Enhancing Yield Estimation and Field Zoning Accuracy in Precision Agriculture Using Solar-Powered Drone-Based Remote Sensing by Abbas Haider Mohammed, Obaid Mohammed Kadhim, Vittalaiah A.

“…The system processes this data using advanced machine learning algorithms to forecast crop yields and generate detailed field zoning maps, enabling optimized resource allocation and improved farm management. …”
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Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI by Tassilo Wald, Benjamin Hamm, Julius C. Holzschuh, Rami El Shafie, Andreas Kudak, Balint Kovacs, Irada Pflüger, Bastian von Nettelbladt, Constantin Ulrich, Michael Anton Baumgartner, Philipp Vollmuth, Jürgen Debus, Klaus H. Maier-Hein, Thomas Welzel

“…Leveraging cross-technique ground truth annotations during training improved the accuracy of DL models in detecting and segmenting BMs. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Conclusion MRI-based radiomic signatures have the potential to serve as biomarkers for PD-RBD. The random forest model, which integrates radiomic signatures with postural instability, and shows improved performance in identifying PD-RBD. …”
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Design and Prototype Verification of a 3-meter Aperture Wrap-rib Reflector by ZHANG Han, YAN Zhongxi, XIANG Ping, WU Minger

“…The shape of the lenticular tube wrap-rib was optimized by combining the form-finding analysis of the flexible reflector with the genetic algorithm. …”
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Image dehazing based on double branch convolution and detail enhancement by ZHAI Fengwen, ZHU Yutong, JIN Jing

“…The quantitative objective analysis and comparison show that the peak signal-to-noise ratio and the structural similarity index reach 39.69 dB and 0.994 respectively, indicating that there is a certain improvement compared with the optimal algorithm in the comparison network model. …”
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Deep Learning-Driven Throughput Maximization in Covert Communication for UAV-RIS Cognitive Systems by Van Nhan Vo, Nguyen Quoc Long, Viet-Hung Dang, Tu Dac Ho, Hung Tran, Symeon Chatzinotas, Dinh-Hieu Tran, Surasak Sanguanpong, Chakchai So-In

“…A deep neural network model is subsequently trained to discover the relationships between the environmental parameters and optimized parameters to enable rapid adaptation to environmental conditions.…”
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Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data by S. R. Mani Sekhar, D. M. Mushtaq Ahmed, G. M. Siddesh

“…It contributes to the growing field of Smart Cities by introducing a scalable and adaptable framework that harnesses the power of deep learning to improve urban living. The result shows that the proposed air pollution model predicted 96.06700 PM2.5 concentration levels, subsequently the temperature model predicted 14.06800∘C. …”
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An artificial neural network approach to comparative aspects: A predictive analysis of magnetic dipole on the heat transfer of maxwell hybrid nano coolants flow in an inclined cyli... by J. Aruna, H. Niranjan

“…Numerical data consisting of 110 points is obtained via bvp4c and implemented in the ANN model, where the training, validation, and testing are 70 %, 15 %, and 15 % respectively as the input data. …”
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Hybrid feature selection for real-time road surface classification on low-end hardware: A machine learning approach by Cong Ngo Van, Duc-Nghia Tran, Ton That Long, Nguyen Gia Minh Thao, Duc-Tan Tran

“…The proposed feature selection approach significantly improves model efficiency and execution speed while maintaining high accuracy. …”
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Activity cliff-aware reinforcement learning for de novo drug design by Xiuyuan Hu, Guoqing Liu, Yang Zhao, Hao Zhang

“…This RL framework is designed to focus model optimization on high-impact regions within the SAR landscape, improving the generation of molecules with targeted properties. …”
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The Application of the Gestalt Theory in Music Psychotherapy for Piano by Fukun Cai

“…Compared with the classification accuracies of DBN, restricted Boltzmann machine (RBM), and K nearest neighbor (kNN) algorithms in mixed music environments, the classification effects were improved by about 3.49%, 12.89%, and 7.24%. …”
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Enhanced Position-Aided Beam Prediction Using Real-World Data and Enhanced-Convolutional Neural Networks by Ahmed Abd El Moaty Mohamed Gouda, Ehab K. I. Hamad, Aziza I. Hussein, M. Mourad Mabrook, A. A. Donkol

“…The proposed E-CNN model has been investigated across nine different scenarios from the DeepSense 6G dataset and compared against the conventional algorithms. …”
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Joint Resource Scheduling of the Time Slot, Power, and Main Lobe Direction in Directional UAV Ad Hoc Networks: A Multi-Agent Deep Reinforcement Learning Approach by Shijie Liang, Haitao Zhao, Li Zhou, Zhe Wang, Kuo Cao, Junfang Wang

“…The algorithm with the main lobe direction scheduling improves performance by 67.06% compared to the algorithm without the main lobe direction scheduling.…”
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Implications of machine learning techniques for prediction of motor health disorders in Saudi Arabia by Ehab M. Almetwally, I. Elbatal, Mohammed Elgarhy, Amr R. Kamel

“…The RF technique achieves the largest area under the curve, and the RF technique is the most effective of all ML algorithms, according to the results of the applied ML algorithms. …”
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Deep learning-driven approach for cataract management: towards precise identification and predictive analytics by Shuaixin Lu, Lingling Ba, Jie Wang, Min Zhou, Peiyao Huang, Xiaohua Zhang, Simo Pan, Xinmiao Zhou, Kai Wen, Jing Sun

“…In the future, it is necessary to improve the generalization ability of model through multimodal data fusion, federated learning and other technologies, and combine interpretable design (such as Grad-CAM) to promote the evolution of DL to a transparent medical decision-making tool, and finally realize the intelligence and universality of cataract management.…”
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Development of intelligent tools to predict neuroblastoma risk stratification and overall prognosis based on multiphase enhanced CT and clinical features by Wei Zhao, Yahui Han, Xiaokun Yu, Jianing Liu, Jiao Zhang, Juan Li

“…The aim of this study was to develop a deep learning model based on multiphase enhanced CT images and clinical features to improve the accuracy of risk stratification and prognostic assessment of NB.MethodsMulti-phase enhanced CT images and clinical features from 202 NB patients were collected. …”
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Research and Analysis of Out-of-Tolerance Problem in Mold Processing Based on Intelligence by Juxian Wang

“…According to the numerical simulation results, the reasoning mechanism of an intelligent design system including instance and rule knowledge is designed, and an uncertain knowledge reasoning algorithm based on the reliability factor is proposed to improve the accuracy of mold size and reduce the overtolerance of the mold.…”
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Advancing road maintenance with EfficientDet-based pothole monitoring by Jenefa Archpaul, Taurshia Antony, Kuriakose Bessy Mani, Kumar Edward Naveen Vijaya, Lincy Archpaul

“…Our experimental evaluations demonstrate that the EfficientDet-based model achieves an impressive average precision of 0.90 and a robust recall of 0.92, highlighting its capacity for accurate and swift pothole detection-an essential component for improving road maintenance. …”
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Identifying and Validating an Acidosis-Related Signature Associated with Prognosis and Tumor Immune Infiltration Characteristics in Pancreatic Carcinoma by Pingfei Tang, Weiming Qu, Dajun Wu, Shihua Chen, Minji Liu, Weishun Chen, Qiongjia Ai, Haijuan Tang, Hongbing Zhou

“…The least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish the optimal model. The tumor immune infiltrating pattern was characterized by the single-sample gene set enrichment analysis (ssGSEA) method, and the prediction of immunotherapy responsiveness was conducted using the tumor immune dysfunction and exclusion (TIDE) algorithm. …”
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Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab by Michael Hafner, Franziska Eckardt, Jakob Siedlecki, Benedikt Schworm, Tina R. Herold, Ben Asani, Siegfried G. Priglinger, Johannes B. Schiefelbein

“…Future research should focus on refining AI models to improve predictive accuracy and assessing long-term outcomes to further optimize disease management. …”
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