FlexiNet: An Adaptive Feature Synthesis Network for Real-Time Ego Vehicle Speed Estimation by Abdalrahaman Ibrahim, Kyandoghere Kyamakya, Wolfgang Pointner

“…To address these challenges, we propose FlexiNet, a novel adaptive feature synthesis network that leverages monocular camera data to perform real-time speed estimation. …”
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Transmission line fault identification method based on weighted federated learning and multimodal residual network by Jian Wang, Fengkai Lin, Dongliang Nan, Qi Zhao, Han Xue, Jinxin Ouyang

“…Although data-driven deep learning networks can be used for transmission line fault identification, the generalization performance of the algorithm will be seriously reduced in the face of “data islands” and class imbalance among fault samples in various regions. …”
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A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…However, most of these extrapolation network architectures are built upon convolutional neural networks, using radar echo images as input. …”
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Improving Temperature Prediction Precision for Aerial Cameras by Correcting Structure and Parameters of Thermal Network Models by Yue Fan, Wei Feng, Zhenxing Ren, Bingqi Liu, Jinying Li

“…The passive thermal control optimization design of the frame insulation structure and convective heat transfer coefficients ensures that key thermal parameter values are maintained within optimum ranges. Following an analysis of the change trend consistency between the predicted temperatures and the transient thermal experimental data, the thermal network structure is modified to reduce the discrepancy between the thermal network and physical models. …”
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SlowFast-TCN: A Deep Learning Approach for Visual Speech Recognition by Nicole Yah Yie Ha, Lee-Yeng Ong, Meng-Chew Leow

“…To address this challenge, viseme classification must not only extract lip image spatial features, but also to handle visemes of varying durations and temporal features. …”
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Study for Predicting Land Surface Temperature (LST) Using Landsat Data: A Comparison of Four Algorithms by Elhadi K. Mustafa, Yungang Co, Guoxiang Liu, Mosbeh R. Kaloop, Ashraf A. Beshr, Fawzi Zarzoura, Mohammed Sadek

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Flooded and Irrigation Area Monitoring After the Kakhovka Dam Disaster Based on Machine Learning and Satellite Data by Bohdan Yailymov, Hanna Yailymova, Andrii Kolotii, Andrii Shelestov, Sergii Skakun, Sheila Baber, Inbal Becker-Reshef, Nataliia Kussul

“…Maps of water bodies were generated before and after the flood using Sentinel-1, Sentinel-2, and Landsat-9 images. The random forest classifier was used for flooded area mapping, while the multilayer perceptron and the U-shaped network classifier were used for irrigated land identification. …”
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Graph-Based 3-Dimensional Spatial Gene Neighborhood Networks of Single Cells in Gels and Tissues by Zhou Fang, Kelsey Krusen, Hannah Priest, Mingshuang Wang, Sungwoong Kim, Anirudh Sriram, Ashritha Yellanki, Ankur Singh, Edwin Horwitz, Ahmet F. Coskun

“…Impact Statement: The pipeline combines 3D imaging-based spatial transcriptomics and graph-based deep learning to identify subcellular motifs. …”
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High-quality control of receiver functions using a capsule neural networkKey points by Mona H. Hegazi, Ahmad M. Faried, Omar M. Saad

“…The automated selection of RFs using a capsule neural network has the potential to significantly improve the efficiency and accuracy of RF analysis, as demonstrated by the stacking test. …”
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CNN-based Gender Prediction in Uncontrolled Environments by Kazım Yıldız, Engin Güneş, Anil Bas

“…The model created with this algorithm was trained with facial images and gender prediction was made. As a result of the experiments, 93.71% success rate was achieved on the VGGFace2 data set and 85.52% success rate on the Adience data set. …”
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Deep learning for enhanced prediction of diabetic retinopathy: a comparative study on the diabetes complications data set by Weijun Gong, You Pu, Tiao Ning, Yan Zhu, Gui Mu, Jing Li

“…While existing studies predominantly focus on image-based AI diagnosis, there is a pressing need for accurate risk prediction using structured clinical data. …”
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Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects by Maryam Yeganegi, Mahsa Danaei, Sepideh Azizi, Fatemeh Jayervand, Reza Bahrami, Seyed Alireza Dastgheib, Heewa Rashnavadi, Ali Masoudi, Amirmasoud Shiri, Kazem Aghili, Mahood Noorishadkam, Hossein Neamatzadeh

“…This review explores AI and machine learning (ML) in the early detection, prediction, and assessment of neural tube defects (NTDs) through prenatal ultrasound imaging. Recent studies highlight the effectiveness of AI techniques, such as convolutional neural networks (CNNs) and support vector machines (SVMs), achieving detection accuracy rates of up to 95% across various datasets, including fetal ultrasound images, genetic data, and maternal health records. …”
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MRI-based risk factors for intensive care unit admissions in acute neck infections by Jari-Pekka Vierula, Harri Merisaari, Jaakko Heikkinen, Tatu Happonen, Aapo Sirén, Jarno Velhonoja, Heikki Irjala, Tero Soukka, Kimmo Mattila, Mikko Nyman, Janne Nurminen, Jussi Hirvonen

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Blockchain Enabled Secure Medical Data Transmission and Diagnosis Using Golden Jackal Optimization Algorithm with Deep Learning by Kiruthikadevi Kulandaivelu, Sivaraj Rajappan, Vijayakumar Murugasamy

“…The empirical analysis of the proposed BGJOA-DLSMTD algorithm has been demonstrated by means of standard medical images and the outcomes underlined the superior achievement of the BGJOA-DLSMTD algorithm.…”
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Development of Navigation Network Models for Indoor Path Planning Using 3D Semantic Point Clouds by Jiwei Hou, Patrick Hübner, Dorota Iwaszczuk

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Cropping Pattern Classification Using Artificial Neural Networks and Evapotranspiration Estimation in the Eastern Mediterranean Region of Turkey by Mahmut Çetin, Muhammet Said Golpinar, Mehmet Ali Akgül, Hakan Aksu, Omar Alsenjar

“…Crop types were classified using the ANN algorithm in the Environment for Visualizing Images (ENVI) program based on combined data from Sentinel-2 images with a 10-m resolution and ground truth data collected during the winter and summer seasons. …”
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PassAI: An Explainable Machine Learning Framework for Predicting Soccer Pass Outcomes Using Multimodal Match Data by Ryota Takamido, Jun Ota, Hiroki Nakamoto

“…As sports data, increasingly shaped by recent advances in in-game data acquisition technologies, become more complex and high-dimensional, analyzing such multimodal datasets presents challenges in both predictive performance and interpretability. …”
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Artificial Vision Systems for Mobility Impairment Detection: Integrating Synthetic Data, Ethical Considerations, and Real-World Applications by Santiago Felipe Luna-Romero, Mauren Abreu de Souza, Luis Serpa Andrade

“…While synthetic data generation helps mitigate dataset limitations, models trained predominantly on simulated images often exhibit reduced performance in uncontrolled environments due to the domain gap. …”
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Predicting the intention to adopt wearable payment devices in China: The use of hybrid SEM-Neural network approach. by Li Luyao, Abdullah Al Mamun, Naeem Hayat, Qing Yang, Mohammad Enamul Hoque, Noor Raihani Zainol

“…In a two-stage data analysis, partial least squares structural equation modelling (PLS-SEM) were employed to analyse the causal effects and associations between independent and dependent variables, whereas artificial neural networks (ANN) were used to evaluate the research model prediction capability. …”
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A Camera Nodes Correlation Model Based on 3D Sensing in Wireless Multimedia Sensor Networks by Chong Han, Lijuan Sun, Fu Xiao, Jian Guo, Ruchuan Wang

“…Then, to farthest eliminate the data redundancy and use the node collaboration characteristic of wireless (multimedia) sensor networks, two kinds of cluster structure, camera sensor nodes cluster, and common sensor nodes cluster are established to cooperate on image processing and transmission tasks. …”
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