ALGORITHM OF PREPARATION OF THE TRAINING SAMPLE USING 3D-FACE MODELING by D. I. Samal, I. I. Frolov

“…The preparation and preliminary processing of images contains the following constituents like detection and localization of area of the person on the image, assessment of an angle of rotation and an inclination, extension of the range of brightness of pixels and an equalization of the histogram to smooth the brightness and contrast characteristics of the processed images, scaling of the localized and processed area of the person, creation of a vector of features of the scaled and processed image of the person by a Principal component analysis (algorithm NIPALS), training of the multiclass SVM-classifier.The provided algorithm of expansion of the training selection is oriented to be used in practice and allows to expand using 3D-models the processed range of 2D – photographs of persons that positively affects results of identification in system of face recognition. …”
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Evaluation of Human Action Based on Feature-Weighted Dynamic Time Warping by Mingdie Yan, Xia Liu, Zhaoyang Li, Naiyu Guo

“…Firstly, we collected human skeletal key-point data based on a depth camera and processed these data with gap filling and filtering; then, the effective data segments were segmented from the whole action dataset, angle and distance features were extracted, and the feature matrix was obtained; then, we used the Euclidean Barycenter Dynamic Time Warping–Barycenter Averaging algorithm to produce action templates; finally, we proposed a Feature-Weighted Dynamic Time Warping algorithm to calculate the similarity between the detected action and the template action and established an action achievement score mechanism to evaluate the rehabilitation action. …”
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FEATURES OF DIAGNOSTIC AND THERAPEUTIC TACTICS FOR BLUNT ABDOMINAL TRAUMA WITH DAMAGE TO THE PANCREAS by A. B. Singayevsky, S. G. Scherbak, B. V. Sigua, N. M. Vrublevsky, A. V. Nikiforenko, A. A. Kurkov, A. K. Dyukov

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Texture Analysis and Classification using Local Binary Patterns and Statistical Features by Hasan Maher

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Honeyword Generation Using a Proposed Discrete Salp Swarm Algorithm by Yasser A. Yasser, Ahmed T. Sadiq, Wasim AlHamdani

“…The honeyword system is an effective password cracking detection system designed to easily detect password cracking in order to improve the security of hashed passwords. …”
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Emotion Recognition in the Eye Region Using Textural Features, IBP and HOG by Laura Jalili, Josue Espejel, Jair Cervantes, Farid Lamont

“…By focusing on these regions, we aim to accurately capture the nuances of emotional states. Methodology: The algorithm we devised not only detects facial features but also autonomously isolates the eyes and mouth regions. …”
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Bag of Feature-Based Ensemble Subspace KNN Classifier in Muscle Ultrasound Diagnosis of Diabetic Peripheral Neuropathy by Kadhim K. Al-Barazanchi, Ali H. Al-Timemy, Zahid M. Kadhim

“…This work develops a computer-aided diagnostic (CAD) system based on muscle ultrasound that integrates the bag of features (BOF) and an ensemble subspace k-nearest neighbor (KNN) algorithm for DPN detection. …”
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Crop classification with deep convolutional neural network based on crop feature by Mohamad Reza Gili, Davoud Ashourloo, Hosein Aghighi, Ali Akbar Matkan, Alireza SHakiba

“…Then the algorithm was implemented using these feature channels in the test area and the overall accuracy was upgraded to 86% and the kappa coefficient to 0.82 compared to which indicated a significant improvement in the results compared to the previous case.Conclusion:The deep convolutional neural network is very sensitive to the type of input channels for detecting agricultural crops and selecting the channels with suitable tempo-spectral characteristics for different types of crops, has a great impact on the accuracy of network training and can reduce the loss of training network and increase its efficiency in the classification of various crops.…”
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A Polyp Segmentation Algorithm Based on Local Enhancement and Attention Mechanism by Lanxi Fan, Yu Jiang

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Research on lightweight weed recognition algorithm based on improved YOLOv8 by Zhang Chao, Liu Bin, Li Kun

“…Then, Effcient-RepGFPN is introduced as the neck network, and RFAConv is used to replace the two CSPStage modules before up-sampling. Different scale features are used to improve the performance of target detection. …”
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Research on Semantic Segmentation Algorithm for Infrared Moving Targets in Complex Backgrounds by Ji Haoyu, Meng Weihua, Zhang Xinchao, Duan Jingfei, Zhang Meng

“…Based on the publicly available target detection and tracking dataset, an infrared image semantic segmentation dataset is annotated and constructed. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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Improve the robustness of algorithm under adversarial environment by moving target defense by Kang HE, Yuefei ZHU, Long LIU, Bin LU, Bin LIU

“…Traditional machine learning models works in peace environment,assuming that training data and test data share the same distribution.However,the hypothesis does not hold in areas like malicious document detection.The enemy attacks the classification algorithm by modifying the test samples so that the well-constructed malicious samples can escape the detection by machine learning models.To improve the security of machine learning algorithms,moving target defense (MTD) based method was proposed to enhance the robustness.Experimental results show that the proposed method could effectively resist the evasion attack to detection algorithm by dynamic transformation in the stages of algorithm model,feature selection and result output.…”
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Development and Validation of an Ultrasound Imaging Algorithm for Structured Reporting in Testicular Pathology by Roxana Pintican, Alexandru Negrea, Isabell Boll, Bianca Boca, Diana Gherman, Marilena Bora, Sorin Dudea, Anca Ciurea

“…<b>Conclusions</b>: This study shows that the proposed diagnostic algorithm is an effective tool for testicular US, facilitating accurate and reproducible assessments, which are crucial for early detection and optimal management of testicular pathologies.…”
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基于脑影像及临床特征的机器学习模型预测缺血性卒中后心房颤动 A Machine Learning Model Based on Brain Imaging and Clinical Features for Predicting Atrial Fibrillation Detected after Stroke... by 张栗源1，刘涛2，姜勇1，李子孝1，3，王拥军1，3，杨晓萌1，3(ZHANG Liyuan1, LIU Tao2, JIANG Yong1, LI Zixiao1,3, WANG Yongjun1,3, YANG Xiaomeng1,3 )

“…Using the LASSO algorithm for feature selection, 31 multimodal features (including 25 imaging and 6 clinical features) were obtained after screening, with an average AUC of 0.73 (95%CI 0.70-0.77). …”
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Identifying Irregular Potatoes by Developing an Intelligent Algorithm Based on Image Processing by Afshin Azızı, Yousef Abbaspour-gılandeh

“…The objective of this study was to develop an algorithm based on image processing for detecting misshapen potatoes from the mass of potatoes and obtaining homogeneous products. …”
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An experimental method for detecting objects in an aqueous environment by Kuzmin Yuri, Proshkin Stanislav

“…To facilitate this process, the researchers developed a specialized algorithm designed to filter out pulse and fluctuation interference. …”
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Deep Learning-Based Atmospheric Visibility Detection by Yawei Qu, Yuxin Fang, Shengxuan Ji, Cheng Yuan, Hao Wu, Shengbo Zhu, Haoran Qin, Fan Que

“…Traditional visibility detection methods, primarily manual and instrumental, have been costly and imprecise. …”
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Integrating Explanations into CNNs by Adopting Spiking Attention Block for Skin Cancer Detection by Inzamam Mashood Nasir, Sara Tehsin, Robertas Damaševičius, Rytis Maskeliūnas

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Presenting a Text Mining Algorithm to Identify Emotion in Persian Corpus by Masoud Garshasbi, Anahid Rais-Rohani, Mohammadreza Kabaranzadeh Ghadim

“…In the first approach, the algorithm is capable of detecting only one emotional word in a sentence, and then it improves to detect boosters and negating and stop word list as well. …”
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