Adaptive pixel attention network for hyperspectral image classification by Yuefeng Zhao, Chengmin Zai, Nannan Hu, Lu Shi, Xue Zhou, Jingqi Sun

“…More importantly, we also propose a new Adaptive Pixel Attention mechanism, which explores Cosine and Euclidean similarity to adaptively explore the distance and angle relationship between pixels of different scale convolution patch features. Moreover, the Cross-Layer Information Complement module is designed to form a contextual interaction by integrating the output features of different convolution layers, which can prevent the omission of discriminative information and further improve the network performance. …”
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Twofold dynamic attention guided deep network and noise-aware mechanism for image denoising by Zihao Chen, Alex Noel Joseph Raj, Vijayarajan Rajangam, Wei Li, Vijayalakshmi G.V. Mahesh, Zhemin Zhuang

“…Convolutional neural networks are given extensive attention towards noise removal due to their good performance over traditional denoising algorithms. …”
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Scmaskgan: masked multi-scale CNN and attention-enhanced GAN for scRNA-seq dropout imputation by You Wu, Li Xu, Xiaohong Cong, Hanxiao Li, Yanli Li

“…Specifically, we integrate masking, convolutional neural networks (CNNs), attention mechanisms, and residual networks (ResNets) to effectively address dropout events in scRNA-seq data. …”
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Multi-Function Working Mode Recognition Based on Multi-Feature Joint Learning by Lei Liu, Minghua Wu, Dongyang Cheng, Wei Wang

“…This hybrid model leverages the local convolution operations of the CNN module to extract local characters from radar pulse sequences, capturing the dynamic patterns of radar waveforms across different modes. …”
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A fine‐grained image classification method based on information interaction by Shuo Zhu, Xukang Zhang, Yu Wang, Zongyang Wang, Jiahao Sun

“…The experimental results show that the method has good generalization on different datasets.…”
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Real-Time Corn Variety Recognition Using an Efficient DenXt Architecture with Lightweight Optimizations by Jin Zhao, Chengzhong Liu, Junying Han, Yuqian Zhou, Yongsheng Li, Linzhe Zhang

“…Corn varieties from different regions have significant differences inblade, staminate and root cap characteristics, and these differences provide a basis for variety classification. …”
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Adaptation of image reconstruction algorithm for purposes of ultrasound transmission tomography (UTT) by A. B. DOBRUCKI, K. J. OPIELIŃSKI

“…In this research, the convolution and backprojection method has been adapted for the purposes of image reconstruction in ultrasound transmission tomography (UTT). …”
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Cross-Modal Object Detection Based on Content-Guided Feature Fusion and Self-Calibration by Liyang Ning, Xuxun Liu, Luoyu Zhou, Xueyu Zou

“…First, we introduce a parallel network in the backbone to enable the model to process information from different modalities simultaneously. Second, we design a content-guided fusion module (CGF) in the feature extraction network, leveraging both transformer and convolution operations to capture global and local information, thereby enhancing the model’s ability to focus on detailed object features. …”
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Short-term photovoltaic power forecasting based on a new hybrid deep learning model incorporating transfer learning strategy by Tiandong Ma, Feng Li, Renlong Gao, Siyu Hu, Wenwen Ma

“…First, the processed data are input into the DCNN layer, and the dilation convolution mechanism captures the spatial features of the wide sensory field of the input data. …”
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PoseAlign network for hybrid structure in 2D human pose estimation by Jin Zhang, Yabo Yin, Wenzhong Yang, Doudou Ren, Danny Chen

“…Abstract In recent years, many Vision Transformers (ViTs)-based methods have become popular in the field of Human Pose Estimation (HPE) and have achieved excellent results. However, Convolutional Neural Networks (CNNs)-based architectures still have many advantages in the field of HPE. …”
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Remote sensing image Super-resolution reconstruction by fusing multi-scale receptive fields and hybrid transformer by Denghui Liu, Lin Zhong, Haiyang Wu, Songyang Li, Yida Li

“…The discriminator combines multi-scale convolution, global Transformer, and hierarchical feature discriminators, providing a comprehensive and refined evaluation of image quality. …”
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Semantic Segmentation of Brain Tumors Using a Local–Global Attention Model by Shuli Xing, Zhenwei Lai, Junxiong Zhu, Wenwu He, Guojun Mao

“…Additionally, the morphology and size of tumors can vary significantly among different patients. These factors pose considerable challenges for the precise segmentation of tumors and subsequent diagnosis. …”
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Speech Recognition in an Enclosure with a Long Reverberation Time by Jedrzej KOCINSKI, Edward OZIMEK

“…For the chosen measurement points, a convolution of the IRs with the Polish Sentence Test (PST) and logatome tests was made. …”
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ShipYOLO: An Enhanced Model for Ship Detection by Xu Han, Lining Zhao, Yue Ning, Jingfeng Hu

“…In the training process, the 3 × 3 convolution, 1 × 1 convolution, and identity parallel mode are used to replace the original feature extraction component (ResUnit) and more features are extracted. …”
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Deep Learning Model of Image Classification Using Machine Learning by Qing Lv, Suzhen Zhang, Yuechun Wang

“…Firstly, based on the analysis of the basic theory of neural network, this paper expounded the different types of convolution neural network and the basic process of its application in image classification. …”
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SFEF-Net: Scattering Feature Extraction and Fusion Network for Aircraft Detection in SAR Images by Qiang Zhou, Zongxu Pan, Ben Niu

“…Firstly, we proposed an innovative sparse convolution operator and applied it to feature extraction. …”
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On Symmetrical Sonin Kernels in Terms of Hypergeometric-Type Functions by Yuri Luchko

“…In this paper, a new class of kernels of integral transforms of the Laplace convolution type that we named symmetrical Sonin kernels is introduced and investigated. …”
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Classification of Satellite Image Time Series and Aerial Images Based on Multiscale Fusion and Multilevel Supervision by H. Kanyamahanga, M. Dorozynski, F. Rottensteiner

“…In this context, it is a challenge to train a classifier given the large difference in resolutions. We utilise convolutions to extract spatial information and consider self-attention in the temporal dimension for SITS. …”
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Two-stage Detection Method for Abnormal Cluster Cervical Cells by LIANG Yi-qin, ZHAO Si-qi, WANG Hai-tao, HE Yong-jun

“…The size and location of convolution kernel can be dynamically adjusted according to the current pathological image content, so as to adapt to the shape, size and other geometric changes of cervical cells in different clusters. …”
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YOLO-UIR: A Lightweight and Accurate Infrared Object Detection Network Using UAV Platforms by Chao Wang, Rongdi Wang, Ziwei Wu, Zetao Bian, Tao Huang

“…Moreover, the LSP module efficiently combines features from different distances using Large Receptive Field Convolution Layers, significantly enhancing the model’s long-range information capture capability. …”
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