MSM: a scaling-based feature matching algorithm for images with large-scale differences by Qifeng Ge, Xiaoping Du, Chen Xu, Jianhao Xu, Zhenzhen Yan, Xiangtao Fan

“…This algorithm extract feature points across multiple scales, identifying them as scale-invariant keypoints. …”
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An Improved Diffusion Based Placement Algorithm for Reducing Interconnect Demand in Congested Regions of FPGAs by Ali Asghar, Husain Parvez

“…Our placer attempts to minimize the routing congestion by evenly disseminating the interconnect demand across an FPGA chip. For the 20 MCNC benchmark circuits, our algorithm reduced the channel width for 15 circuits. …”
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Low-Light Image Enhancement Algorithm Integrating Retinex Illumination Estimation and Multi-Attention by Yaping Jiang, Shixian Guo

“…Comprehensive quantitative and qualitative evaluations across seven benchmark datasets validate the proposed algorithm effectively removes artifacts, significantly improves image quality, and enhances visual perception.…”
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ECT Image Reconstruction Algorithm Based on Multiscale Dual-Channel Convolutional Neural Network by Lili Wang, Xiao Liu, Deyun Chen, Hailu Yang, Chengdong Wang

“…Feature unions are used across the scales to fuse the information of the output layer with feature maps. …”
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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…Therefore, we propose MTEPN as an innovative deep convolutional neural network algorithm specifically designed to perform multiple visual tasks concurrently. …”
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A Multi-Scale Feature Extraction Algorithm for Chinese Herbal Medicine Image Classification by Wenbin Dai, Yuxin Ma, Yan Fan, Jun Ma

“…Due to the low quality of existing Chinese herbal medicine datasets and the lack of recognition algorithms for herbal images, automatic classification of Chinese herbal medicine is ineffective. …”
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Big Data and AI Algorithms for Sustainable Development Goals: A Topic Modeling Analysis by Prema Nedungadi, Simi Surendran, Kai-Yu Tang, Raghu Raman

“…The study suggests future research focus on AI transparency, scaling across diverse sectors, and integrating advanced techniques such as neurosymbolic AI and quantum neural networks to enhance system reliability. …”
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MPVF: Multi-Modal 3D Object Detection Algorithm with Pointwise and Voxelwise Fusion by Peicheng Shi, Wenchao Wu, Aixi Yang

“…Finally, evaluation on the KITTI dataset demonstrates a mean Average Precision (mAP) of 69.24%, a 2.75% improvement over GraphAlign++. …”
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Handwritten Words Image Character Extraction Adaptive Algorithm Based on the Multi-branch Structure by GUO Xiaojing, ZHAO Xiaoyuan, ZOU Songlin

“…This study applies a new method of multi-branch convolution, the Re-parameterized and Multi-branch Convolution Algorithm (RMCA), to enhance the recognition of complex structures and similar words, improving mean average precision (MAP) and identification efficiency. …”
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Fractional Impervious Surface Mapping on Multispectral Images With Visible Shadows via a Bundle-Based Sparse Unmixing Model by Yanze Liu, Dacheng Li, Wei Xiong, Qijin Han, Lingling Ma

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Interpretable Multi-Sensor Fusion of Optical and SAR Data for GEDI-Based Canopy Height Mapping in Southeastern North Carolina by Chao Wang, Conghe Song, Todd A. Schroeder, Curtis E. Woodcock, Tamlin M. Pavelsky, Qianqian Han, Fangfang Yao

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Statewide Forest Canopy Cover Mapping of Florida Using Synergistic Integration of Spaceborne LiDAR, SAR, and Optical Imagery by Monique Bohora Schlickmann, Inacio Thomaz Bueno, Denis Valle, William M. Hammond, Susan J. Prichard, Andrew T. Hudak, Carine Klauberg, Mauro Alessandro Karasinski, Kody Melissa Brock, Kleydson Diego Rocha, Jinyi Xia, Rodrigo Vieira Leite, Pedro Higuchi, Ana Carolina da Silva, Gabriel Maximo da Silva, Gina R. Cova, Carlos Alberto Silva

“…To address this, we combined GEDI with Synthetic Aperture Radar (SAR), and optical imagery (Sentinel-1 GRD and Landsat–Sentinel Harmonized (HLS)) data to create a comprehensive canopy cover map for Florida. Using a random forest algorithm, our model achieved an R² of 0.69, RMSD of 0.17, and MD of 0.001, based on out-of-bag samples for internal validation. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

“…Further, activations are used to generate an attention map in the form of Heat Maps which are included as a post-processing step before the classification of the output. …”
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Advancing Particle Tracking: Self-Organizing Map Hyperparameter Study and Long Short-Term Memory-Based Outlier Detection by Max Klein, Niklas Dormagen, Lukas Wimmer, Markus H. Thoma, Mike Schwarz

“…Reliable PTV algorithms are crucial in such scenarios. Previous work has demonstrated that the Self-Organizing Map (SOM) machine learning approach offers superior outcomes on complex-plasma data compared with traditional methods, though its performance is sensitive to hyperparameter calibration, which requires optimization for specific flow scenarios. …”
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MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction by R. Ramani, S. Edwin Raja, D. Dhinakaran, S. Jagan, G. Prabaharan

“…The proposed AKW-MRPK framework achieves up to 92 % accuracy, reduces computational time to as low as 0.875 ms for 25 patients, and demonstrates superior speedup efficiency with a value of 1.9 ms using two computational nodes, consistently outperforming supervised machine learning algorithms and Hadoop-based clusters across these critical metrics. • The AKW-MRPK method selects attributes and accelerates computations for predictions. • Parallelizing polynomial kernels improves accuracy and speed in healthcare data analysis.…”
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FastSLAM-MO-PSO: A Robust Method for Simultaneous Localization and Mapping in Mobile Robots Navigating Unknown Environments by Xu Bian, Wanqiu Zhao, Ling Tang, Hong Zhao, Xuesong Mei

“…This strategic fusion of MO-PSO with FastSLAM not only circumvents the pitfalls of particle degeneration, but also enhances the overall robustness and precision of the SLAM process across a spectrum of operational environments. Our empirical evaluation involves testing the proposed method on three distinct simulation benchmarks, comparing its performance against four other algorithms. …”
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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…The methodology involves two experiments: the first uses free prompting with random street-view images, employing Grounding Dino and SAM algorithms to assess performance across categories. …”
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Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach by Mar Roca, Chengfa Benjamin Lee, Avi Putri Pertiwi, Alina Blume, Isabel Caballero, Gabriel Navarro, Dimosthenis Traganos

“…Our methodology highlights the key role of using a large image archive to generate the multi-temporal optical composite and an optimized bathymetry dataset to better map and account blue carbon in seagrass ecosystems across depth, showing the importance to integrate this Earth Observation approach to ensure a seagrass ecosystem monitoring at regional scales. …”
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Mapping Nationwide Subfield Division Dynamics in Saudi Arabia Using Temporal Patterns of Sentinel-2 NDVI and Machine Learning by Ting Li, Oliver Miguel Lopez Valencia, Matthew F. McCabe

“…These parameters were applied to map the nationwide center-pivot subfield division dynamics across Saudi Arabia from 2019 to 2023. …”
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Urban Tree Canopy Mapping and Analysis Using Iterative Annotation Method and Deep Learning: A Case Study in Beijing by Yulong Ding, Ximin Cui, Zhengchao Chen, Zeqing Wang, Debao Yuan, Xiang Meng, Xuan Yang, Yue Xu, Xiangyu Tian

“…To comprehensively analyze the tree canopy characteristics of urban trees across large areas, this study selects Beijing as the research area, and employs high-resolution remote sensing imagery with deep learning techniques to construct the UTC map of Beijing. …”
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