AI-Based Forecasting in Renewable-Rich Microgrids: Challenges and Comparative Insights by Martins Osifeko, Josiah Lange Munda

“…Classical ML models outperformed most DL architectures, including Transformer and Convolutional Neural Network (CNN)-LSTM, which underperformed despite their complexity. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…Furthermore, we propose a Position–Morphology Matching IoU loss function, P-MIoU, which integrates center distance constraints and morphological penalty mechanisms to more precisely capture the spatial and structural differences between predicted and ground truth bounding boxes. …”
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Analysis of the mechanism of physical activity enhancing well-being among college students using artificial neural network by Yuxin Cong, Roxana Dev Omar Dev, Shamsulariffin Bin Samsudin, Kaihao Yu

“…Concurrently, the regulatory influence of sports behavior demonstrates differing intensities across diverse conditions. This study provides a new theoretical basis for designing personalized sports interventions and improves the accuracy of predicting psychological measurement data. …”
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Tomato detection in natural environment based on improved YOLOv8 network by Wancheng Dong, Yipeng Zhao, Jiaxing Pei, Zuolong Feng, Zhikai Ma, Leilei Wang, Simon Shemin Wang

“… In this paper, an improved lightweight YOLOv8 method is proposed to detect the ripeness of tomato fruits, given the problems of subtle differences between neighboring stages of ripening and mutual occlusion of branches, leaves, and fruits. …”
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Methodology for Occupant Head-Neck Injury Testing in Under-Body Blast Impact Based on Virtual-Real Fusion by Xinge Si, Changan Di, Peng Peng, Cong Xu

“…To address the limitations of low-cost, simplified dummy head–neck structures, which exhibit significant differences in mechanical properties compared to high-biofidelity dummies, a virtual–real fusion-based test method for assessing occupant head–neck injury in under-body blast impacts is proposed. …”
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An artificial intelligence algorithm for the detection of pulmonary ground-glass nodules on spectral detector CT: performance on virtual monochromatic images by Zhong-Yan Ma, Hai-lin Zhang, Fa-jin Lv, Wei Zhao, Dan Han, Li-chang Lei, Qin Song, Wei-wei Jing, Hui Duan, Shao-Lei Kang

“…And Delong’s test indicated that the differences between the area-under-the-curve (AUC) values of the CPIs group and the VMIs group were not statistically significant (P > 0.05). …”
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Surface water mapping from remote sensing in Egypt’s dry season using an improved U-Net model with multi-scale information and attention mechanism by Yong Li, Xiuhui Liu, Vagner Ferreira, Heiko Balzter, Huiyu Zhou, Ying Ge, Meiyun Lai, Simin Chu, Han Ding, Zhenrong Gu

“…During dry seasons, Egyptian water bodies exhibit unique challenges for remote sensing detection due to their significant spectral differences, complex morphological patterns, and numerous small streams. …”
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Choroidal neovascularization activity and structure by optical coherence tomography angiography in age related macular degeneration by M. A. Kovalevskaya, O. A. Pererva

“…Group 1A: Df – 1.5871 ± 0.05, CVS – 2.29 ± 0.29, area – 11734 ± 4866; group 1B: Df – 1.6462 ± 0.08, CVS – 1.65 ± 0.18, area – 6797 ± 3818; control: Df – 1.9167 ± 0.06, CVS – 1, area – 0. Significant differences were found for CVS (p = 0.0003). Df correlates with the CNV area (p = 0.7) and is probably an unreliable parameter due to incomplete visualization of active CNV.Conclusions. …”
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An Improved V-Net Model for Thyroid Nodule Segmentation by Büşra Yetginler, İsmail Atacak

“…In practice, manual segmentation methods based on ultrasound images are widely used; however, owing to the limitations arising from the imaging sources and differences based on radiologist opinions, their standalone use may not be sufficient for thyroid nodule segmentation. …”
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Revealing Depression Through Social Media via Adaptive Gated Cross-Modal Fusion Augmented With Insights From Personality Traits by Gede Aditra Pradnyana, Wiwik Anggraeni, Eko Mulyanto Yuniarno, Mauridhi Hery Purnomo

“…However, existing multimodal depression detection approaches often adopt rigid fusion strategies and disregard individual differences in expressive behavior by adopting generalized, one-size-fits-all frameworks. …”
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Hybrid AI and semiconductor approaches for power quality improvement by Ravikumar Chinthaginjala, Asadi Srinivasulu, Anupam Agrawal, Tae Hoon Kim, Sivarama Prasad Tera, Shafiq Ahmad

“…The results showed notable differences in performance, with deep learning models, especially LSTM, proving to be more accurate and dependable in identifying and forecasting power quality issues. …”
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Private Data Incrementalization: Data-Centric Model Development for Clinical Liver Segmentation by Stephanie Batista, Miguel Couceiro, Ricardo Filipe, Paulo Rachinhas, Jorge Isidoro, Inês Domingues

“…However, these models often face challenges in adapting to diverse clinical data sources as differences in dataset volume, resolution, and origin impact generalization and performance. …”
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A Rapid Identification Method for Cottonseed Varieties Based on Near-Infrared Spectral and Generative Adversarial Networks by Qingxu Li, Hao Li, Renhao Liu, Xiaofeng Dong, Hongzhou Zhang, Wanhuai Zhou

“…China is a major cotton-growing country with numerous cotton varieties, each exhibiting significant differences in yield and fiber quality. However, the current management of cottonseed varieties is disorganized, resulting in severe homogenization and the presence of counterfeit and mislabeled varieties. …”
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Experimental Study on Heat Transfer Performance of FKS-TPMS Heat Sink Designs and Time Series Prediction by Mahsa Hajialibabaei, Mohamad Ziad Saghir

“…Among all configurations, the P6 design demonstrated the best performance, with surface temperature differences ranging from 13.1 to 14.2 °C at 0.019 kg/s and a 54.46% higher heat transfer coefficient compared to the P8 design at the lowest mass flow rate. …”
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PI-ADFM: Enhancing Multimodal Remote Sensing Image Matching Through Phase-Integrated Aggregated Deep Features by Haiqing He, Shixun Yu, Yongjun Zhang, Yufeng Zhu, Ting Chen, Fuyang Zhou

“…Geometric distortions and significant nonlinear radiometric differences in multimodal remote sensing images (MRSIs) introduce substantial noise in feature extraction. …”
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Wi-FiAG: Fine-Grained Abnormal Gait Recognition via CNN-BiGRU with Attention Mechanism from Wi-Fi CSI by Anming Dong, Jiahao Zhang, Wendong Xu, Jia Jia, Shanshan Yun, Jiguo Yu

“…This dual-feature extraction capability positions the proposed CNN-BiGRU architecture as a promising approach for enhancing classification accuracy in scenarios involving multiple gaits with subtle differences in their characteristics. Moreover, the attention mechanism is employed to selectively focus on critical spatiotemporal features for fine-grained abnormal gait detection, enhancing the model’s sensitivity to subtle anomalies. …”
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Artificial Intelligence in the Surgery-First Approach: Harnessing Deep Learning for Enhanced Condylar Reshaping Analysis: A Retrospective Study by Umberto Committeri, Gabriele Monarchi, Massimiliano Gilli, Angela Rosa Caso, Federica Sacchi, Vincenzo Abbate, Stefania Troise, Giuseppe Consorti, Francesco Giovacchini, Valeria Mitro, Paolo Balercia, Antonio Tullio

“…The SFA and SLA exhibited similar rates of condylar surface remodeling, with minor differences in resorption and formation across dentoskeletal classifications. …”
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A rapid, low-cost deep learning system to classify strawberry disease based on cloud service by Guo-feng YANG, Yong YANG, Zi-kang HE, Xin-yu ZHANG, Yong HE

“…Compared with popular Convolutional Neural Networks (CNN) and five other methods, our network achieves better disease classification effect. …”
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Electrocardiograph analysis for risk assessment of heart failure with preserved ejection fraction: A deep learning model by Zheng Gao, Yuqing Yang, Zhiqiang Yang, Xinyue Zhang, Chao Liu

“…Methods and results A cohort study was conducted utilising data from Cohorts A and B. A convolutional neural network‐long short‐term memory (CNN‐LSTM) DLM was employed. …”
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Application of Deep Learning Techniques in Uranium Microparticle Fission Track Detection by ZHAO Xiong, REN Fangda, SHEN Yan

“…Uranium microparticle isotopic ratios are closely linked to uranium enrichment activities and distinctly differ from natural uranium isotopes. Through isotopic analysis of uranium microparticles, important information regarding material origins, production processes, and products can be obtained. …”
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