Data-Driven Prediction of Grape Leaf Chlorophyll Content Using Hyperspectral Imaging and Convolutional Neural Networks by Minglu Zeng, Xinghui Zhu, Ling Wan, Jian Xu, Luming Shen

“…This study develops a data-driven integrated framework that combines hyperspectral imaging (HSI) and convolutional neural networks (CNNs) to predict the chlorophyll content in grape leaves, employing hyperspectral images and <i>chlorophyll a + b</i> content data. …”
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BreastCNet: Breast Cancer Detection, Classification, and Localization Convolutional Neural Network With Advanced Optimization Techniques by Hassan Mahichi, Vahid Ghods, Mohammad Karim Sohrabi, Arash Sabbaghi

“…This study introduced BreastCNet, a Convolutional Neural Network (CNN) with hyperparameter optimization and a multi-task learning framework, enhancing classification and lesion localization. …”
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Design of financial data analysis and visualization system combining fuzzy c-means and convolutional neural network by Tianxia Li

“…This work contributes a scalable, interpretable, and data-driven framework for financial analytics.…”
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Carotid plaque segmentation and classification using MRI-based plaque texture analysis and convolutional neural network by Zakarya Hasan Ahmed Abu Alregal, Gehad Abdullah Amran, Ali A. Al-Bakhrani, Saleh Abdul Amir Mohammad, Amerah Alabrah, Lubna Alkhalil, Abdalla Ibrahim, Maryam Ghaffar, Maryam Ghaffar

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Hybrid convolutional neural network optimized with an artificial algae algorithm for glaucoma screening using fundus images by M. Shanmuga Eswari, S. Balamurali, Lakshmana Kumar Ramasamy

“…Methods We combined computer vision algorithms with a convolutional network for fundus images and applied a faster region-based convolutional neural network (FRCNN) and artificial algae algorithm with support vector machine (AAASVM) classifiers. …”
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Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints by Fenghui Lian, Yingjie Sun, Meiyu Li

“…We evaluate the proposed framework on two public databases (NIH Pancreas-CT and MICCAI Sliver07). …”
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MCTGNet: A Multi-Scale Convolution and Hybrid Attention Network for Robust Motor Imagery EEG Decoding by Huangtao Zhan, Xinhui Li, Xun Song, Zhao Lv, Ping Li

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Fishing operation type recognition based on multi-branch convolutional neural network using trajectory data by Bohui Jiang, Weifeng Zhou

“…To address this, this study proposes a novel framework integrating Geohash-based geocoding with embedding techniques inspired by natural language processing to extract spatiotemporal features from trajectory sequences. …”
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Seafloor Sediment Classification Using Small-Sample Multi-Beam Data Based on Convolutional Neural Networks by Haibo Ma, Xianghua Lai, Taojun Hu, Xiaoming Fu, Xingwei Zhang, Sheng Song

“…To overcome the scarcity of seafloor sediment acoustic image data, we applied a deep convolutional generative adversarial network (DCGAN) for data augmentation, incorporating a de-normalization and anti-normalization module into the original DCGAN framework. …”
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A Focal Attention-Based Large Convolutional Kernel Network for Anomaly Detection of Coated Fuel Particles by Zhaochuan Hu, Jiang Yu, Hang Zhang, Jian Liu, Ning Chen, Rong Li

“…To address these issues, this study proposes an innovative focal attention-based large convolutional kernel network detection framework comprising three core modules. …”
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An Elliptic Kernel Unsupervised Autoencoder&#x2014;Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing by Estefania Alfaro-Mejia, Carlos J. Delgado, Vidya Manian

“…This article introduces the autoencoder graph ensemble model (AEGEM), a novel ensemble-based framework designed to enhance performance in both endmember extraction and abundance estimation. …”
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ACLC-Detection: A Network for Remote Sensing Image Detection Based on Attention Mechanism and Lightweight Convolution by Shaodong Liu, Faming Shao, Chenshan Yang, Juying Dai, Jinhong Xue, Qing Liu, Tao Zhang

“…To address this issue, a novel detection framework named ACLC-Detection has been introduced. …”
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EHC-GCN: Efficient Hierarchical Co-Occurrence Graph Convolution Network for Skeleton-Based Action Recognition by Ying Bai, Dongsheng Yang, Jing Xu, Lei Xu, Hongliang Wang

“…In this paper, we therefore propose an Efficient Hierarchical Co-occurrence Graph Convolution Network (EHC-GCN). By employing a simple and practical hierarchical co-occurrence framework to adjust the degree of feature aggregation on demand, we first use spatial graph convolution to learn the local features of joints and then aggregate the global features of all joints. …”
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Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network by Feng-Ping An

“…Moreover, through an in-depth study of the multicolumn convolutional neural network framework, this paper finds that the number of features and the convolution kernel size at different levels of the convolutional neural network are different. …”
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Residual capsule network with threshold convolution and attention mechanism for forest fire detection using UAV imagery by Soufiane Ben Othman, Obaid Ali

“…This paper introduces ResCaps-TC-Attn-Fire, a novel deep learning framework tailored for UAV-based forest fire detection, combining Residual-Capsule Networks, Threshold Convolution, and Attention Mechanisms. …”
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LS-MambaNet: Integrating Large Strip Convolution and Mamba Network for Remote Sensing Object Detection by Lingyu Yan, Zijian He, Zhiqi Zhang, Guangqi Xie

“…To address the above challenges, we propose a new target detection framework for complex remote sensing images, LS-MambaNet. …”
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A Novel Model for Predicting PM2.5 Concentrations Utilizing Graph Convolutional Networks and Transformer by Yuan Huang, Feilong Han, Qimeng Feng

“…In response, this paper proposes a new approach based on Graph Convolutional Networks (GCN) and Transformer. To enhance the model&#x2019;s predictive performance, we designed a new Transformer architecture named FFPformer, which incorporates the Fast Fourier Transform into the Transformer framework. …”
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Impact of the Radar Image Resolution of Military Objects on the Accuracy of their Classification by a Deep Convolutional Neural Network by I. F. Kupryashkin

“…An eight-layer convolutional neural network was designed, trained and tested using the Keras library and Tensorflow 2.0 framework. …”
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WaViT-CDC: Wavelet Vision Transformer With Central Difference Convolutions for Spatial-Frequency Deepfake Detection by Nour Eldin Alaa Badr, Jean-Christophe Nebel, Darrel Greenhill, Xing Liang

“…To address these challenges, a novel end-to-end Wavelet Central Difference Convolutional Vision Transformer framework is designed to enhance spatial-frequency deepfake detection. …”
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Precision Recognition of Rock Thin Section Images With Multi‐Head Self‐Attention Convolutional Neural Networks by Pengfei Lv, Weiying Chen, Xinyu Zou

“…We propose a lightweight framework that integrates the multi‐head self‐attention (MSA) mechanism into classical convolutional neural network (CNN) architectures, and is hereinafter denoted as MSA‐CNN. …”
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