An improved deep learning approach for automated detection of multiclass eye diseases by Feudjio Ghislain, Saha Tchinda Beaudelaire, Romain Atangana, Tchiotsop Daniel

“…Conclusion: The integration of biorthogonal wavelet transforms into our CNN model has proven effective, surpassing the performance of several similar algorithms reported in the literature. This advancement not only enhances the accuracy of real-time diagnoses but also supports the development of sophisticated tools for the detection of a wide range of retinal pathologies, thereby improving clinical decision-making processes.…”
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AIpollen: An Analytic Website for Pollen Identification Through Convolutional Neural Networks by Xingchen Yu, Jiawen Zhao, Zhenxiu Xu, Junrong Wei, Qi Wang, Feng Shen, Xiaozeng Yang, Zhonglong Guo

“…For the optimization algorithm, we opted for the Adam optimizer and utilized the cross-entropy loss function. …”
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A Quantitative Evaluation of UAV Flight Parameters for SfM-Based 3D Reconstruction of Buildings by Inho Jo, Yunku Lee, Namhyuk Ham, Juhyung Kim, Jae-Jun Kim

“…Under controlled environmental conditions on representative building structures, key variables were manipulated, and all collected data were processed through a consistent SfM pipeline based on the SIFT algorithm. …”
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Depth-Supervised and Curvature-Optimized 3D Gaussian Splatting for Scene Reconstruction by Antong Li, Lutao Wang, Ziwei Wang

“…The Adaptive Density Control (ADC) algorithm plays a pivotal role in 3DGS, utilizing an image gradient-based average gradient threshold to regulate the splitting and cloning of Gaussians and optimize the density of Gaussian distributions. …”
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Semi-Supervised Approach for Automatic Counting of Whiteflies With Small Annotated Dataset by Laura Gomez-Zamanillo, Arantza Bereciartua-Perez, Andoni Elola, Artzai Picon, Aitor Alvarez-Gila, Itziar Egusquiza, Ramon Navarra-Mestre

“…Our new semi-supervised approach using only 48 manually annotated images achieves similar results as the fully supervised approach trained with 474 manually annotated images.…”
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Identification of neural outgrowth genes using genome-wide RNAi. by Katharine J Sepp, Pengyu Hong, Sofia B Lizarraga, Judy S Liu, Luis A Mejia, Christopher A Walsh, Norbert Perrimon

“…The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. …”
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Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function by Imran Uddin, Dzati A. Ramli, Abdullah Khan, Javed Iqbal Bangash, Nosheen Fayyaz, Asfandyar Khan, Mahwish Kundi

“…To achieve this objective, a dataset of 43000 images was created. Three Feed Forward Neural Network models with backpropagation algorithm using different Rectified Linear Unit (ReLU) layer configurations (Model 1 with 1-ReLU Layer, Model 2 with 2-ReLU layers, and Model 3 with 3-ReLU Layers) were trained and tested with this dataset. …”
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BedEye: A Bed Exit and Bedside Fall Warning System Based on Skeleton Recognition Technology for Elderly Patients by Liang-Bi Chen, Wan-Jung Chang, Tzu-Chin Yang

“…The proposed BedEye system processes real-time images captured by an RGB sensor, which are then fed into a deep learning model running locally on an Nvidia Jetson Xavier-NX edge computing device. …”
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DualTransAttNet: A Hybrid Model with a Dual Attention Mechanism for Corn Seed Classification by Fei Pan, Dawei He, Pengjun Xiang, Mengdie Hu, Daizhuang Yang, Fang Huang, Changmeng Peng

“…Varietal purity is a critical quality indicator for seeds, yet various production processes can lead to the mixing of seeds from different varieties. …”
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Single camera 6-dof object tracking using spatial resection based techniques by M. Davoudkhani, C. Mulsow, H.-G. Maas

“…Photogrammetric methods and advanced algorithms are widely used for tracking objects in camera image sequences in various sectors, such as motion analysis, industrial inspection, monitoring of environmental processes, or analyzing impact events or explosions. …”
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Towards Accurate Photogrammetry Using Molded Markers by Iñigo Auzmendi Iriarte, Oier Saez de Egilaz, Pedro Gonzalez de Alaiza Martinez, Imanol Herrera

“…A two-stage detection algorithm is developed to accurately identify their centers: initial approximate detection by a Faster R-CNN model, followed by accurate localization using a classical cross center detection algorithm. …”
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FRESH: Fusion-Based 3D Apple Recognition via Estimating Stem Direction Heading by Geonhwa Son, Seunghyeon Lee, Yukyung Choi

“…Furthermore, we effectively fused 3D point clouds with 2D images to leverage the geometric data from point clouds and the semantic information from images, enhancing the apple detection performance. …”
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Quantifying Spatiotemporal Changes in Supraglacial Debris Cover in Eastern Pamir from 1994 to 2024 Based on the Google Earth Engine by Hehe Liu, Zhen Zhang, Shiyin Liu, Fuming Xie, Jing Ding, Guolong Li, Haoran Su

“…To address this research gap, this study employed Landsat remote sensing images within the Google Earth Engine platform, leveraging the Random Forest algorithm to classify the supraglacial debris cover. …”
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A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models by Hamidreza Najafi, Kimia Savoji, Marzieh Mirzaeibonehkhater, Seyed Vahid Moravvej, Roohallah Alizadehsani, Siamak Pedrammehr

“…Methods: To address these hurdles, this paper presents an innovative three-step approach that leverages Generative Adversarial Networks (GAN), Long Short-Term Memory (LSTM), and VGG16 algorithms for the accurate reconstruction of three-dimensional (3D) lung tumor images. …”
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Application of graph theory in liver research: A review by Xumei Hu, Longyu Sun, Rencheng Zheng, Xueqin Xia, Meng Liu, Weibo Chen, Xinyu Zhang, Chengyan Wang

“…By representing images as graphs, it is possible to analyze and process them with graph‐based algorithms, handling complex relationships among pixels and making them useful in boundary extraction and texture analysis. …”
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Deep Learning-Based Pulmonary Nodule Screening: A Narrative Review by Abhishek Mahajan, Ujjwal Agarwal, Rajat Agrawal, Aditi Venkatesh, Shreya Shukla, K S. S. Bharadwaj, M L. V. Apparao, Vivek Pawar, Vivek Poonia

“…Artificial intelligence algorithms have recently demonstrated remarkable progress in medical imaging, especially with deep learning techniques such as convolutional neural networks (CNNs). …”
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A Novel THz Differential Spectral Clustering Recognition Method Based on t-SNE by Tie-Jun Li, Chih-Cheng Chen, Jian-jun Liu, Gui-fang Shao, Christopher Chun Ki Chan

“…Comparative experiments indicate that our model can judge the existence of sample defect features or not through spectrum clustering, as a predetection process for image analysis.…”
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Real time counting method for coal mine drill pipes based on deep learning by Fukai ZHANG, Yiran SUN, Xufeng WU, Aijun LI, Peiyang LI, Dengke WANG, Guan YUAN, Shan ZHAO, Haiyan ZHANG

“…Experiments on the CMDPC dataset show that the improved Drill-YOLOv8 model performs well in mAP@0.5 The mAP @ [0.5:0.95] index has increased by 3.0% and 2.7% respectively, effectively solving the problem of false detection and missed detection of drilling head and drill pipe targets under strong light, water vapor, and occlusion environments, and the detection speed has reached 86 frames per second; At the same time, the weighted average error rate of the counting inference algorithm Pipe Count is 2%, showing good robustness against multi scene data, and the processing speed reaches 40 frames per second, meeting real-time counting requirements.…”
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A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications by Gege Ding, Jiayue Liu, Dongsheng Li, Xiaming Fu, Yucheng Zhou, Mingrui Zhang, Wantong Li, Yanjuan Wang, Chunxu Li, Xiongfei Geng

“…The application potential of unmanned aerial vehicles (UAVs) in marine search and rescue is especially of concern for the ongoing advancement of visual recognition technology and image processing technology. Limited computing resources, insufficient pixel representation for small objects in high-altitude images, and challenging visibility conditions hinder UAVs’ target recognition performance in maritime search and rescue operations, highlighting the need for further optimization and enhancement. …”
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Robust Corner Detection Using Local Extrema Differences by Reza Yazdi, Hassan Khotanlou, Hosna Khademfar

“…We conduct a comprehensive evaluation comparing our detector to seven established algorithms using five benchmark images with ground truth corner locations. …”
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