A visual-assisted relocalization add-on for autonomous robots by Yao Cheng, Fengyang Jiang, Zhe Han, Huaizhen Wang, Fengyu Zhou

“…Extensive experiments across diverse environments confirm the performance superiority of the proposed strategy, demonstrating its practical value for real-world applications.…”
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Lightweight UAV Detection Method Based on IASL-YOLO by Huaiyu Yang, Bo Liang, Song Feng, Ji Jiang, Ao Fang, Chunyun Li

“…Finally, we employ the LAMP pruning algorithm to compress the model. Experimental results on the Anti-UAV dataset show that the improved model achieves a 2.9% increase in Precision, a 6.8% increase in Recall, and 3.9% and 3.8% improvements in mAP50 and mAP50-95, respectively. …”
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SR-DETR: Target Detection in Maritime Rescue from UAV Imagery by Yuling Liu, Yan Wei

“…This study proposes an enhanced SR-DETR algorithm aimed at improving the detection of individuals who have fallen overboard. …”
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Explainable AI for Spectral Analysis of Electromagnetic Fields by Dimitris Kalatzis, Agapi Ploussi, Ellas Spyratou, Theodor Panagiotakopoulos, Efstathios P. Efstathopoulos, Yiannis Kiouvrekis

“…A comparative evaluation of six machine learning algorithms was conducted: XGBoost, LightGBM, Random Forests, k-Nearest Neighbors, Neural Networks and Decision Trees to assess prediction performance across each frequency band. …”
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BREATHE: A GeoAI-Powered Air Quality Monitoring and Forecasting System for Urban Sustainability by S. D. Adduri, T. Ali

“…BREATHE system features four essential aspects that include (1) real-time AQI checks at 12 locations across the UAE territory (2) predictive models for AQI forecasting through climatic and historical data analyses (3) interactive dashboards with mapping visuals and alert features and (4) AI-powered chatbot assistance along with non-specialist user-friendly accessibility. …”
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Three-Dimensional Unmanned Aerial Vehicle Path Planning in Simulated Rugged Mountainous Terrain Using Improved Enhanced Snake Optimizer (IESO) by Wuke Li, Kongwen Zhang, Qi Xiong, Xiaoxiao Chen

“…Comparative simulation experiments benchmarked IESO against five state-of-the-art biologically inspired optimization algorithms across test functions and path-planning simulated scenarios. …”
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EOD-EMDA: A method for automatically identifying and tracking individual pigs in herds by Wei Li, Hu Yuan, Xianpeng Zhu, Xiaojiang Yang

“…This paper proposes an EOD (Enhanced Object Detection Network) object detection model and an EMDA (Enhanced Matching Strategy and Dynamic ID Allocation Algorithm) tracking algorithm, designed for tracking pigs during online sales from an oblique perspective. …”
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Spatial Estimation of Trophic State for Reservoir Using Ground Monitoring and Remote Sensing Data by Thong Nguyen Hoang, Van Tran Thi

“…In contrast, the Chl-a parameter correlated best with the NIR/RED algorithm. From there, we mapped the spatial distribution of parameters and trophic state according to TSI in the entire Dau Tieng Reservoir based on the spectral values from remote sensing algorithms and regression models. …”
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AI generations: from AI 1.0 to AI 4.0 by Jiahao Wu, Hengxu You, Jing Du

“…This paper traces the historical foundations of AI across roughly 70 years, mapping how changes in technological bottlenecks from algorithmic innovation to high-performance computing to specialized data have stimulated each generational leap. …”
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Coal-rock interface real-time recognition based on the improved YOLO detection and bilateral segmentation network by Shuzhan Xu, Wanming Jiang, Quansheng Liu, Hongsheng Wang, Jun Zhang, Jinlong Li, Xing Huang, Yin Bo

“…The comparison with three other models demonstrates the superior edge inference performance of the proposed model, achieving a mean Average Precision (mAP) of 90.2 at the Intersection over Union (IoU) threshold of 0.50 (mAP50) and 81.4 across a range of IoU thresholds from 0.50 to 0.95 (mAP[50,95]). …”
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Versatile Solver of Nonconformal Volume Integral Equation Based on SWG Basis Function by Chunbei Luo, Mingjie Pang, Hai Lin

“…The integral equation is solved by the method of moments (MoM) and further accelerated by the multilevel fast multipole algorithm (MLFMA). What’s more, the hybrid scheme of MLFMA and adaptive cross approximation (ACA) is developed to resolve the low-frequency (LF) breakdown when dealing with over-dense mesh objects. …”
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Hierarchical diagnosis of breast phyllodes tumors enabled by deep learning of ultrasound images: a retrospective multi-center study by Yuqi Yan, Yuanzhen Liu, Yao Wang, Tian Jiang, Jiayu Xie, Yahan Zhou, Xin Liu, Meiying Yan, Qiuqing Zheng, Haifei Xu, Jinxiao Chen, Lin Sui, Chen Chen, RongRong Ru, Kai Wang, Anli Zhao, Shiyan Li, Ying Zhu, Yang Zhang, Vicky Yang Wang, Dong Xu

“…A comparative analysis was conducted between the algorithm’s diagnostic capabilities and those of radiologists with varying clinical experience within an external validation cohort. …”
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Breakage fusion bridge cycles drive high oncogene number with moderate intratumoural heterogeneity by Siavash Raeisi Dehkordi, Ivy Tsz-Lo Wong, Jing Ni, Jens Luebeck, Kaiyuan Zhu, Gino Prasad, Lena Krockenberger, Guanghui Xu, Biswanath Chowdhury, Utkrisht Rajkumar, Ann Caplin, Daniel Muliaditan, Aditi Gnanasekar, Ceyda Coruh, Qiushi Jin, Kristen Turner, Shu Xian Teo, Andy Wing Chun Pang, Ludmil B. Alexandrov, Christelle En Lin Chua, Frank B. Furnari, John Maciejowski, Thomas G. Paulson, Julie A. Law, Howard Y. Chang, Feng Yue, Ramanuj DasGupta, Jean Zhao, Paul S. Mischel, Vineet Bafna

“…Both breakage fusion bridge (BFB) cycles and extrachromosomal DNA (ecDNA) can lead to high oncogene copy numbers, but the impact of BFB amplifications on intratumoral heterogeneity, treatment response, and patient survival remains poorly understood due to detection challenges with DNA sequencing. We introduce an algorithm, OM2BFB, designed to detect and reconstruct BFB amplifications using optical genome mapping (OGM). …”
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Clustering and visualisation of the GABRIEL network expertise in the field of infectious diseases by Philippe Vanhems, Shally Awasthi, Firdausi Qadri, Sayera Banu, Francine Ntoumi, Graciela Russomando, Jianwei Wang, Zakir Hossain, Bourema Kouriba, Sara Eyangoh, Chan Leakhena Phoeung, Cécile Chauvel, Marie-Charlotte Quemin, Marianne Abifadel, Silvia Figueiredo Costa, Monzer Hamze, Daniel Mukadi-Bamuleka, Abdoul-Salam Ouedraogo, Phimpha Paboriboune, Jean William Pape, Ana Tereza Ribeiro Vasconcelos, Luc Samison, Marilda Agudo Mendonça Siqueira, Nestani Tukvadze, Florence Komurian Pradel

“…Introduction The Global Approach to Biology Research, Infectious diseases and Epidemics in Low-income countries (GABRIEL) network is an international scientific network of 21 centres coordinated by the Merieux Foundation (Lyon, France). Mapping and characterising the similarities and differences in expertise and activities across four major infectious diseases (tuberculosis, antimicrobial-resistant infections, acute respiratory infections and emerging pathogens) among these centres would help to provide a better understanding of the network’s capacity. …”
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AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks by Mayalen Etcheverry, Clément Moulin-Frier, Pierre-Yves Oudeyer, Michael Levin

“…Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, and controlling the complex behavior of chemical and genetic networks. …”
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UNS Geo: LiDAR Dataset for point cloud classification in urban areas by M. Govedarica, G. Jakovljevic, I. Ruskoviski, V. Pajic

“…The classification of the urban point cloud is an essential task for numerous applications, including mapping, 3D urban modelling, etc.. Although in the last few years, different methodologies and algorithms have been proposed, precise and detailed point cloud labelling is still challenging. …”
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A Hybrid Machine Learning Model for Accurate Autism Diagnosis by Durga Prasad Kavadi, Venkata Rami Reddy Chirra, Palacharla Ravi Kumar, Sai Babu Veesam, Sagar Yeruva, Lalitha Kumari Pappala

“…Additionally, a hybrid classification approach is introduced, combining Autoencoder (AE) with the Butterfly Optimization Algorithm (BOA) to enhance detection accuracy. To manage and process large datasets effectively, the MapReduce tool is used for efficient data handling. …”
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Multi-Platform Detection of Melon Leaf Abnormalities Using AVGHEQ and YOLOv7 by Sahrial Ihsani Ishak, Karlisa Priandana, Sri Wahjuni

“…The system employs preprocessing with Average Histogram Equalization (AVGHEQ) to enhance image quality, followed by modeling with the YOLOv7 algorithm on a dataset of 469 training images and 52 test images, validated through 5-fold cross-validation. …”
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Estimation of Anthocyanins in Apple Leaves Based on Ground Hyperspectral Imaging and Machine Learning Models by Yu Zhang, Mi Zou, Yanjun Li, Qingrui Chang, Xing Chen, Zhiyong Dai, Weihao Yuan

“…The original hyperspectral imaging at wavelengths before 720 nm shows a decrease in reflectance as the growth stages progress, while the spectral curves after 720 nm remain largely consistent across stages; (2) Compared to single original spectral variables, multivariate estimation models using original spectra and second-order derivative transformed spectra show improved accuracy for anthocyanins estimation across different growth stages, with the most significant improvement during the Fruit Enlargement stage; (3) Although the computation of the three-band spectral indices is resource-intensive and time-consuming, it can enhance anthocyanins estimation accuracy; (4) Among all models, the CatBoost model based on original spectra and second-order derivative transformed spectra indices for the entire growth period achieved the highest accuracy, with a validation set R² of 0.934 and a RPD of 3.888, and produced effective leaf anthocyanins inversion maps. …”
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Land-cover classification with remote sensing images based on low-rank fusion of multimodal features by LIU Wenjie, WU Xiaoning, DONG Fuan, ZHANG Jinwen, LI Yiyang, CHEN Yong

“…This article proposes a unified multimodal remote sensing feature classification network, which includes: a weight sharing backbone network responsible for extracting preliminary feature representations from the input data of each modality; The multimodal feature low rank fusion module performs cross modal transmission on high-level semantic features to enhance semantic interaction between modalities; The upsampling operation is responsible for restoring the fused feature map to the same resolution as the input image. …”
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