Robust Forward-Looking Sonar-Image Mosaicking Without External Sensors for Autonomous Deep-Sea Mining by Xinran Liu, Jianmin Yang, Changyu Lu, Enhua Zhang, Wenhao Xu

“…For image fusion, a radial adaptive fusion algorithm with a protective frame is proposed to improve edge transitions and preserve structural consistency in the resulting panoramic image. …”
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Experimental Study of Trajectory Features for the Recognition of Low-Flying Low-Speed Radar Targets Using Passive Coherent Radar Systems by V. L. Dao, A. A. Konovalov, M. H. Le

“…The knowledge of differences between the flight path of UAVs and birds can improve the quality of the UAV recognition problem.…”
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CPT-DF: Congestion Prediction on Toll-Gates Using Deep Learning and Fuzzy Evaluation for Freeway Network in China by Tongtong Shi, Ping Wang, Xudong Qi, Jiacheng Yang, Rui He, Jingwen Yang, Yu Han

“…The comparative tests show the proposed CPT-DF (congestion prediction on toll-gates using deep learning and fuzzy evaluation) outperforms the current-used other models by 6-15%. The successful prediction could extend to the real-time prediction and early warning of traffic congestion in the toll system to improve the intelligent level of traffic emergency management and guidance on the key road of disasters to some extent.…”
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Autonomous unmanned aerial vehicles exploration for semantic indoor reconstruction using 3D Gaussian splatting by Hao Xuan Zhang, Yilin Yang, Zhengbo Zou

“…Keeping an up-to-date three-dimensional (3D) representation of buildings is a crucial yet time-consuming step for Building Information Modeling (BIM) and digital twins. To address this issue, we propose ICON (Intelligent CONstruction) drone, an unmanned aerial vehicle (UAV) designed to navigate indoor environments autonomously and generate point clouds. …”
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SPL-PlaneTR: Lightweight and Generalizable Indoor Plane Segmentation Based on Prompt Learning by Zhongchen Deng, Yuanlong Ge, Xiatian Qi, Kai Sun, Ruixi Wan, Bingxu Zhang, Shenman Zhang, Xun Zhang, Yan Meng

“…Notably, our lightweight SPL-PlaneTR also surpasses several state-of-the-art algorithms in this domain. Our code and model have been publicly available.…”
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Precision autofocus in optical microscopy with liquid lenses controlled by deep reinforcement learning by Jing Zhang, Yong-feng Fu, Hao Shen, Quan Liu, Li-ning Sun, Li-guo Chen

“…Additionally, parallel “state” dataset lists with random sampling training are proposed which enhances the model’s adaptability to unknown samples, thereby improving its generalization capability. …”
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SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

“…This method improves tracking performance across various farming environments by enhancing the model’s adaptability to different domains and integrating an optimized tracking strategy, significantly increasing the generalization of group pig tracking technology across different scenarios. …”
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Predicting suicidality in people living with HIV in Uganda: a machine learning approach by Anthony B. Mutema, Anthony B. Mutema, Anthony B. Mutema, Lillian Linda, Lillian Linda, Daudi Jjingo, Segun Fatumo, Segun Fatumo, Eugene Kinyanda, Allan Kalungi, Allan Kalungi, Allan Kalungi

“…Incorporating PRS as an additional feature in the model resulted in a 6% improvement in model sensitivity and a 9% reduction in specificity. …”
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Enhanced Detection of Mitochondrial Heteroplasmy and DNA Hypomethylation in Adipose-Derived Mesenchymal Stem Cells Using a Novel Adaptive Sampling Protocol by Antonina Gospodinova, Yuliia Mariienko, Diana Pendicheva-Duhlenska, Soren Hayrabedyan, Krassimira Todorova

“…Third-generation sequencing overcomes the limitations of traditional mtDNA analysis methods, offering improved cost, throughput, and sensitivity. We developed an integrated approach for analyzing methylation patterns and genetic variations in mtDNA and ADME genes. …”
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FDG‐PET patterns associate with survival in patients with prion disease by Nick Corriveau‐Lecavalier, Yoav D. Piura, Brian S. Appleby, Dror Shir, Leland R. Barnard, Venkatsampath Gogineni, David T. Jones, Gregory S. Day

“…Advances in diagnostic testing have improved recognition of patients with atypical presentations and protracted disease courses, raising key questions surrounding the relationship between patterns of neurodegeneration and survival. …”
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A novel and sturdy MPPT architecture for grid-tied EV charging stations using Ali Baba and forty thieves optimization by Debabrata Mazumdar, Hassan Abdurrahman Shuaibu, Chiranjit Sain, Taha Selim Ustun

“…This approach aims to optimize modelling for all EV fleets. The developed method performs exceptionally well in comparison to other algorithms that have been studied in the literature. …”
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The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…Subsequently, a hybrid optimization method is designed, combining the Genetic Algorithms with particle swarm optimization to improve the model’s global search capability and local convergence speed. …”
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Utilizing Multi-omics analysis to elucidate the role of mitochondrial gene defects in Gastric cancer progression. by Jie Chu, Hanying Song, Kemin Fu, Wei Xiao, Jiudong Jiang, Qixin Gan, Bo Deng

“…Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”
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Discrete Phase Shift IRS-Assisted Energy Harvesting in Cognitive Radio Networks With Spectrum Sensing by Lilian Chiru Kawala, Guoquan Li, Mihertie Habtamu Demeke, Junzhou Xiong, Hao Xiong, Hang Hu

“…Simulation results demonstrate the superior performance of the proposed framework and the novel resource allocation algorithm based on alternating optimization. These results highlight the transformative potential of IRS with discrete phase shifts in enhancing EH-CRN efficiency, particularly in improving energy harvesting and SU throughput under practical constraints.…”
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Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

“…Abstract Smart waste management is vital for reducing environmental impact and improving quality of life in smart cities. This study presents an AI-driven waste classification model that integrates IoT and Blockchain technologies. …”
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Multiphysics Feature-Based State-of-Energy Estimation for LiFePO4 Batteries Using Bidirectional Long Short-Term Memory and Particle Swarm-Optimized Kalman Filter by Zhengpu Wu, Xu He, Haisen Chen, Lu Lv, Jiuchun Jiang, Lujun Wang

“…Experimental results across different operating conditions and temperatures reveal that the introduction of mechanical force significantly improves SOE estimation accuracy. Compared to models using only traditional electrical and thermal features, the model with the introduction of mechanical force achieves average improvements of 67.06%, 66.38%, and 66.46% for the root mean square error (RMSE), maximum absolute error (MAXE), and mean absolute error (MAE), respectively. …”
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Attention mechanism and mixup data augmentation for classification of COVID-19 Computed Tomography images by Özgür Özdemir, Elena Battini Sönmez

“…Moreover, the original performance of the network has been improved using the mixup data augmentation technique. …”
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The use of artificial intelligence in stereotactic ablative body radiotherapy for hepatocellular carcinoma by Atsuto Katano

“…Clinical studies have demonstrated notable benefits, such as a reduction in contouring time and improved dosimetric quality using machine learning–based optimization algorithms. …”
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MSF-GhostNet: Computationally Efficient YOLO for Detecting Drones in Low-Light Conditions by Maham Misbah, Misha Urooj Khan, Zeeshan Kaleem, Ali Muqaibel, Muhamad Zeshan Alam, Ran Liu, Chau Yuen

“…We also integrated autoanchor and batch size mechanisms to ensure efficient model training and avoid overfitting. Our proposed model showed 1.25% fewer false positives than the state-of-the-art GhostNet-YOLOv5 model. …”
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Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma by Yun Liang, Yun Liang, Min He, Wenqing Chen, Wenqing Chen, Lizhen Li, Lizhen Li, Yumeng Dong, Yumeng Dong, Gang Liang, Hui Huangfu, Zengyu Jiang, Zengyu Jiang, Sheng He, Sheng He, Sheng He

“…Radiomics features were extracted from CT images, and 7 machine learning algorithms were used to develop 7 radiomics models, which were combined with deep learning features extracted from the ResNet50 deep learning network to form deep learning radiomics (DLR) models. …”
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