The Effective Evaluation of Emotions in the Visual Emotion Images Using Convolutional Neural Networks by Modestas Motiejauskas, Gintautas Dzemyda

“…This effectively improves the recognition of emotions when training a convolutional neural network against the baseline. The proposed contrastive-center loss function optimizes deep neural networks by enhancing feature discriminability. …”
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Lightweight Sheep Face Recognition Model Combining Grouped Convolution and Parameter Fusion by Gaochao Liu, Lijun Kang, Yongqiang Dai

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Multi-scale convolutional transformer network for motor imagery brain-computer interface by Wei Zhao, Baocan Zhang, Haifeng Zhou, Dezhi Wei, Chenxi Huang, Quan Lan

“…This study presents the Multi-Scale Convolutional Transformer (MSCFormer) model that integrates multiple CNN branches for multi-scale feature extraction and a Transformer module to capture global dependencies, followed by a fully connected layer for classification. …”
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ECOLOGICAL RESILIENCE ASSESSMENT FEATURES OF NATURAL-INDUSTRIAL SYSTEMS BY INDEX-BASED METHODS USING SOFT COMPUTING by A.V. Masloboev

Multifractal-Aware Convolutional Attention Synergistic Network for Carbon Market Price Forecasting by Liran Wei, Mingzhu Tang, Na Li, Jingwen Deng, Xinpeng Zhou, Haijun Hu

“…The fractal attention (FA) module calculates similarity matrices within a multi-scale feature space through multi-head attention, adaptively integrating multifractal market dynamics and implicit associations. …”
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SA-UMamba: Spatial attention convolutional neural networks for medical image segmentation. by Lei Liu, Zhao Huang, Shuai Wang, Jun Wang, Baosen Liu

“…However, Mamba and its variants are still limited in their ability to extract local receptive field features. To address this limitation, we propose a novel residual spatial state-space (RSSS) block that enhances spatial feature extraction by integrating global and local representations. …”
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A Convolutional Neural Network-Based Stress Prediction Method for Airfoil Structures by Wendi Jia, Quanlong Chen

“…The model incorporates a multi-scale feature extraction and attention mechanism based on Unet to capture complex stress distribution features more efficiently, and is applied to the stress prediction of wing skin structures. …”
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Enhanced Convolutional Neural Network for Accurate Crop Recommendation System on Climate Data by Adnan Myasar M., AI_Sadi Hafidh l., Abhilash Pideka Kundil

“…The chosen features are classified and Improved Convolutional Neural Network (ICNN) algorithm predicts crops accurately. …”
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Inverse link prediction with graph convolutional networks for knowledge-preserving sparsification in cheminformatics by Elnaz Bangian Tabrizi, Mehrdad Jalali, Mahboobeh Houshmand

“…The framework comprises four key components: (1) Graph Convolutional Networks (GCNs) to predict edge importance based on node features, (2) ILP to compute inverse weights identifying redundant edges, (3) dual-weight analysis to integrate initial similarity weights with GCN-derived weights, and (4) modularity optimization to prune edges while preserving community structures and domain knowledge. …”
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GCBAM-UNet: Sun Glare Segmentation Using Convolutional Block Attention Module by Nabila Zrira, Anwar Jimi, Mario Di Nardo, Issam Elafi, Maryam Gallab, Redouan Chahdi El Ouazzani

“…To further enhance the segmentation performance, we integrated a Convolutional Block Attention Module (CBAM), enabling the model to focus on important features in both spatial and channel dimensions. …”
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Hyper-LKCNet: Exploring the Utilization of Large Kernel Convolution for Hyperspectral Image Classification by Rong Liu, Zhilin Li, Jiaqi Yang, Jian Sun, Quanwei Liu

“…To explore the potential of large kernel convolution, we propose a hyperspectral image (HSI) classification algorithm in this article that utilizes a large kernel convolution module combined with multiscale coattention and an adaptive geometric feature (AGF) classifier, named Hyper-LKCNet. …”
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Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

“…The features are optimized using a Taylor-based African Vulture Optimization Algorithm (AVOA) and classified using a Bilinear Convolutional Attention Network (BCAN). …”
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VG-CGARN: Video Generation Using Convolutional Generative Adversarial and Recurrent Networks by Fatemeh Sobhani Manesh, Amin Nazari, Muharram Mansoorizadeh, MirHossein Dezfoulian

“…CNNs extract spatial features, LSTMs model temporal dynamics, and GANs enhance visual realism through adversarial training. …”
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Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

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Novel Wavelet Convolutional Neural Networks for Signal Detection in OFDM-IM Systems by Yang Zhao, SI-YU Zhang, Yuexia Zhang, Gongpu Wang, Behnam Shahrrava

“…The second network, named Single Network Wavelet Convolutions (SN-WTConv), features a more compact single stage design that combines wavelet convolution and CNN layers. …”
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The Detection and Classification of Scaphoid Fractures in Radiograph by Using a Convolutional Neural Network by Tai-Hua Yang, Yung-Nien Sun, Rong-Shiang Li, Ming-Huwi Horng

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A Deep Curriculum Learning Semi-Supervised Framework for Remote Sensing Scene Classification by Qing Zhang, Jialu Chen, Baohua Yuan

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Deep Learning-Based Interference Fringes Detection Using Convolutional Neural Network by Haowei Li, Chunxi Zhang, Ningfang Song, Huipeng Li

“…By integrating the feature maps of multiple layers and fine-tuning, the ability of the modified network to extract more complicated fringes is improved. …”
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Convolution Self-Guided Transformer for Diagnosis and Recognition of Crop Disease in Different Environments by Huinian Li, Nannan Li, Wenmin Wang, Chengcheng Yang, Ningxia Chen, Fuqin Deng

“…The proposed Convolution Self-Guided Transformer (CSGT) model integrates CNN’s local feature extraction with the Self-Guided Transformer’s(SGT) global information processing, enhancing the precision and efficiency of agricultural diagnostics. …”
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Dose Reduction in Scintigraphic Imaging Through Enhanced Convolutional Autoencoder-Based Denoising by Nikolaos Bouzianis, Ioannis Stathopoulos, Pipitsa Valsamaki, Efthymia Rapti, Ekaterini Trikopani, Vasiliki Apostolidou, Athanasia Kotini, Athanasios Zissimopoulos, Adam Adamopoulos, Efstratios Karavasilis

“…The ECAE architecture integrates multiscale feature extraction, channel attention mechanisms, and efficient residual blocks to reconstruct high-quality images from low-dose inputs. …”
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