection by Jie Liu, Jinpeng He, Huaixin Chen, Ruoyu Yang, Ying Huang

“…In recent years, numerous advanced lightweight models have been proposed for salient object detection (SOD) in optical remote sensing images (ORSI). However, most methods still face challenges such as performance limitations and imbalances between accuracy and computational cost. …”
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A novel multi-scale and fine-grained network for large choroidal vessels segmentation in OCT by Wei Huang, Qifeng Yan, Lei Mou, Yitian Zhao, Wei Chen, Wei Chen, Wei Chen

“…The experimental results show that the proposed method has the best performance compared to the most advanced segmentation networks currently available. …”
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Partial feature reparameterization and shallow-level interaction for remote sensing object detection by Minh Tai Pham Nguyen, Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Minh Khue Phan Tran, Tadashi Nakano, Thi Hong Tran

“…As a result, our proposed detector obtains a competitive performance that outperforms most of the other large-size models and SOTA works. …”
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YOLO-WTB: Improved YOLOv12n Model for Detecting Small Damage of Wind Turbine Blades From Aerial Imagery by Phat T. Nguyen, Duy C. Huynh, Loc D. Ho, Matthew W. Dunnigan

“…In addition, in the backbone part, we also propose to remove a Convolution module and an Area Attention Concatenate-Convolution-Fusion module and add an improved SoftPool Feature Spatial Pyramid Pooling - Fast module to increase the feature extraction ability while maintaining the complexity of the model. …”
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A Bridge Structure 3D Representation for Deep Neural Network and Its Application in Frequency Estimation by Kejian Hu, Xiaoguang Wu

“…Currently, most predictions related to bridge geometry use shallow neural networks, which limit the network’s ability to fit since the input form limits the depth of the neural network. …”
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Application of DEO Method to Solving Fuzzy Multiobjective Optimal Control Problem by Latafat A. Gardashova

“…On the other hand, the number of the criteria is not small and most of them are integral criteria. Due to the above mentioned aspects, solving the considered problem by using convolution of criteria into one criterion would lead to loss of information and also would be counterintuitive and complex. …”
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A new approach to the room impulse response simulation by H. Łopacz, R. Marczuk

“…The most important problem of room acoustics is the evaluation of the acoustic quality of projected and modernized rooms. …”
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ORD-YOLO: A Ripeness Recognition Method for Citrus Fruits in Complex Environments by Zhaobo Huang, Xianhui Li, Shitong Fan, Yang Liu, Huan Zou, Xiangchun He, Shuai Xu, Jianghua Zhao, Wenfeng Li

“…First, the standard convolution operations are replaced with Omni-Dimensional Dynamic Convolution (ODConv) to improve feature extraction capabilities. …”
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WSN intrusion detection method using improved spatiotemporal ResNet and GAN by Yang Jing

“…A network intrusion detection method that integrates improved spatiotemporal residual network and generative adversarial network (GAN) in a big data environment is proposed to address the issues of poor feature extraction and significant impact from data imbalance in most existing intrusion detection methods. First, GANs are used for wireless sensor network data resampling to generate new sample sets, thereby overcoming the impact of data imbalance. …”
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Semi-supervised machine learning for primary user emulation attack detection and prevention through core-based analytics for cognitive radio networks by Sundar Srinivasan, KB Shivakumar, Muazzam Mohammad

“…Selfish attacks among other attacks are the most challenging, in which a secondary user or an unauthorized user with unlicensed spectrum pretends to be a primary user by altering the signal characteristics. …”
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Load Reconstruction Technique Using D-Optimal Design and Markov Parameters by Deepak K. Gupta, Anoop K. Dhingra

“…It has been noted that the computation of inverse Markov parameters, like most other inverse problems, is ill-conditioned which causes their convolution with the measured response to become quite sensitive to errors in system modeling and response measurements. …”
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GNN for LoRa Device Fingerprint Identification by Bojun Zhang

“…It calculates the similarity between signals using the Wasserstein distance and selects the top K most similar signals for each as first-order neighbors through heap sorting, constructing phase and RSSI(Received Signal Strength Indicator) graphs and transforming the signal classification problem into a graph-based node classification problem. …”
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Stationary Underdispersed INAR(1) Models based on the Backward Approach by Emad-Eldin A. A. Aly, Nadjib Bouzar

“… Most of the stationary first-order autoregressive integer-valued (INAR(1)) models in the literature have been developed using the idea of binomial thinning. …”
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University proceedings. Volga region. Technical sciences by V.I. Volchikhin, A.I. Ivanov, A.V. Bezyaev, I.A. Filipov

“…Replacing classical statistical criteria with their equivalent binary neurons provides significant redundancy of the output code of the neural network, which isconvolved with error elimination. The mechanism of convolution of code redundancy can be improved if the most informative part of the neuron response is not quantized. …”

EcoDetect-YOLOv2: A High-Performance Model for Multi-Scale Waste Detection in Complex Surveillance Environments by Jing Su, Ruihan Chen, Mingzhi Li, Shenlin Liu, Guobao Xu, Zanhong Zheng

“…Conventional waste monitoring relies heavily on manual inspection, while most detection models are trained on close-range, simplified datasets, limiting their applicability for real-world surveillance. …”
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Impact of increased anthropogenic Amazon wildfires on Antarctic Sea ice melt via albedo reduction by Sudip Chakraborty, Maloy Kumar Devnath, Atefeh Jabeli, Chhaya Kulkarni, Gehan Boteju, Jianwu Wang, Vandana P. Janeja

“…This study also employs the matrix profile and convolution operation of the Convolution Neural Network (CNN) to detect anomalous events in sea ice loss. …”
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