Few-shot crop disease recognition using sequence- weighted ensemble model-agnostic meta-learning by Junlong Li, Quan Feng, Junqi Yang, Jianhua Zhang, Jianhua Zhang, Sen Yang

“…While deep learning-based computer vision techniques have emerged as powerful tools for crop disease recognition, these methods are heavily reliant on large datasets, which are often difficult to obtain in practical agricultural settings. …”
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Design of path planning robot simulator by applying sampling based method by Heru Suwoyo, Julpri Andika, Andi Adriansyah

“…The simulator uses sampling-based path planning algorithms such as RRT*, Fast RRT*, RRT*-Smart, informed-RRT*, and Honey Bee Mating Optimization-based Fast-RRT*. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

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Can Knowledge Distillation Enable Seismic Interpolation, Super-Resolution, and Denoising Simultaneously? by Benwen Zhang, Linrong Wang

“…Consequently, SNet inherits TNet’s capabilities and further refines them during optimization. For comparison, we combine three interpolation algorithms with three super-resolution algorithms and select the one with the best performance. …”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…Additionally, a lightweight cross-attention fusion module is introduced, optimizing the use of differential and shared features while minimizing computational complexity. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

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Research on Urban Traffic Signal Control Systems Based on Cyber Physical Systems by Li-li Zhang, Qi Zhao, Li Wang, Ling-yu Zhang

“…With this proposed system, managers and researchers can realize the construction and simulation of various types of traffic scenarios, the rapid development, and optimization of new control strategies and can apply effective control strategies to actual traffic management. …”
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Causal Unit Selection using Tractable Arithmetic Circuits by Haiying Huang, Adnan Darwiche

“…This is done through compiling the meta-model into a special class of tractable arithmetic circuits that allows the computation of optimal units in time linear in the circuit size. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…Nine machine learning algorithms (Logistic Regression LR, Decision Tree DT, Gradient Boosting Machine GBM, K-Nearest Neighbors KNN, LASSO, Principal Component Analysis PCA, Random Forest RF, Support Vector Machine SVM, and XGBoost) were applied to training and testing datasets with 10-fold cross-validation to select three optimized algorithm models. …”
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Image Super Resolution Reconstruction Based on Multi-Level Residual Skip Connection Network by WANG Xiaoyu, LU Jianyu, WEI Yuxin, YU Yue

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Three-Dimensional Guidance Approach with Obstacle Avoidance against Maneuvering Targets by Zi-jie Jiang, Xiu-xia Yang, Yi Zhang, Cong Wang, Hao Yu

“…Finally, to solve the above optimization problems, a hybrid solver is developed based on the adaptive moment estimation (Adam) algorithm, whose output will serve as the real-time guidance command. …”
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Electric Bus Charging Schedules Relying on Real Data-Driven Targets Based on Hierarchical Deep Reinforcement Learning by Jiaju Qi, Lei Lei, Thorsteinn Jonsson, Lajos Hanzo

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Emerging generalization advantage of quantum-inspired machine learning in the diagnosis of hepatocellular carcinoma by Domenico Pomarico, Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, Antonio Lacalamita, Marianna La Rocca, Tommaso Maggipinto, Ester Pantaleo, Sabina Tangaro, Sebastiano Stramaglia, Roberto Bellotti

“…By using previously characterized genetic communities, we minimize the computational complexity associated with the number of qubits, enabling the execution of quantum-inspired algorithms on classical machines. …”
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Quick eVALUATION OF THE INTERVAL STABILITY OF THE LINEAR ASSIGNMENT problem SOLUTIONS by M. P. Revotjuk, M. K. Qaraleh, P. M. Batura

“…An efficient algorithm for evaluating the interval of solutions stability of opened and closed linear assignment problems based on a review of the results of optimization iterations is proposed. …”
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Faster quantum subroutine for matrix chain multiplication via Chebyshev approximation by Xinying Li, Pei-Lin Zheng, Chengkang Pan, Fei Wang, Chunfeng Cui, Xian Lu

“…The algorithm can be applied to any complex matrix. Furthermore, we discuss integrating our QMM algorithm as a subroutine in other matrix operations and propose strategies to optimize QMM for matrices with large condition numbers with numerical simulation.…”
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Transient Attracting Profiles in the Great Pacific Garbage Patch by L. Kunz, A. Griesel, C. Eden, R. Duran, R. Duran, B. Sainte-Rose

“…TRAPs are the attracting form of hyperbolic Objective Eulerian Coherent Structures and are computable from the instantaneous strain field on the ocean surface. …”
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Real time obstacle motion prediction using neural network based extended Kalman filter for robot path planning by Najva Hassan, Abdul Saleem P.K

“…In terms of computation time and robustness in closely spaced obstacles, simulation experiments demonstrated that the path planning using the proposed algorithm outperforms the hybrid A star, artificial potential field, and decision algorithms. …”
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Learning from Octopuses: Cutting-Edge Developments and Future Directions by Jinjie Duan, Yuning Lei, Jie Fang, Qi Qi, Zhiming Zhan, Yuxiang Wu

“…These studies mainly explore how humans can learn from the physiological characteristics of octopuses for sensor design, actuator development, processor architecture optimization, and intelligent optimization algorithms. …”
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NRNH-AR: A Small Robotic Agent Using Tri-Fold Learning for Navigation and Obstacle Avoidance by Carlos Vasquez-Jalpa, Mariko Nakano, Martin Velasco-Villa, Osvaldo Lopez-Garcia

“…The proposed algorithm was evaluated in four critical aspects: computational cost, learning stability, required memory size, and operation speed. …”
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Enhanced Rapid Autofocus Back-Projection for PBSAR Based on the GEO Satellite by Te Zhao, Jun Wang, Zuhan Cheng, Ziqian Huang, Jiaqi Song

“…Furthermore, we introduce a ground Cartesian back projection algorithm to adapt it to the PBSAR architecture, significantly improving computational efficiency in autofocusing processing. …”
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