Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective by Arshi Baig, Azhar Zafar

“…The image analysis by AI and deep-learning algorithms offers insight into the future of screening in diabetes. …”
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Research on Digital Morphogenesis and Sustainability of 3D Printing Bionic Materials Based on Convolutional Neural Networks by Shaoting Zeng, Renshui Zhang, Yifei Cai

“…CNNs style transfer technologies are utilized, employing 53 cross-sectional images of 3D models as content images for the style transfer algorithm, alongside natural two-dimensional form images as style images. …”
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Quantum optical classifier with superexponential speedup by Simone Roncallo, Angela Rosy Morgillo, Chiara Macchiavello, Lorenzo Maccone, Seth Lloyd

“…Abstract Classification is a central task in deep learning algorithms. Usually, images are first captured and then processed by a sequence of operations, of which the artificial neuron represents one of the fundamental units. …”
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ICT-Net: A Framework for Multi-Domain Cross-View Geo-Localization with Multi-Source Remote Sensing Fusion by Min Wu, Sirui Xu, Ziwei Wang, Jin Dong, Gong Cheng, Xinlong Yu, Yang Liu

“…Furthermore, capitalizing on the Transformer’s flexible input processing mechanism, we develop an attention-guided non-uniform cropping strategy that dynamically eliminates redundant image patches with minimal impact on localization accuracy, thereby achieving enhanced computational efficiency. …”
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Deteksi Dan Klasifikasi Hama Potato Beetle Pada Tanaman Kentang Menggunakan YOLOV8 by Daniel Geoffrey Manurung, Mohammad Ryan Pinasthika, Muhammad Azka Obila Vasya, Rania Aprilia Dwi Setya Putri, Agustinus Parasian Tampubolon, Rakan Fadhil Prayata, Septia Khoirin Nisa, Novanto Yudistira

“…The Convolutional Neural Network (CNN) algorithm, which is effective in image processing, is utilized for the detection and classification of potato beetles. …”
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Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning by Spyridon Chavlis, Panayiota Poirazi

“…Abstract Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. …”
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Innovative approaches for skin disease identification in machine learning: A comprehensive study by Kuldeep Vayadande, Amol A. Bhosle, Rajendra G. Pawar, Deepali J. Joshi, Preeti A. Bailke, Om Lohade

“…Investigate the effectiveness and performance of several algorithms, such as the flexible k-nearest neighbor, the sturdy support vector machine (SVM), and the complex convolutional neural networks (CNNs), advanced techniques for automated skin disease detection encompass deep learning methods such as recurrent neural networks (RNNs) for sequential data processing, generative adversarial networks (GANs) for generating synthetic data, and attention mechanisms for focusing on relevant image regions by means of a thorough examination of the most recent studies. …”
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Autonomous Waste Classification Using Multi-Agent Systems and Blockchain: A Low-Cost Intelligent Approach by Sergio García González, David Cruz García, Rubén Herrero Pérez, Arturo Álvarez Sanchez, Gabriel Villarrubia González

“…Latency was kept below 9 ms per image with YOLOv12, ensuring smooth and lag-free processing, even for utilitarian embedded systems. …”
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ISEE: Industrial Internet of Things perception in solar cell detection based on edge computing by Meiya Dong, Jumin Zhao, Deng-ao Li, Biaokai Zhu, Sihai An, Zhaobin Liu

“…ISEE uses the edge device to collect the real-time video image of the solar panel through the camera. Then it uses the powerful neural network processing unit module of the edge computing unit, combined with the convolutional neural network algorithm transplanted to the edge, to detect the defects of solar panels in real time. …”
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Soybean–Corn Seedling Crop Row Detection for Agricultural Autonomous Navigation Based on GD-YOLOv10n-Seg by Tao Sun, Feixiang Le, Chen Cai, Yongkui Jin, Xinyu Xue, Longfei Cui

“…Firstly, the dataset of soybean–corn seedling crop rows was established, and the images were labeled with line labels. Then, an improved model GD-YOLOv10n-seg model was constructed by integrating GhostModule and DynamicConv into the YOLOv10n-segmentation model. …”
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Lightweight Vehicle Detection Based on Mamba_ViT by Ze Song, Yuhai Wang, Shuobo Xu, Peng Wang, Lele Liu

“…Current vehicle detection algorithms largely rely on deep learning techniques, enabling the automatic extraction of vehicle image features through convolutional neural networks (CNNs). …”
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AG-Yolo: Attention-Guided Yolo for Efficient Remote Sensing Oriented Object Detection by Xiaofeng Wang, Chengshan Han, Liang Huang, Ting Nie, Xin Liu, Hao Liu, Mingxuan Li

“…On the DOTA-v1.0 and DOTA-v1.5 datasets, compared with other advanced methods, our algorithm reduces the processing latency from 33.8 ms to 19.7 ms (a roughly 40% decrease) and produces a certain degree of improvement in the mAP metric.…”
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OCT-based diagnosis of glaucoma and glaucoma stages using explainable machine learning by Md Mahmudul Hasan, Jack Phu, Henrietta Wang, Arcot Sowmya, Michael Kalloniatis, Erik Meijering

“…To address the issue, this study uses optical coherence tomography (OCT) images to develop an explainable artificial intelligence (XAI) tool for diagnosing and staging glaucoma, with a focus on its clinical applicability. …”
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A rolling bearing fault diagnosis method based on GADF-CWT-GCNN by ZHANG Xiaoli, LUO Xin, LI Min, LIANG Wang, WANG Fangzhen

“…The sample sub-graph is imported into the convolutional neural network with the group normalization algorithm for diagnostic detection. The results show that the generalization ability of the data processing method and the model built in this paper in the small-sample environment is much higher than that of other network models such as the small vector machine and the 1D-CNN. …”
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Development of an artificial intelligence-based application for the diagnosis of sarcopenia: a retrospective cohort study using the health examination dataset by Chang-Won Jeong, Dong-Wook Lim, Si-Hyeong Noh, Sung Hyun Lee, Chul Park

“…Abstract Background Medical imaging techniques for diagnosing sarcopenia have been extensively investigated. …”
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A Spatiotemporal Fusion Network for Remote Sensing Based on Global Context Attention Mechanism by Weisheng Li, Yusha Liu, Yidong Peng, Fengyan Wu

“…Spatial-temporal fusion algorithms commonly encounter difficulties in effectively striking a balance between the extraction of intricate spatial details and changes over time. …”
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DiffBTS: A Lightweight Diffusion Model for 3D Multimodal Brain Tumor Segmentation by Zuxin Nie, Jiahong Yang, Chengxuan Li, Yaqin Wang, Jun Tang

“…However, their high complexity when processing 3D images remains a limitation. To mitigate this, researchers typically preprocess data into 2D slices, enabling the model to perform segmentation in a reduced 2D space. …”
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Combined L-Band Polarimetric SAR and GPR Data to Develop Models for Leak Detection in the Water Pipeline Networks by Yuyao Zhang, Hongliang Guan, Fuzhou Duan

“…The model features are selected with the Boruta wrapper algorithm based on the SAOCOM-1A images after pre-processing, and the SSRDC values at sampling locations within the research area are calculated with the reflected wave method based on the GPR data. …”
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An Iterative Adaptive Polarization Calibration Method Independent of Corner Reflectors by Bowen Chi, Jixian Zhang, Guoman Huang, Lijun Lu, Shucheng Yang

“…Polarimetric calibration (PolCal) is essential for the quantitative processing of polarimetric synthetic aperture radar data. …”
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Modified particle swarm optimization (MPSO) optimized CNN’s hyperparameters for classification by Murinto Murinto, Sri Winiarti

“…This research demonstrates the performance of the MPSO algorithm in optimizing CNN architectures, highlighting its potential for improving image recognition tasks.…”
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