Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm by Wenliang Zhu, Guanming Qiu

“…Lastly, we utilized a second-order Bezier curve to smoothen the path, eliminating sharp corners and discontinuities, ultimately yielding the optimal path. Across diverse map environments and two distinct dimensional scenarios, we conducted multiple sets of simulation experiments to validate the algorithm’s feasibility. …”
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Underwater Object Detection Algorithm Based on an Improved YOLOv8 by Fubin Zhang, Weiye Cao, Jian Gao, Shubing Liu, Chenyang Li, Kun Song, Hongwei Wang

“…Due to the complexity and diversity of underwater environments, traditional object detection algorithms face challenges in maintaining robustness and detection accuracy when applied underwater. …”
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YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11 by Yue Liao, Lerong Li, Huiqiang Xiao, Feijian Xu, Bochen Shan, Hua Yin

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Network pharmacognosy of Galphimia glauca: Mapping the molecular landscape of a traditional Mexican medicinal plant. by María José Cambero Acosta, Guillermo de Anda-Jáuregui

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Improving National Forest Mapping in Romania Using Machine Learning and Sentinel-2 Multispectral Imagery by Mohamed Islam Keskes, Aya Hamed Mohamed, Stelian Alexandru Borz, Mihai Daniel Niţă

“…A sensitivity analysis across multiple spatial resolutions revealed that the performance of all algorithms varied significantly with changes in resolution, emphasizing the importance of selecting an appropriate scale for accurate forest mapping. …”
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Mapping hierarchical wetland characteristics by optical-SAR integration with collaborative spatial-spectral-temporal learning by Linwei Yue, Meiyue Wang, Chengpeng Huang, Qing Cheng, Qiangqiang Yuan, Huanfeng Shen

“…Inspired by the relationships of deep and shallow features, the intra-layer features are fused across the branches to generate the multi-level wetland mapping results (i.e., general wetland land cover, and wetland vegetation types). …”
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Multi-modal integration of MRI and global chamber charge density mapping for the evaluation of atrial fibrillation by Alexander J. Sharp, Michael T. B. Pope, Andre Briosa e Gala, Richard Varini, Timothy R. Betts, Abhirup Banerjee

“…We apply the CDM inverse algorithm to both sets of reconstructions in order to compare derived conductions across various heart rhythms and AF conduction patterns. …”
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Mapping forest-agroforest frontiers in the Peruvian Amazon with deep learning and PlanetScope satellite data by Wanting Yang, Daniel Ortiz-Gonzalo, Xiaoye Tong, Dimitri Gominski, Rasmus Fensholt

“…Integrating a DEM as an additional helped the generalization of models across different geographical sites but did not improve the overall accuracy, whereas adding temporal information did not improve generalization or accuracy. …”
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Long-Duration UAV Localization Across Day and Night by Fusing Dual-Vision Geo-Registration with Inertial Measurements by Xuehui Xing, Xiaofeng He, Ke Liu, Zhizhong Chen, Guofeng Song, Qikai Hao, Lilian Zhang, Jun Mao

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Preliminary performance analysis using the PPP-RTK service of the National Land and Mapping Center in Taiwan by J.-Y. Lin, C.-H. Chu, F.-Y. Chu, K.-W. Chiang, M.-L. Tsai

“…The experimental equipment includes a tactical-grade Inertial Measurement Unit (IMU) and a low-cost receiver capable of receiving National Land Surveying and Mapping Center (NLSC) correction signals for PPP-RTK functionality. …”
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A Dynamic State Cluster-Based Particle Swarm Optimization Algorithm by Zhenya Diao, Fei Yu, Hongrun Wu, Xuewen Xia

“…Eventually, comparative analysis with 10 advanced existing algorithms on the CEC2017 and CEC2022 benchmark suites demonstrates that DSCPSO achieves competitive performance across over 70% of the functions, validating the algorithm’s effectiveness and superiority. …”
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Improvement of Dung Beetle Optimization Algorithm Application to Robot Path Planning by Kezhen Liu, Yongqiang Dai, Huan Liu

“…Experimental results demonstrate that TSDBO exhibits significant improvements in all aspects compared to other modified algorithms across 12 benchmark tests. Furthermore, we validated the practicality and reliability of TSDBO in robotic path planning applications, where it shortened the shortest path by 5.5–7.2% on a 10 × 10 grid and by 11.9–14.6% on a 20 × 20 grid.…”
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Quantification of MODIS Land Surface Temperature Downscaled by Machine Learning Algorithms by Qi Su, Xiangchen Meng, Lin Sun, Zhongqiang Guo

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Machine Learning-Based Summer Crops Mapping Using Sentinel-1 and Sentinel-2 Images by Saeideh Maleki, Nicolas Baghdadi, Hassan Bazzi, Cassio Fraga Dantas, Dino Ienco, Yasser Nasrallah, Sami Najem

“…Accurate crop type mapping using satellite imagery is crucial for food security, yet accurately distinguishing between crops with similar spectral signatures is challenging. …”
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V-STAR: A Cloud-Based Tool for Satellite Detection and Mapping of Volcanic Thermal Anomalies by Simona Cariello, Arianna Beatrice Malaguti, Claudia Corradino, Ciro Del Negro

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SpaGAN: A spatially-aware generative adversarial network for building generalization in image maps by Zhiyong Zhou, Cheng Fu, Robert Weibel

“…Building generalization is an essential task in generating multi-scale topographic maps. The progress of deep learning offers a new paradigm to overcome the coordination challenges faced by conventional building generalization algorithms. …”
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Mapping Gridded GDP Distribution of China Based on Remote Sensing Data and Machine Learning Methods by Saimiao Liu, Wenliang Liu, Yi Zhou, Shixin Wang, Futao Wang, Zhenqing Wang

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Mapping Mountain Permafrost via GPR-Augmented Machine Learning in the Northeastern Qinghai–Tibet Plateau by Yao Xiao, Guangyue Liu, Guojie Hu, Defu Zou, Ren Li, Erji Du, Tonghua Wu, Xiaodong Wu, Guohui Zhao, Yonghua Zhao, Lin Zhao

“…Accurate permafrost mapping in mountainous regions is hindered by sparse in situ observations and heterogeneous terrain. …”
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EnSCAN: ENsemble Scoring for prioritizing CAusative variaNts across multiplatform GWASs for late-onset alzheimer’s disease by Onur Erdogan, Cem Iyigun, Yeşim Aydın Son

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HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware by Nicolas PD Sawaya, Daniel Marti-Dafcik, Yang Ho, Daniel P Tabor, David E Bernal Neira, Alicia B Magann, Shavindra Premaratne, Pradeep Dubey, Anne Matsuura, Nathan Bishop, Wibe A de Jong, Simon Benjamin, Ojas Parekh, Norm Tubman, Katherine Klymko, Daan Camps

“…The goals of this effort are (a) to save researchers time by eliminating the need to prepare problem instances and map them to qubit representations, (b) to allow for more thorough tests of new algorithms and hardware, and (c) to allow for reproducibility and standardization across research studies.…”
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