Automatic detection of pupil reactions in cataract surgery videos. by Natalia Sokolova, Klaus Schoeffmann, Mario Taschwer, Stephanie Sarny, Doris Putzgruber-Adamitsch, Yosuf El-Shabrawi

“…In this work, we automatically detect pupil reactions in cataract surgery videos. …”
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Domain Adaptation for Satellite-Borne Multispectral Cloud Detection by Andrew Du, Anh-Dzung Doan, Yee Wei Law, Tat-Jun Chin

“…In this paper, we address the domain gap problem in the context of onboard multispectral cloud detection. Our main contributions lie in formulating new domain adaptation tasks that are motivated by a concrete EO mission, developing a novel algorithm for bandwidth-efficient supervised domain adaptation, and demonstrating test-time adaptation algorithms on space deployable neural network accelerators. …”
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Potato late blight leaf detection in complex environments by Jingtao Li, Jiawei Wu, Rui Liu, Guofeng Shu, Xia Liu, Kun Zhu, Changyi Wang, Tong Zhu

“…Abstract Potato late blight is a common disease affecting crops worldwide. To help detect this disease in complex environments, an improved YOLOv5 algorithm is proposed. …”
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Automated Computer Vision System for Urine Color Detection by Ban Shamil Abdulwahed, Ali Al-Naji, Izzat Al-Rayahi, Ammar Yahya, Asanka G. Perera

“…To get better assistance for urine color detection in the proposed system, a urine color automatic identification has been developed based on computer vision. …”
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Strawberry Disease Detection Using Multispectral UAV Imagery by A. F. Cheshkova, V. S. Riksen

“…(Results and discussion) Analysis of the multispectral data enabled the identification of informative feature sets for distinguishing between healthy and fungus-infected strawberry plants. A disease detection model developed using the Random Forest algorithm, achieved a classification accuracy of 77%. …”
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Change Detection in Multitemporal High Spatial Resolution Remote-Sensing Images Based on Saliency Detection and Spatial Intuitionistic Fuzzy C-Means Clustering by Liang Huang, Qiuzhi Peng, Xueqin Yu

“…In order to improve the change detection accuracy of multitemporal high spatial resolution remote-sensing (HSRRS) images, a change detection method of multitemporal remote-sensing images based on saliency detection and spatial intuitionistic fuzzy C-means (SIFCM) clustering is proposed. …”
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Spectrum sensing algorithm based on stochastic resonance and non-central F-distribution by Yuanmeng FAN, Shunlan LIU

“…To solve the problem that the detection probability of the spectrum sensing algorithm is low and the number of samples required for detection is large at low signal-to-noise ratio (SNR), a spectrum sensing algorithm based on stochastic resonance and non-central F-distribution (SRNF) was proposed.By introducing direct-current stochastic resonance noise, the system model of SRNF was established, and the expression of test statistic, false alarm probability and detection probability, and the expression of decision threshold obeying non-central F-distribution were deduced, and the optimal stochastic resonance noise parameter was solved by numerical method.The simulation results show that the detection performance of the proposed SRNF algorithm is better than that of energy detection (ED) algorithm and blind spectrum sensing based on F-distribution (BSF) algorithm at a low SNR.When the false alarm probability is 5%, the SNR is -12 dB, and the number of samples is 200, the detection probability of the proposed algorithm is 95%, which is 34% and 67% higher than BSF algorithm and ED algorithm, respectively.When the SNR is -12 dB, and the detection probability reaches 95%, the number of samples required by the proposed algorithm is 210, which saves 340 samples compared to the BSF algorithm.Furthermore, the proposed algorithm is less affected by noise uncertainty than ED algorithm.…”
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Change Detection Network Based on Transformer and Transfer Learning by Hua Li, Jingyu Li, Guanghao Luo, Liang Zhou, Hao Wu, Zhangcai Yin

“…The deep-learning-based change-detection algorithm can extract pixel-level semantic segmentation results for changed objects. …”
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Fire and Smoke Detection Based on Improved YOLOV11 by Zhipeng Xue, Lingyun Kong, Haiyang Wu, Jiale Chen

“…Traditional object detection methods rely more on manually designed features and rules. …”
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Detection of child depression using machine learning methods. by Umme Marzia Haque, Enamul Kabir, Rasheda Khanam

“…The variables of yes/no value of low correlation with the target variable (depression status) have been eliminated. The Boruta algorithm has been utilized in association with a Random Forest (RF) classifier to extract the most important features for depression detection among the high correlated variables with target variable. …”
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Image information optimization processing based on fractional order differentiation and WT algorithm. by Qiong Long

“…Therefore, the study is based on wavelet transform algorithm and fractional order differentiation to perform edge detection and image fusion. …”
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Use of Diagnostic Algorithms for *NTRK* Fusion-Positive Tumors in Pathology Institutes in Switzerland by Holger Moch, Gieri Cathomas, Milo Frattini, Wolfram Jochum, Erik Vassella, Laurence de Leval, Joachim Diebold, Christian Britschgi, Thomas McKee, Lukas Bubendorf

“…While in certain types of tumors an *NTRK* gene fusion is often detectable, it is rare in some other types. As the detection of *NTRK* gene fusion opens up new treatment options for patients, it is vital to ensure that the detection methods and diagnostic algorithms in pathology institutes are optimized and of high quality. …”
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An Algorithm of Train Operation Environment Recognition Based onEmbedded GPU Platform by XIONG Minjun, LI Chen, ZHANG Huiyuan, PENG Liantie, SU Zhen

“…Aiming at the problems of low efficiency, poor accuracy and weak robustness of traditional train operation environment sensing algorithms, a real-time detection algorithm of train operation environment based on image instance segmentation is proposed. …”
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Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

“…Furthermore, while feature selection benefits simpler algorithms (such as RF), normalization is more useful for complex algorithms like ANNs and deep neural networks (DNNs), and algorithms such as Naive Bayes are unsuitable for IDS modeling. …”
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Algorithm for False Alarm Stabilization against the Background of Nonstationary Noise with Trend Estimation by V. A. Belokurov, T. Q. Nguyen

“…Introduction. A detection algorithm that ensures a constant value of the false alarm rate against the background of nonstationary noise, whose average value varies within a sliding window. …”
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Trisomy 21 screening with αlpha software and the Fetal Medicine Foundation algorithm by L Pistorius, C A Cluver, I Bhorat, L Geerts

“…Screening for trisomy 21 provides pregnant women with accurate risk information. Different algorithms are used to screen for trisomy 21 in South Africa (SA). …”
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Incremental cooperative spectrum sensing algorithm with n-out-of-K fusion rule by Xiao-ge ZHANG, Shi-bing ZHANG, Gong-an QIU

“…The algorithm divided the total relays into two subsections.The front subsection included N number of relays,and the later one included K−N number of relays.Firstly,the front N relays sensed the spectrum.If no more than m_L number of relays had detected the existing of the primary user,the global detection was that the spectrum holes existed.If more than m_H number of relays had detected the existing of the primary user,the global detection was that no spectrum holes existed.Otherwise,the later K−N number of relays continued to sense the spectrum.The global detection was that the spectrum holes existed only when there were totally over n number of relays having detected the existing of the primary user in the two sensing stages.The object function was built for minimizing the time-slot consumption by adjusting the parameters m_L,m_H and N with the limit of detection probability and false probability.Simulation results show that the proposed incremental cooperative spectrum sensing algorithm has much lower time-slot consumption than the traditional one by properly setting the parameters with high sensing performance kept.…”
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Analysis of Internet Marketing Forecast Model Based on Parallel K-Means Algorithm by Xiaolei Chen, Sikun Ge

“…Secondly, the weights in the K-means algorithm are mostly only applicable to target detection tasks. …”
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Design of Enhanced License Plate Information Recognition Algorithm Based on Environment Perception by Zilu Wang, Limin Zheng, Gang Li

“…The effectiveness of our proposed perceptual enhancement algorithm is further confirmed by the fact that when validating the China City Parking Dataset 2019 (CCPD 2019), it improves the detection rate by 24.53% compared to traditional image enhancement methods. …”
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Harmonic Measurement Algorithm of Power System Integrating Wavelet Transform and Deep Learning by Hanshu Jiang, Yutian Li, Zhu Liu, Guanghao Wu, Zeyang Liu

“…The new method consistently showed higher accuracy in harmonic detection compared to conventional approaches. CONCLUSION: The study concludes that the proposed harmonic measurement algorithm significantly improves accuracy compared to traditional methods. …”
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