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

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Enhancing Real Estate Listings Through Image Classification and Enhancement: A Comparative Study by Eyüp Tolunay Küp, Melih Sözdinler, Ali Hakan Işık, Yalçın Doksanbir, Gökhan Akpınar

“…Each model’s performance and benchmark results were measured to identify the most effective method. In addition, the classification pipeline was expanded using image enhancement with contrastive unsupervised representation learning (CURL). …”
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A review of plant leaf disease identification by deep learning algorithms by Junmin Zhao, Laixiang Xu, Zizhen Ma, Juncai Li, Xiaowei Wang, Yunchang Liu, Xiaojie Du

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Node Classification Based on Kolmogorov-Arnold Networks by YUAN Lining, FENG Wengang, LIU Zhao

“…Most graph deep learning methods extract feature information from graph data by using learnable weights and specific activation functions. …”
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Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques by Chinna Gopi Simhadri, Hari Kishan Kondaveeti, Valli Kumari Vatsavayi, Alakananda Mitra, Preethi Ananthachari

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Artificial Intelligence and Hand Hygiene Accuracy: A New Era in Infection Control for Dental Practices by Salwa A. Aldahlawi, Amr H. Almoallim, Ibtesam K. Afifi

“…Step 3 (back of fingers to opposing palm with fingers interlocked) was consistently identified as the most frequently missed step by both the AI model and the infection control auditors. …”
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Automated classification of chest X-rays: a deep learning approach with attention mechanisms by Burcu Oltu, Selda Güney, Seniha Esen Yuksel, Berna Dengiz

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A Multispectral Feature Selection Method Based on a Dual-Attention Network for the Accurate Estimation of Fractional Vegetation Cover in Winter Wheat by Runzhi Yang, Shanshan Li, Bing Zhang, Quanjun Jiao, Dailiang Peng, Songlin Yang, Ruyi Yu

“…Band 3 (Green), band 4 (Red), band 5 (Red-edge 1), and band 6 (Red-edge 2) of Sentinel-2 satellite images contribute most significantly to winter wheat FVC estimation, achieving an accuracy comparable to that obtained using all bands, while reducing the training time by 19.1%, as confirmed by field survey data.…”
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MeetSafe: enhancing robustness against white-box adversarial examples by Ruben Stenhuis, Dazhuang Liu, Yanqi Qiao, Mauro Conti, Manos Panaousis, Kaitai Liang

“…Convolutional neural networks (CNNs) are vulnerable to adversarial attacks in computer vision tasks. …”
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Improving Solar Radiation Forecasting in Cloudy Conditions by Integrating Satellite Observations by Qiangsheng Bu, Shuyi Zhuang, Fei Luo, Zhigang Ye, Yubo Yuan, Tianrui Ma, Tao Da

“…Solar radiation forecasting is the basis of building a robust solar power system. Most ground-based forecasting methods are unable to consider the impact of cloud changes on future solar radiation. …”
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Multimodal driver emotion recognition using motor activity and facial expressions by Carlos H. Espino-Salinas, Huizilopoztli Luna-García, José M. Celaya-Padilla, Cristian Barría-Huidobro, Nadia Karina Gamboa Rosales, David Rondon, Klinge Orlando Villalba-Condori

“…The research applies machine learning to identify the most relevant motor activity signals for emotion recognition. …”
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Opposition-Based White Shark Optimizer for Optimizing Modified EfficientNetV2 in Road Crack Classification by Mohammed Al-Shalabi, Mohammed A. Mahdi, Malik Braik, Mohammed Azmi Al-Betar, Shahanawaj Ahamad, Sawsan A. Saad

“…The outcome emphasizes its ability to identify the most effective solution for crack detection in practical scenarios, where PCA-based feature selection improves computational efficiency without compromising performance. …”
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Design of a hybrid AI network circuit for epilepsy detection with 97.5% accuracy and low cost-latency by Liufang Sheng, Xuanxu Chen, Yuejun Zhang, Ke Yan, Junping Chen, Zhikang Chen, Hanyu Shi, Yi Gong

“…Then, the design of the multiply-accumulate circuit was completed using a parallel-style row computation method, and a pipelined convolutional computation circuit was used to accelerate the convolutional computation and reduce the computational overhead and delay. …”
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Classifying sex with volume-matched brain MRI by Matthis Ebel, Martin Domin, Nicola Neumann, Carsten Oliver Schmidt, Martin Lotze, Mario Stanke

“…MRI data was used from two population-based data sets of 3298 mostly older adults from the Study of Health in Pomerania (SHIP) and 399 mostly younger adults from the Human Connectome Project (HCP), respectively. …”
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Enhancing maize LAI estimation accuracy using unmanned aerial vehicle remote sensing and deep learning techniques by Zhen Chen, Weiguang Zhai, Qian Cheng

“…Therefore, this study evaluates the potential of multi-source feature fusion and convolutional neural networks (CNN) in estimating maize LAI. …”
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A Two-Stage Method for Diagnosing COVID-19, Leveraging CNN, and Transfer Learning on CT Scan Images by Touba torabipour, Abolfazl Gandomi, Mohammad Ghanimi

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Vision-Based American Sign Language Classification Approach via Deep Learning by Nelly Elsayed

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MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation by Muna Khalaf, Ban N. Dhannoon

“…The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. …”
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A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion by Jing Mao, Lianming Sun, Jie Chen, Shunyuan Yu

“…Convolutional neural networks have achieved excellent results in image denoising; however, there are still some problems: (1) The majority of single-branch models cannot fully exploit the image features and often suffer from the loss of information. (2) Most of the deep CNNs have inadequate edge feature extraction and saturated performance problems. …”
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Crowd anomaly estimation and detection: A review by A. Hussein, M.W. Raed, A. Al-Shaikhi, M. Mohandes, B. Liu

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