A Benchmark Dataset for Aircraft Detection in Optical Remote Sensing Imagery by Jianming Hu, Xiyang Zhi, Bingxian Zhang, Tianjun Shi, Qi Cui, Xiaogang Sun

“…The problem is that existing aircraft detection datasets rarely simultaneously consider the diversity of target features and the complexity of environmental factors, which has become an important factor restricting the effectiveness and reliability of aircraft detection algorithms. …”
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A dense multi-pooling convolutional network for driving fatigue detection by Qing Han, Shimiao Cui, Weidong Min, Cong Yan, Li Liu, Feng Ning, Longfei Li

“…In the DSD module, MTCNN is employed to locate the driver’s face and detect facial landmarks in real time. Additionally, a face detection bounding box filtering algorithm is proposed to reduce false detections of the driver. …”
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Implementing E-MOTIVE for detection and treatment of postpartum haemorrhage in South Africa by M Singata-Madliki, S Fawcus, N Moran, E Arends, E Muller, S Mandondo, G J Hofmeyr

“…E-MOTIVE was integrated into the existing Essential Steps in Managing Obstetric Emergencies algorithm. Certain research-related elements of the trial setting cannot be replicated in routine practice. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…For regression and classification, deep neural network (DNN) from deep learning algorithms and support vector machine (SVM), decision trees (DTs), k-nearest neighbor (KNN), random forest (RF), logistic regression (LR), and extreme gradient boosting (XGBoost) algorithms from machine learning algorithms were used. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…The results highlight the system’s effectiveness in detecting security threats and improving navigation through adaptive recommendations. …”
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Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy Devices by Muhammad Ahsan Sami, Muhammad Nabeel Tahir, Umer Hassan

“…This visual improvement was then quantified by calculating the signal-difference-to-noise ratio (SDNR) and contrast-to-noise ratio (CNR) of filtered and unfiltered original images using a custom-developed quality assessment algorithm (AQAFI). Lastly, noise correction using Averaging and Gaussian filters with the previously identified optimal parameters was applied to images of fluorescently tagged human peripheral blood leukocytes captured using an SFM under various conditions. …”
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Breast cancer survival prediction using an automated mitosis detection pipeline by Nikolas Stathonikos, Marc Aubreville, Sjoerd deVries, Frauke Wilm, Christof A Bertram, Mitko Veta, Paul J vanDiest

“…In conclusion, a fully automated MC AI algorithm was validated in a large cohort of breast cancer with regard to retained prognostic value compared with traditional light‐microscopic MC.…”
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An improved YOLOv5s-based method for detecting rice leaves in the field by Cheng Zhou, Caohang Zhou, Lili Yao, Yagang Du, Xin Fang, Zhangbin Chen, Chengliang Yin

“…First, we added a high-resolution layer and removed the original low-resolution detection layer, using the K-Means++ clustering algorithm to reset the anchor box sizes, enhancing the model’s ability to identify small leaf tip targets while reducing the number of parameters. …”
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Detecting global financial crises with scarce data by multivariate nonlinear filtering by Cécile Bastidon, Antoine Parent, Patrice Abry, Pierre Borgnat, Pablo Jensen, Barbara Pascal

“…It consists of: i) the construction of time series from the time-windowed estimations of crisis relevant information (cross-correlations or volatilities); ii) the piecewise-linear filtering of times series by nonlinear filtering, achieved by nonsmooth proximal minimization implemented by an efficient iterative algorithm; iii) the estimation of a reassigned time in each window; iv) the detection of crises and estimation of their intensities by exploiting the multivariate structure of denoised time series. …”
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Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification by Zne-Jung Lee, Jing-Xun Cai, Liang-Hung Wang, Ming-Ren Yang

“…<b>Background:</b> Ovarian cancer is a difficult and lethal illness that requires early detection and precise classification for effective therapy. …”
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Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage by Zhenzhuo Wei, Wei Guo, Yanjun Lan, Ben Liu, Yu Sun, Sen Gao

“…In this study, a data-driven cooperative localization algorithm with a velocity prediction model is proposed to improve the positioning accuracy of DSLV under track slippage. …”
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A Quadratic Traversal Algorithm of Shortest Weeding Path Planning for Agricultural Mobile Robots in Cornfield by Le Zhang, Rui Li, Zhiqiang Li, Yuyao Meng, Jinxin Liang, Leiyang Fu, Xiu Jin, Shaowen Li

“…Finally, based on the contour of the target plants and the Canny edge detection operator, the shortest weeding path guidance can be calculated by the proposed quadratic traversal algorithm. …”
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Improvement of YOLO v8 Segmentation Algorithm and Its Study in the Identification of Hazards in Plateau Pika by Yaosheng Han, Yunpeng Jin, Chunmei Li, Xiangjie Huang

“…Secondly, the latest segmentation algorithm provided by YOLO v8 is improved to design a segmentation algorithm that can accurately detect the distribution of rodent infestation in the plateau scene. …”
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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…Lung segmentation plays a pivotal role in the diagnostic pipeline, directly impacting the accuracy of disease detection and treatment planning. This study presents an advanced AI-driven framework, optimized through genetic algorithms, for precise lung segmentation in early cancer diagnosis. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…ObjectivePedestrian detection is a crucial task in computer vision, especially in applications like autonomous driving, robot navigation, and intelligent surveillance. …”
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Hyperspectral Simultaneous Anomaly Detection and Denoising: Insights From Integrative Perspective by Minghua Wang, Lianru Gao, Longfei Ren, Xian Sun, Jocelyn Chanussot

“…The proposed algorithm is efficiently solved by the well-designed linearized alternating direction method of multipliers with an adaptive penalty. …”
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Deep Learning-Based Postural Asymmetry Detection Through Pressure Mat by Iker Azurmendi, Manuel Gonzalez, Gustavo García, Ekaitz Zulueta, Elena Martín

“…These pressure platforms generate data that can be very useful for detecting postural anomalies. In this paper we will discuss the application of deep learning algorithms in the analysis of pressure data for the detection of postural asymmetries in 139 patients aged 3 to 20 years. …”
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Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype by Chenzheng Gu, Junlu Wu, Wei Zhang, Yiwen Yao, Wenhui Yan, Yi Yuan, Weiwei Wang, Anquan Shang

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An Efficient Density-Based Local Outlier Detection Approach for Scattered Data by Shubin Su, Limin Xiao, Li Ruan, Fei Gu, Shupan Li, Zhaokai Wang, Rongbin Xu

“…In addition, the outlier data occupy a relatively small amount in the dataset, but the existing approaches need to perform local outlier factor calculation on all data during the outlier detection, which greatly reduces the efficiency of the algorithms. …”
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A Review of Research on Cloud Detection Methods for Hyperspectral Infrared Radiances by Zhuoya Ni, Mengdie Wu, Qifeng Lu, Hongyuan Huo, Chunqiang Wu, Ruixia Liu, Fu Wang, Xiaoying Xu

“…The results indicate the use of deep learning methods offer advantages in detection accuracy and algorithm efficiency of hyperspectral IR cloud detection.…”
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