Potato Disease and Pest Question Classification Based on Prompt Engineering and Gated Convolution by Wentao Tang, Zelin Hu

“…This mechanism only extracts the extreme value responses within the local receptive field, which leads to the degradation of fine-grained feature representation and significantly amplifies text noise. To address these issues, a dataset construction method based on prompt engineering is proposed, along with a question classification method utilizing a gated fusion–convolutional neural network (GF-CNN). …”
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EFM-ResNet: A Feature Enhanced Network for Tobacco Strips Classification by Bo Zhang, Shanshan Zheng, Leyuan Han, Yucan Qiu

“…In this paper, we propose a tobacco strip image classification model based on multi-scale fusion attention mechanism and feature enhancement improved ResNet, named EFM-ResNet, to address the issues of detail information loss during feature extraction and the difficulty in capturing long-range dependencies. …”
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Generative Adversarial learning with Negative Data Augmentation for Semi-supervised Text Classification by Shahriar Shayesteh, Diana Inkpen

“…Although FM addresses some of the critical issues of SS-GANs, these models still suffer from mode collapse with missing coverage outside the data manifold. …”
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GLNet: global-local feature network for wheat leaf disease image classification by Shangze Li, Shen Liu, Mingyu Ji, Yuhao Cao, Bai Yun, Bai Yun

“…Addressing the issues with insufficient multi-scale feature perception and incomplete understanding of global information in traditional convolutional neural networks for image classification of wheat leaf disease, this paper proposes a global local feature network, i.e. …”
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Highly Accurate Brain Tumor Segmentation and Classification Using Multiple Feature Sets by Megha Sunil Borse, Murali Prasad R, Tummala Ranga Babu

“…If a tumor is discovered later on, the medical issues are significant. Therefore, early diagnosis is essential. …”
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Dual-Branch Spatial–Spectral Transformer with Similarity Propagation for Hyperspectral Image Classification by Teng Wen, Heng Wang, Liguo Wang

“…Experimental results demonstrate that DBSSFormer-SP exhibits excellent classification performance.…”
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Disasters classification in a compound event perspective: insights from existing databases by Carlo De Michele, Fabiola Banfi, Maria Pia Russomando

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Spectral-Spatial Ensemble Low-Rank Domain Adaptation for Hyperspectral Image Classification by Xue Zhang, Guoguo Yang, Hongjun Su, Yiping Chen, Zhaohui Xue, Qian Du

“…Domain adaptation has been proven effective for addressing cross-domain hyperspectral image (HSI) classification, especially when the target domain has no labeled samples. …”
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Detection and Classification Expression of Visual Information Based on Artificial Intelligent Review Work by Nashwan J. Hussein, Amar A. Mahawish, Ibrahim Sami Attar

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DiffFormer: A Differential Spatial-Spectral Transformer for Hyperspectral Image Classification by Muhammad Ahmad, Manuel Mazzara, Salvatore Distefano, Adil Mehmood Khan, Silvia Liberata Ullo

“…To mitigate these issues, this work proposes the differential spatial-spectral transformer (<italic>DiffFormer</italic>), a novel framework designed to enhance feature discrimination and improve classification accuracy. …”
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Flat vs. Curved: Machine Learning Classification of Flexible PV Panel Geometries by Ahmad Manasrah, Yousef Jaradat, Mohammad Masoud, Mohammad Alia, Khaled Suwais, Piero Bevilacqua

“…However, they also showed overconfidence and underconfidence issues with the curved module geometries.…”
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Towards transparency in AI: Explainable bird species image classification for ecological research by Samparthi V.S. Kumar, Hari Kishan Kondaveeti

“…This study addresses these issues by employing Explainable Artificial Intelligence (XAI) to enhance the transparency of deep learning models for bird species image classification. …”
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The Imbalanced Target Classification Method Based on Mixed Learning of Virtual and Real Data by Fengyu Yang, Peng Wang, Wutao Qin, Zhangze Liao

“…We proposes a category imbalance classification model based on mixed feature enhancement between virtual and real domains to address the class imbalance problem in maritime target classification applications. …”
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Life cycle cost of communication towers: identification and hierarchical classification of influencing factors by Jing Zhang, Yang Wang, Qianyi Xu, Hongshuai Gao

“…While existing research has focused on structural optimization and technological advancements, few studies address cost-related issues across various stages, perspectives, and stakeholders. …”
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Optimizing forensic file classification: enhancing SFCS with βk hyperparameter tuning by D. Paul Joseph, Viswanathan Perumal

“…By integrating α, β, and βj into file classification systems, classification models converge to local optima with O(n log n* |V|) time complexity. …”
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Combining Transfer Learning and Ensemble Algorithms for Improved Citrus Leaf Disease Classification by Hongyan Zhu, Dani Wang, Yuzhen Wei, Xuran Zhang, Lin Li

“…Compared to traditional methods, the algorithm (integrating transfer learning Alexnet, VGG, and Resnet) we proposed can address the issues of limited categories, slow processing speed, and low recognition accuracy. …”
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Rice Leaf Nutrient Deficiency Classification System Using CAR-Capsule Network by M. Amudha, K. Brindha

“…Rice, a worldwide grown grain, frequently suffers production issues caused by nutrient imbalances, particularly potassium, nitrogen, and phosphorus. …”
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Unsupervised Segmentation and Classification of Waveform-Distortion Data Using Non-Active Current by Andrea Mariscotti, Rafael S. Salles, Sarah K. Rönnberg

“…The method can be applied to load identification and classification for non-intrusive load monitoring, with the aim of implementing automatic and unsupervised assessment of load behavior, including transient detection, power-quality issues and improvement in energy efficiency.…”
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Dual-Scale Complementary Spatial-Spectral Joint Model for Hyperspectral Image Classification by Huayue Chen, Yue Sun, Xiang Li, Bochuan Zheng, Tao Chen

“…This article proposes a novel dual-scale complementary spatial-spectral joint classification model (DSCSM) to mitigate the issues of detail loss and insufficient utilization of spatial information, which traditionally lead to lower classification accuracy. …”
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FishAI: Automated hierarchical marine fish image classification with vision transformer by Chenghan Yang, Peng Zhou, Chun‐Sheng Wang, Ge‐Yi Fu, Xue‐Wei Xu, Zhibin Niu, Lin Zhu, Ye Yuan, Hong‐Bin Shen, Xiaoyong Pan

“…Abstract To address the issues of high demand for efficiently recognizing fish species in marine scientific research, such as impact assessments on biodiversity and monitoring, an automated hierarchical image classification web‐based platform, named FishAI, was developed. …”
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