Understanding biological motion through the lens of animate motion processing by Li Shen, Li Shen, Xinlin Yang, Xinlin Yang, Yi Jiang, Yi Jiang, Ying Wang, Ying Wang

“…In this review, we synthesize empirical findings from human and non-human animal studies to reveal how BM enjoys a unique position in visual perception as an animate motion and how it elicits animacy perception. …”
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Generative Artificial Intelligence-Enabled Facility Layout Design Paradigm by Fuwen Hu, Chun Wang, Xuefei Wu

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Examining the Impact of Content Features on Customer Engagement in Social Media: A Data Mining Approach on Instagram by Azade Shekari, Mohammad Mehdi Poursaeed, Saeed Dehyadegari

“…Findings The results of this study indicate the effects of embedded visual and textual content features of published messages on customer engagement behavior. …”
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Scene Graph and Natural Language-Based Semantic Image Retrieval Using Vision Sensor Data by Jaehoon Kim, Byoung Chul Ko

“…Specifically, we utilize a graph neural network (GNN) to learn features of nodes and edges and generate graph embeddings, enabling image retrieval through natural language queries without relying on additional image metadata. …”
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Integrated data-driven topology reconstruction and risk-aware reconfiguration for resilient power distribution systems under incomplete observability by Sipei Sun, Ning Li, Liang Zhang, Dongpo Zhao, Di Lun, Liang Feng

“…Abstract This paper proposes a unified data-driven framework for topology identification, risk quantification, and reconfiguration optimization in power distribution networks under incomplete and fragmented observability. …”
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Autonomous novel class discovery for vision-based recognition in non-interactive environments by Xuelin Zhang, Feng Liu, Xuelian Cheng, Siyuan Yan, Zhibin Liao, Zongyuan Ge

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Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects by Awal Ahmed Fime, Saifuddin Mahmud, Arpita Das, Md. Sunzidul Islam, Jong-Hoon Kim

“…Automatic scene generation is an essential area of research with applications in robotics, recreation, visual representation, training and simulation, education, and more. …”
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MDFT-GAN: A Multi-Domain Feature Transformer GAN for Bearing Fault Diagnosis Under Limited and Imbalanced Data Conditions by Chenxi Guo, Vyacheslav V. Potekhin, Peng Li, Elena A. Kovalchuk, Jing Lian

“…While generative adversarial networks (GANs) have shown promise in data augmentation, their efficacy deteriorates in the presence of multi-category and structurally complex fault distributions. …”
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Transformers for Vision: A Survey on Innovative Methods for Computer Vision by Balamurugan Palanisamy, Vikas Hassija, Arpita Chatterjee, Arpita Mandal, Debanshi Chakraborty, Amit Pandey, G. S. S. Chalapathi, Dhruv Kumar

“…We delve into the theoretical adaptations required to apply transformers to visual data, including image tokenization and the integration of positional embeddings. …”
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Evaluation of the precision and accuracy in the classification of breast histopathology images using the MobileNetV3 model by Kenneth DeVoe, Gary Takahashi, Ebrahim Tarshizi, Allan Sacker

“…Using transfer learning to take advantage of ImageNet embeddings without special feature extraction, we were able to correctly classify histopathology images broadly as benign or malignant with 0.98 precision, 0.97 recall, and an F1 score of 0.98. …”
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Analysis of argument structure constructions in a deep recurrent language model by Pegah Ramezani, Pegah Ramezani, Achim Schilling, Achim Schilling, Patrick Krauss, Patrick Krauss

“…We then analyzed the internal hidden layer activations using Multidimensional Scaling (MDS) and t-Distributed Stochastic Neighbor Embedding (t-SNE) to visualize sentence representations. …”
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Kohonen’s algorithm in problems of classification of defects in printed circuit assemblies by S. U. Uvaysov, V. V. Chernoverskaya, An Kuan Dao, Van Tuan Nguyen

“…The results of the study showed that the network automatically classifies the characteristic defects of electronic components using the algorithms embedded in it. …”
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Integrated deep learning framework for driver distraction detection and real-time road object recognition in advanced driver assistance systems by Rakesh Salakapuri, Naveen Kumar Navuri, Thrimurthulu Vobbilineni, G. Ravi, Karthik Karmakonda, K. Asish vardhan

“…The behaviour of a driver is categorized into physical and visual distraction and cognitive distraction using Convolutional Neural Networks (CNN’s) and transfer learning in order to achieve greater accuracy while also consuming lesser computational resources. …”
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An improved reversible image watermarking algorithm based on difference expansion by Zhengwei Zhang, Lifa Wu, Yunyang Yan, Shaozhang Xiao, He Sun

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Privacy-preserved data hiding using compressive sensing and fuzzy C-means clustering by Ming Li, Lanlan Wang, Haiju Fan

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A novel two-dimensional reversible data hiding scheme based on high-efficiency histogram shifting for JPEG images by Ben He, Yi Chen, Yonghui Zhou, Yongrong Wang, Yanli Chen

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Target Recognition Method Based on Graph Structure Perception of Invariant Features for SAR Images by Jingyi CAO, Yang ZHANG, Ya’nan YOU, Yamin WANG, Feng YANG, Weijia REN, Jun LIU

“…The t-Distributed Stochastic Neighbor Embedding (t-SNE) method is used to qualitatively evaluate the algorithm’s classification ability, while metrics like accuracy, recall, and F1 score are used to quantitatively analyze key units and overall network performance. …”
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Machine Learning-Based Harvest Date Detection and Prediction Using SAR Data for the Vojvodina Region (Serbia) by Gordan Mimić, Amit Kumar Mishra, Miljana Marković, Branislav Živaljević, Dejan Pavlović, Oskar Marko

“…Clustering of harvested and unharvested fields was performed with Principal Component Analysis, multidimensional scaling and t-distributed Stochastic Neighbour Embedding, for initial cluster visualization. It is shown that the separability of unharvested and harvested data in two-dimensional space does not depend on the selected method but more on the crop itself. …”
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Potential of diagnostic electron microscopy of calcification, pathological neovascularization and elastolysis in combination with phenotyping of cell populations in large arteries by R. A. Mukhamadiyarov, K. Yu. Klyshnikov, V. A. Koshelev, A. G. Kutikhin

“…Whole specimens were subjected to chemical fixation, staining with heavy metal salts, embedding in epoxy resin followed by layer-by-layer grinding, polishing, contrasting, visualization using back-scattered electron scanning electron microscopy and three-dimensional reconstruction with color mapping (modified EM-BSEM).Results. …”
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Exploring the chemical space of ionic liquids for CO2 dissolution through generative machine learning models by Xiuxian Chen, Guzhong Chen, Kunchi Xie, Jie Cheng, Jiahui Chen, Zhen Song, Zhiwen Qi

“…The re-balanced VAE transforms the chemical space of ILs into continuous latent space, which is demonstrated by t-distributed stochastic neighbor embedding (t-SNE) visualization and sampled ions of the latent space. …”
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