Enhancing Real-Time Aerial Image Object Detection with High-Frequency Feature Learning and Context-Aware Fusion by Xin Ge, Liping Qi, Qingsen Yan, Jinqiu Sun, Yu Zhu, Yanning Zhang

“…Aerial image object detection faces significant challenges due to notable scale variations, numerous small objects, complex backgrounds, illumination variability, motion blur, and densely overlapping objects, placing stringent demands on both accuracy and real-time performance. …”
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RSDCNet: An efficient and lightweight deep learning model for benign and malignant pathology detection in breast cancer by Yuan Liu, Haipeng Li, Zhu Zhu, Chen Chen, Xiaojing Zhang, Gongsheng Jin, Hongtao Li

“…Traditional diagnostic methods, reliant on manual interpretation, are not only time-intensive and subjective but also susceptible to variability based on the pathologist's expertise and workload. …”
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IoT-Enhanced Smart Parking Management With IncepDenseMobileNet for Improved Classification by Xiaoxia Zheng, Wenxi Feng, Ning Wang, Huhemandula

“…Advanced preprocessing techniques, such as Temporal Variability Adjustment and Harmonic Noise Compensation, enhanced data quality, while Proportional Adaptive Balancing and Augmentation (PABA) addressed class imbalance. …”
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Automatic detection of optic canal fractures and recognition and segmentation of anatomical structures in the orbital apex based on artificial intelligence by Yu-Lin Li, Yu-Hao Li, Mu-Yang Wei, Guang-Yu Li

“…However, diagnosing OCF can be challenging for inexperienced clinicians due to atypical OCF changes in imaging studies and variability in optic canal anatomy. This study aimed to develop an artificial intelligence (AI) image recognition system for OCF to assist in diagnosing OCF and segmenting important anatomical structures in the orbital apex.MethodsUsing the YOLOv7 neural network, we implemented OCF localization and assessment in CT images. …”
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A Multi-Scale Adaptive Fusion Network: End-to-End Interpretable Small-Sample Classifier for Motor Imagery EEG by Qiulei Han, Yan Sun, Ze Song, Hongbiao Ye, Tingwei Chen, Jian Zhao

“…However, the non-stationarity and individual variability of EEG signals present significant challenges to improving decoding accuracy. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The GAT model exhibited less variability in its median error 0.22, 0.21, and 0.038, respectively, in each case. …”
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DaGAM-Trans: Dual graph attention module-based transformer for offline signature forgery detection by Sara Tehsin, Ali Hassan, Farhan Riaz, Inzamam Mashood Nasir

“…Its outstanding performance, especially in reducing error rates and handling cross-linguistic signature variability, demonstrates its robustness and applicability for real-world biometric and forensic authentication tasks.…”
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