Research on image generation technology based on deep learning by Li Jinchen

“…Based on the above problems, this paper analyzes the methods of improving and optimizing the mainstream image generation algorithm from the perspectives of improving and optimizing the loss function, improving the space modeling, revising the structure of both the generator and discriminator, while speeding up the training process. …”
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External archive guided radial-grid multi objective differential evolution by Vikas Palakonda, Samira Ghorbanpour, Jae-Mo Kang, Heechul Jung

“…Abstract Differential evolution (DE) is a robust evolutionary algorithm for solving single-objective and multi-objective optimization problems (MOPs). …”
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A comparative study of ultra-massive MIMO intelligent receivers with adversarial robustness and energy efficiency for 6G applications by Pushkar Nidagundi, Advesh Darvekar, Malik Amber, Ramesh R

“…The Taguchi method yields up to 40 % improvement in energy efficiency while maintaining near-perfect BER. Practical implications of massive power consumption, system complexity, and execution time are discussed, alongside a comparative analysis with recent neural network and genetic algorithm optimizations. …”
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DeepLabV3+-Based Semantic Annotation Refinement for SLAM in Indoor Environments by Shuangfeng Wei, Hongrui Tang, Changchang Liu, Tong Yang, Xiaohang Zhou, Sisi Zlatanova, Junlin Fan, Liping Tu, Yaqin Mao

“…The proposed method utilizes MobileNetV3 as the backbone network for DeepLabV3+ to maintain segmentation accuracy while reducing computational demands. In this paper, we introduce a parameter-adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm incorporating K-nearest neighbors and accelerated by KD-tree structures, effectively addressing the limitations of manual parameter tuning and erroneous annotations in conventional methods. …”
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Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays by Sina Hasibi Taheri, Javad Mohammadpour, Ali Lalbakhsh, Slawomir Koziel, Stanislaw Szczepanski

“…Optimal WAIM parameters are efficiently determined using a genetic algorithm (GA). …”
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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

“…XGBoost optimizes decision tree ensembles and provides class probabilities, while the ANN processes numerical data to learn deeper representations. …”
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Thoracoabdominal stab wounds: modern surgical tactics by B. N. Kotiv, I. M. Samokhvalov, V. Ju. Markevich, I. I. Dzidzava, O. V. Barinov, V. V. Suvorov, A. V. Goncharov, K. V. Petukhov

“…The objective was to determine the optimal therapeutic and diagnostic algorithm for thoracoabdominal injury.Material and methods. …”
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Beamforming Design for Dual-functional Radar-communication Systems with Holographic Metasurface Antennas by Guangyi CHEN, Ruoyu ZHANG, Hong REN, Yue MA, Chen MIAO, Wen WU

“…To tackle this nonconvex optimization challenge, we propose an alternating optimization algorithm based on fractional programming. …”
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Long‐Term Trend and Seasonal Cycles of Gap‐Free Downscaled Diurnal/Nocturnal LST and the Interaction to Functional Plant Trait Under Tropical Monsoon Climate by Pham Viet Hoa, Nguyen An Binh, Giang Thi Phuong Thao, Nguyen Ngoc An, Pham The Trinh, Nguyen Quang Tuan, Nguyen Cao Hanh

“…Abstract Land surface temperature (LST) monitoring via Earth observation constellation will become optimized and consistent with spatiotemporal‐explicit characteristics. …”
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Targeted molecular generation with latent reinforcement learning by Ragy Haddad, Eleni E. Litsa, Zhen Liu, Xin Yu, Daniel Burkhardt, Govinda Bhisetti

“…We additionally show how our method can generate molecules that contain a pre-specified substructure while simultaneously optimizing for molecular properties, a task highly relevant to real drug discovery scenarios.…”
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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

“…Experimental results demonstrate that the optimized deep learning algorithm excels in precision (96.4%), recall (96.2%), and mAP50 (98.3), significantly outperforming other mainstream models. …”
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Aplikasi belajar tajwid menggunakan binary search by Anita Andriani, Arbiati Faizah, Indana Lazulfa, Istiqomah Istiqomah

“…Therefore, the aim of this study is to construct tajweed learning application based on website and applied binary search algorithm for better result. Binary search is a search algorithm that works by finding the position of elements in a sorted array and comparing their values. …”
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Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT. by Haoran Zhang, Jinlong Liu, Danyang Su, Zhen Bai, Yan Wu, Yuanbo Ma, Qiuju Miao, Mingyue Wang, Xiaopeng Yang

“…Among all models used for diagnosing fatty liver, the 2D radiomics model based on the random forest algorithm achieved the highest AUC (0.973), while the 2D radiomics model based on the Bagging decision tree algorithm showed the highest sensitivity (0.873), specificity (0.939), accuracy (0.864), precision (0.880), and F1 score (0.876).…”
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Bio-inspired clustering scheme for Internet of Drones application in industrial wireless sensor network by Farooq Aftab, Ali Khan, Zhongshan Zhang

“…The results indicate that the proposed scheme has improved 60% and 38% with respect to ant colony optimization and grey wolf optimization, respectively, in terms of average cluster building time while average energy consumption has improved 23% and 33% when compared to the ant colony optimization and grey wolf optimization, respectively.…”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. …”
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RIS-Aided Integrated Sensing and Communication Systems: STAR-RIS Versus Passive RIS? by Prajwalita Saikia, Anand Jee, Keshav Singh, Cunhua Pan, Wan-Jen Huang, Theodoros A. Tsiftsis

“…The proposed algorithm is also shown to be effective in delivering nearly optimal design outcomes in scenario where the channel state information is imperfect (ICSI). …”
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Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment under Emergency Conditions by Guangcan Xu, Qiguang Lyu

“…Meanwhile, usage of distribution trucks is optimized in the distribution network, that is, usage of single- and double-compartment trucks is reduced while that of three-compartment trucks is increased. …”
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A Set-Based Method for Planning Coordinated Trajectories for Skid-Steered Robotic Units Subject to Constraints, Uncertainties, and External Disturbances by Valerio Scordamaglia, Alessia Ferraro

“…The proposed solution aims to define optimal trajectories that can be simultaneously tracked by the robots while ensuring collision-free motion, even in the presence of unavoidable tracking errors due to the limited authority of the control algorithm. …”
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Performance of a new stabilized structure-preserving finite element method for the Allen–Cahn equation by Panason Manorot, Ben Wongsaijai, Kanyuta Poochinapan

“…The scheme combines the Crank–Nicolson/Adams–Bashforth technique with the Galerkin method, complementing a thoughtfully designed stabilization term. While the Allen–Cahn equation is inherently nonlinear, our proposed algorithm effectively addresses this nonlinearity by utilizing the implicit nature of the resulting system of equations. …”
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