End-to-End Multi-Scale Adaptive Remote Sensing Image Dehazing Network by Xinhua Wang, Botao Yuan, Haoran Dong, Qiankun Hao, Zhuang Li

“…The design of this module can extract important image features at different scales. By expanding convolution, the receptive field is expanded to capture broader contextual information, thereby obtaining a more global feature representation. …”
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Predicting Gender from Twitter Text Messages Using Methods Based on Artificial Intelligence and Text Analysis by Md. Nyem Hasan Bhuiyan, Anisur Rahman

“…For this purpose, 2 different approaches, namely Neural Networks (NNs) and Machine Learning (ML), were used for classification. …”
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FLEDNet: Enhancing the Drone Classification in the Radio Frequency Domain by Boban Sazdic-Jotic, Milenko Andric, Boban Bondzulic, Slobodan Simic, Ivan Pokrajac

“…Researchers are actively pursuing advancements in convolutional neural networks and their application in anti-drone systems for drone classification tasks. …”
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Research on CNC Machine Tool Spindle Fault Diagnosis Method Based on DRSN–GCE Model by Xiaoxu Li, Jiahao Wang, Jianqiang Wang, Jixuan Wang, Jiaming Chen, Xuelian Yu

“…In the first step, the data are preprocessed by adding different noises with different ratios of signal to noise and different frequencies to the vibration signals. …”
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A Lightweight Forward–Backward Independent Temporal-Aware Causal Network for Speech Emotion Recognition by Sijia Fei, Qiang Feng, Fei Gao

“…Finally, different levels of forward-backward features are fused to refine historical-future emotion change trends and better perceive the details of emotion changes. …”
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An incremental learning framework for pipeline weld crack damage identification and leakage rate prediction by Jing Huang, Zhifen Zhang, Yanlong Yu, Yongjie Li, Shuai Zhang, Rui Qin, Ji Xing, Wei Cheng, Guangrui Wen, Xuefeng Chen

“…Then, according to the attenuation characteristics of acoustic emission signals, a portable input-attention module is designed to add different weights to the input sequence. Finally, the accurate prediction of leakage rate under different conditions is realized based on the temporal convolutional network. …”
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Corn variety identification based on improved EfficientNet lightweight neural network by Jinpu Xu, Jinpu Xu, Jinhao Lan, Guangjie Lv, Dexin Ma

“…The phenotypic characteristics of corn ears can be used to better classify and identify different varieties of corn, providing a reference for intelligent sorting of corn ears.…”
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Segmentation of Stone Slab Cracks Based on an Improved YOLOv8 Algorithm by Qitao Tian, Runshu Peng, Fuzeng Wang

“…Comparative tests and industrial validation demonstrate stable performance across different stone materials and textures and a 30% false-positive reduction in real production environments. …”
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Dual-Stream Architecture Enhanced by Soft-Attention Mechanism for Plant Species Classification by Imran Ullah Khan, Haseeb Ali Khan, Jong Weon Lee

“…Moreover, we have contributed a novel dataset that comprises 48 classes of different plant species. The results demonstrate a higher level of performance when compared to current models, emphasizing the capability of the dual-stream design in improving accuracy and model generalization. …”
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In-Wheel Motor Fault Diagnosis Method Based on Two-Stream 2DCNNs with DCBA Module by Junwei Zhu, Xupeng Ouyang, Zongkang Jiang, Yanlong Xu, Hongtao Xue, Huiyu Yue, Huayuan Feng

“…To address the challenge of fault diagnosis for in-wheel motors in four-wheel independent driving systems under variable driving conditions and harsh environments, this paper proposes a novel method based on two-stream 2DCNNs (two-dimensional convolutional neural networks) with a DCBA (depthwise convolution block attention) module. …”
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CDUNeXt: efficient ossification segmentation with large kernel and dual cross gate attention by Hailiang Xia, Chuantao Wang, Zhuoyuan Li, Yuchen Zhang, Shihe Hu, Jiliang Zhai

“…By designing lightweight module structures, utilizing large-kernel convolutions to extracts the long-distance dependencies of different features of the image, and adopting dual-cross-gate-attention(DCGA) to sequentially capture the channel and spatial dependencies so as to fast and accurate segmentation while maintaining fewer parameters and lower complexity. …”
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Automatic license-plate recognition by A. V. Poltavskii, T. G. Yurushkina, M. V. Yurushkin

“…Quality of the system is provided through the optimization of various models with different modifications. In particular, convolution neural networks were trained using images from several datasets. …”
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Lightweight and Low-Parametric Network for Hardware Inference of Obstructive Sleep Apnea by Tanmoy Paul, Omiya Hassan, Christina S. McCrae, Syed Kamrul Islam, Abu Saleh Mohammad Mosa

“…Using each type of convolution, three different models were developed using ECG, SpO₂, and model fusion. …”
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Wind Power Forecasting Based on Multi-Graph Neural Networks Considering External Disturbances by Xiaoyin Xu, Zhumei Luo, Menglong Feng

“…Extensive experiments across diverse wind farm clusters and different weather conditions indicate that GCN-EIF achieves an 18.99% lower RMSE and 5.08% lower MAE than state-of-the-art methods. …”
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FruitsMultiNet: A deep neural network approach to identify fruits through multi-scale feature fusion using mobile interface by Tasauf Mim, Md Mahbubur Rahman, Jahanur Biswas, Ahmad Shafkat, Khandaker Mohammad Mohi Uddin

“…The data were fragmented into training, testing, and validation sets for eight different fruits. The proposed FruitsMultiNet achieved a 99.84 % accuracy rate, which is greater than the accuracy rates of individual Deep Learning (DL) models. …”
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Optimizing Automated Hematoma Expansion Classification from Baseline and Follow-Up Head Computed Tomography by Anh T. Tran, Dmitriy Desser, Tal Zeevi, Gaby Abou Karam, Julia Zietz, Andrea Dell’Orco, Min-Chiun Chen, Ajay Malhotra, Adnan I. Qureshi, Santosh B. Murthy, Shahram Majidi, Guido J. Falcone, Kevin N. Sheth, Jawed Nawabi, Seyedmehdi Payabvash

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A Real-Time Cotton Boll Disease Detection Model Based on Enhanced YOLOv11n by Lei Yang, Wenhao Cui, Jingqian Li, Guotao Han, Qi Zhou, Yubin Lan, Jing Zhao, Yongliang Qiao

“…A dataset of cotton boll diseases under different lighting conditions and shooting angles in the field was constructed. …”
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Comparative study of citrus fruits (Citrus reticulata Blanco cv. Batu 55) detection and counting with single and double labels based on convolutional neural network using YOLOv7 by Dimas Firmanda Al Riza, Lucky Candra Musahada, Romzi Izzudin Aufa, Mochamad Bagus Hermanto, Hermawan Nugroho, Yusuf Hendrawan

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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…Interpretation: ConvNeXt and MobileNet DL models accurately distinguished OSCC from OPMD in clinical photographs taken with different types of image-capture devices. Grad-CAM proved to be an outstanding tool to improve performance interpretation. …”
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MCANet: An Unsupervised Multi-Constraint Cascaded Attention Network for Accurate and Smooth Brain Medical Image Registration by Min Huang, Haoyu Wang, Guanyu Ren

“…The registration subnetwork is called the dilated self-attention network (DSNet), which incorporates dilated convolution combinations with different dilation rates and attention gate modules. …”
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