Prediction of bone oligometastases in breast cancer using models based on deep learning radiomics of PET/CT imaging by Guoxiu Lu, Guoxiu Lu, Ronghui Tian, Wei Yang, Jiayi Zhao, Wenjing Chen, Zijie Xiang, Shanhu Hao, Guoxu Zhang

“…Radiomic features were extracted from computed tomography (CT), positron emission tomography (PET), and fused PET/CT images using PyRadiomics embedded in the uAI Research Portal. …”
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Flood Image Classification using Convolutional Neural Networks by Olusogo Julius Adetunji, Ibrahim Adepoju Adeyanju, Adebimpe Omolayo Esan, Adedayo Aladejobi Sobowale Sobowale

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AE-XGBoost: A Novel Approach for Machine Tool Machining Size Prediction Combining XGBoost, AE and SHAP by Mu Gu, Shuimiao Kang, Zishuo Xu, Lin Lin, Zhihui Zhang

“…In this study, XGBoost was used to establish an evaluation system for the actual machining size of computer numerical control (CNC) machine tools. The XGBoost model was combined with SHAP approximation to effectively capture local and global features in the data using autoencoders and transform the preprocessed data into more representative feature vectors. …”
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Hysteresis and Eddy Currents Effects Simulation in Idling Mode of the Transformer by Yarymbash D.S., Kotsur M.I., Yarymbash S.T., Divchuk T.Ye.

“…Therefore, the aim of the work is to develop interconnected circuit and field models that ensure high accuracy of idling parameters by allow for the parameters of the external network, transformer design features and nonlinear magnetic properties of electrical steel, asymmetry and non-sinusoidal idling currents. …”
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Variational autoencoder-based multipath clustering algorithm for terahertz channels by HAO Xinyu, LIAO Xi, ZHENG Xiangquan, WANG Yang, LIN Feng, CHEN Qianbin, ZHANG Jie

“…To address the shortcomings of multipath clustering algorithms in terahertz channel modeling, particularly in terms of multidimensional parameter adaptability and unsupervised feature separation, a variational autoencoder-based latent space multipath clustering (VAE-LMC) model was proposed. …”
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Shape factor analysis of water and aluminium oxide nanoparticles in a porous medium with slip effects by Prasun Choudhary, K. Loganathan, Kavita Jat, Kalpna Sharma, S. Eswaramoorthi

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Laser_RobMap: An open source ROS2 compatible tool for 3D mapping using a Mobile Robot and 2D LiDAR by Daniel D. Yanyachi, Yamir H. Anco-Agüero, German A. Echaiz, Miguel A. Esquivel, Alfredo Mamani-Saico, Pablo R. Yanyachi

“…The tool adapts to any ROS2-enabled robot that provides inertial and odometry data, with configurable parameters to optimize performance on systems with limited computational resources. …”
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TransferBAN-Syn: a transfer learning-based algorithm for predicting synergistic drug combinations against echinococcosis by Haitao Li, Haitao Li, Yuanyuan Chu, Yuanyuan Chu, Liyuan Jiang, Liyuan Jiang, Lei Li, Lei Li, GuoDong Lv, Yuansheng Liu, Chunhou Zheng, Chunhou Zheng, Yansen Su, Yansen Su

“…TransferBAN-Syn is designed and initially trained on the abundant data from the 21 parasitic diseases, which serves as the source domain. The parameters in the feature representation modules of drug interactions and diseases are preserved from this source domain, and those in the prediction module are then fine-tuned to specifically identify the synergistic drug combinations for echinococcosis in the target domain. …”
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The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis by Zeyu Chen, Zheng Lin, Zihan Lin, Qi Zhang, Haoyun Zhang, Haiwen Li, Qing Chang, Jianqi Sun, Feng Li

“…Recently, several studies attempted to build prognostic models by extracting predictive variates from pulmonary function data, basic information, or chest computed tomography (CT) and CT-derived parameters with clinical characteristics. …”
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Supervised and unsupervised machine learning approaches for prediction and geographical discrimination of Iranian saffron ecotypes based on flower-related and phytochemical attribu... by Seid Mohammad Alavi-Siney, Jalal Saba, Alireza Fotuhi Siahpirani, Jaber Nasiri

“…Based on the results of Leave-One-Out Cross-Validation (LOOCV), various prediction values were computed for all 10 classifiers of LDA, QDA, FDA, MDA, RDA, Naive Bayes, Decision Tree, Linear SVM, Radial SVM, and Random Forest in terms of accuracy, sensitivity and specificity parameters. …”
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An automatic modulation recognition network based on multi-channel lightweighting by WAN Jinhua, SHANG Junna, ZHANG Huadi

“…This shows that MCLMR not only has a small number of parameters and low computational complexity, but also has excellent performance in recognition accuracy.…”
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Deep Learning-Based Infrared Image Segmentation for Aircraft Honeycomb Water Ingress Detection by Hang Fei, Hongfu Zuo, Han Wang, Yan Liu, Zhenzhen Liu, Xin Li

“…The demonstrated reductions in computational effort and parameter count underscore the model’s efficiency, fortifying its relevance in broader contexts.…”
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A Novel Hypersonic Target Trajectory Estimation Method Based on Long Short-Term Memory and a Multi-Head Attention Mechanism by Yue Xu, Quan Pan, Zengfu Wang, Baoquan Hu

“…In model training, information redundancy is reduced, and information validity is improved through feature selection and data preprocessing. Eventually, the model achieves accurate prediction of hypersonic target trajectories with limited computational resources. …”
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Robust Automatic Modulation Classification via a Lightweight Temporal Hybrid Neural Network by Zhao Wang, Weixiong Zhang, Zhitao Zhao, Ping Tang, Zheng Zhang

“…However, existing networks face challenges in robustness against signals containing phase shift keying and computational efficiency. This paper introduces TCN-GRU, a lightweight model that combines the advantages of multiscale feature extraction of the temporal convolutional network (TCN) and global sequence modeling of gated recurrent unit (GRU). …”
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Multiple Chaos Synchronization System for Power Quality Classification in a Power System by Cong-Hui Huang, Chia-Hung Lin

“…The proposed method can adapt itself without the need for adjustment of parameters or iterative computation. For a sample power system, the test results showed accurate discrimination, good robustness, and faster processing time for the detection of PQ disturbances.…”
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Football sports video tracking and detection technology based on YOLOv5 and DeepSORT by Bin Wang

“…The outcomes indicated that the average accuracy value of the improved YOLOv5 model for target detection was more than 90%, which effectively reduced the number of computational parameters. The detection performance under target overlap and uneven lighting and shadows exceeded 90%, and the difference between the algorithm and other algorithms was at least greater than 2%. …”
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Urban Traffic State Estimation with Online Car-Hailing Data: A Dynamic Tensor-Based Bayesian Probabilistic Decomposition Approach by Wenqi Lu, Ziwei Yi, Dongyu Luo, Yikang Rui, Bin Ran, Jianqing Wu, Tao Li

“…However, most of the advanced studies focus on building complex deep learning structures to learn the spatiotemporal feature of the urban traffic flow, ignoring improving the efficiency of the traffic state estimation. …”
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Sparse Deep Neural Network for Encoding and Decoding the Structural Connectome by Satya P. Singh, Sukrit Gupta, Jagath C. Rajapakse

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A Lightweight Cotton Field Weed Detection Model Enhanced with EfficientNet and Attention Mechanisms by Lu Zheng, Lyujia Long, Chengao Zhu, Mengmeng Jia, Pingting Chen, Jun Tie

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Binocular stereo vision-based relative positioning algorithm for drone swarm by Qing Cheng, Yazhe Wang

“…Finally, the extracted feature points from UAVs are input into a binocular vision localization model to compute their three-dimensional coordinates. …”
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