MCFNet: Multi-Scale Contextual Fusion Network for Salient Object Detection in Optical Remote Sensing Images by Jinting Ding, Yueqian Quan, Honghui Xu

“…Despite increasing attention, salient object detection for optical remote sensing images (ORSI-SOD) remains highly challenging due to the intrinsic complexities of remote sensing scenes. …”
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Ship crack detection method based on lightweight fast convolution and bidirectional weighted feature fusion network by Chong WANG, Yuhui ZHU

“…ObjectiveAs traditional ship crack detection methods based on artificial visual inspection and ultrasonic methods in ship repair and inspection processes have the characteristics of low efficiency, high cost and high danger, a ship crack detection method based on deep learning is proposed. …”
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Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…Comparative analysis shows that DLECA outperforms Random Walk and Bayesian Optimization in multimodal fake news detection, offering a more efficient and accurate solution.…”
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YOLO-SUMAS: Improved Printed Circuit Board Defect Detection and Identification Research Based on YOLOv8 by Ying Tang, Runhao Liu, Sheng Wang

“…Aiming at the demand for defect detection accuracy and efficiency under the trend of high-density and integration in printed circuit board (PCB) manufacturing, this paper proposes an improved YOLOv8n model (YOLO-SUMAS), which enhances detection performance through multi-module collaborative optimization. …”
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Detection of Mycotoxins in Cereal Grains and Nuts Using Machine Learning Integrated Hyperspectral Imaging: A Review by Md. Ahasan Kabir, Ivan Lee, Chandra B. Singh, Gayatri Mishra, Brajesh Kumar Panda, Sang-Heon Lee

“…Mycotoxins exhibit heightened sensitivity to specific spectral bands within HSI, facilitating accurate detection. Additionally, selecting only relevant spectral features reduces ML model complexity and enhances reliability in the detection process. …”
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BurgsVO: Burgs-Associated Vertex Offset Encoding Scheme for Detecting Rotated Ships in SAR Images by Mingjin Zhang, Yaofei Li, Jie Guo, Yunsong Li, Xinbo Gao

“…Moreover, oriented bounding box-based detection methods often prioritize accuracy excessively, leading to increased parameters and computational costs, which in turn elevate computational load and model complexity. …”
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Deep learning-based dual monitoring system for power forecasting and fault detection in nuclear power applications by Mingzhe Lyu, Helin Gong, Zhang Chen, Jiangyu Wang, Mingxiao Zhong, Zhiyong Wang, Qing Li, Zefei Pan

“…For fault diagnosis, the dual-monitoring system reduces the false negative rate to 18.73% and improves recall to 81.27%, demonstrating strong anomaly detection under complex conditions. By combining short-term fluctuation sensitivity with long-term trend stability, the proposed approach offers a robust and generalizable solution for intelligent monitoring. …”
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MSCD-YOLO: A Lightweight Dense Pedestrian Detection Model with Finer-Grained Feature Information Interaction by Qiang Liu, Zhongmin Li, Lei Zhang, Jin Deng

“…The experimental results show that under the same experimental conditions, MSCD-YOLO significantly outperforms the original model in terms of detection accuracy, efficiency, and model complexity.…”
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YOLOv10-kiwi: a YOLOv10-based lightweight kiwifruit detection model in trellised orchards by Jie Ren, Wendong Wang, Yuan Tian, Jinrong He

“…YOLOv10-Kiwi offers an efficient solution for automated kiwifruit detection on low-power agricultural robots.…”
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Towards automatic farrowing monitoring-A Noisy Student approach for improving detection performance of newborn piglets. by Martin Wutke, Clara Lensches, Ulrich Hartmann, Imke Traulsen

“…Challenges such as frequent animal occlusions, high overlapping rates or strong heterogeneous animal postures increase the complexity and place new demands on the detection model. …”
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Analyzing the Efficacy of Computer-Aided Detection in Cerebral Aneurysm Diagnosis Using MRI Modality: A Review by Keerthi A. S. Pillai, Preena K. P., Madhu S. Nair

“…CNNs have proven to be a crucial component in improving the accuracy and efficiency of aneurysm detection by automatically learning features from raw imaging data, bypassing the need for manual feature extraction. …”
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ContourTL-Net: Contour-Based Transfer Learning Algorithm for Early-Stage Brain Tumor Detection by N. I. Md. Ashafuddula, Rafiqul Islam

“…An increasing patient longevity rate requires prompt detection; however, the complexities of brain tissue make early diagnosis challenging. …”
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Multi-Signal Induction Motor Broken Rotor Bar Detection Based on Merged Convolutional Neural Network by Tianyi Wang, Shiguang Wen, Shaotong Sheng, Huimin Ma

“…Traditional methods face challenges in motor broken rotor bar (BRB) detection: model-driven methods are difficult to apply accurately in complex and changing environments, while data-driven methods usually require sophisticated feature extraction and classification processes. …”
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Intelligent Stress Detection Using ECG Signals: Power Spectrum Imaging with Continuous Wavelet Transform and CNN by Rodrigo Mateo-Reyes, Irving A. Cruz-Albarran, Luis A. Morales-Hernandez

“…The proposed approach is characterized by its ability to transform ECG signals into time–frequency representations by means of short duration sampling, achieving an accurate classification of stress states without the need for complex feature extraction processes. This model is an efficient and accurate tool for stress analysis from biomedical signals.…”
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A Dual-Task Approach for Onset Time Picking and the Detection of Microseismic Waveforms Based on Deep Learning by Hang Zhang, Ruoyu Li, Chunchi Ma, Xiaobing Cheng, Simeng Meng, Zhenxing Huang, Di Li

“…Before the analysis of source information and further prediction of possible disasters, it is generally necessary to perform onset time picking and detection of microseismic signals. To improve the accuracy and efficiency of these tasks, this paper proposes an advanced deep dual-task neural network, which sequentially integrates the two processes. …”
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LGR-Net: A Lightweight Defect Detection Network Aimed at Elevator Guide Rail Pressure Plates by Ruizhen Gao, Meng Chen, Yue Pan, Jiaxin Zhang, Haipeng Zhang, Ziyue Zhao

“…LGR-Net achieves low computational complexity and high detection accuracy, providing an efficient and effective solution for defect detection in elevator guide rail pressure plates.…”
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Research on detection and location method of safflower filament picking points during the blooming period in unstructured environments by Bangbang Chen, Feng Ding, Baojian Ma, Qijun Yao, Shanping Ning

“…Secondly, a novel lightweight segmentation detection head (LSDH) was introduced, based on the YOLO-SaFi model, to efficiently segment safflower filaments and fruit balls. …”
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Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting? by Nouf Alturayeif, Jameleddine Hassine

“…However, automated tools with advanced ML techniques are increasingly recognized as essential for efficiently identifying quality issues in large and complex codebases, enhancing the overall effectiveness of code review processes. …”
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LS-MambaNet: Integrating Large Strip Convolution and Mamba Network for Remote Sensing Object Detection by Lingyu Yan, Zijian He, Zhiqi Zhang, Guangqi Xie

“…To address the above challenges, we propose a new target detection framework for complex remote sensing images, LS-MambaNet. …”
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An Optimally Oriented Coherence Attribute Method and Its Application to Faults and Fracture Sets Detection in Carbonate Reservoirs by Shuai Chen, Shengjun Li, Qi Ma, Lu Qin, Sanyi Yuan

“…Overall, the OOCA method offers a geologically consistent and computationally efficient solution for high-resolution fault interpretation and drilling risk prediction in structurally complex carbonate reservoirs.…”
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