A General Framework for CFAR Detection in PolSAR Imagery Based on Quadratic Statistics by Ziyuan Yang, Liguo Liu, Xiaoyang Hou, Yinghui Quan, Xian Zhang, Tao Liu

“…In the field of target detection in polarimetric synthetic aperture Radar (PolSAR) imagery, the constant false alarm rate (CFAR) algorithm is renowned for its operability and high interpretability. …”
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Machine Learning Model for Predicting Pathological Invasiveness of Pulmonary Ground‐Glass Nodules Based on AI‐Extracted Radiomic Features by Guozhen Yang, Yuanheng Huang, Huiguo Chen, Weibin Wu, Yonghui Wu, Kai Zhang, Xiaojun Li, Jiannan Xu, Jian Zhang

“…An independent cohort of 210 patients (118 with preinvasive lesions, 92 with IAC) from the Tianhe Campus served as external validation. Nineteen radiomic features were extracted and filtered using Boruta and LASSO algorithms. …”
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Research review on intelligent object detection technology for coal mines based on deep learning by Fan ZHANG, Jiarong ZHANG, Haixing CHENG

“…Firstly, a brief overview of object detection technology was provided, and the evolution process and algorithm classification of object detection technology based on deep learning were introduced. …”
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Detection of Water Content of Watermelon Seeds Based on Hyperspectral Reflection Combined with Transmission Imaging by Siyi Ouyang, Siwei Lv, Bin Li

“…The intermediate data fusion of the feature spectral data of reflectance and transmittance selected by the CARS algorithm improves the prediction effect of the model more obviously, in which the model with the best prediction accuracy is Raw-CRAS-LSSVR, whose <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msubsup><mi>R</mi><mi>P</mi><mn>2</mn></msubsup></semantics></math></inline-formula> and RMSEP are 0.9149 and 0.0144, respectively, which improves the prediction effect of the model built by a single full-spectrum datum by 5.72%. …”
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Abnormal sound detection method for coal mine belt conveyors based on convolutional autoencoder by SHEN Long, SHAN Haoran, PEI Wenliang, YANG Guixiang, WANG Yongli

“…Background noise in the signals was filtered using the WebRTC noise reduction algorithm, and Mel-Frequency Cepstral Coefficients (MFCC) were calculated from the denoised signals to obtain audio features of normal operation. …”
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TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection by Rijun Wang, Rijun Wang, Yesheng Chen, Fulong Liang, Xiangwei Mou, Xiangwei Mou, Guanghao Zhang, Hao Jin

“…Current tomato leaf disease detection methods, however, encounter challenges in extracting multi-scale features, identifying small targets, and mitigating complex background interference. …”
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Diagnostic accuracy of artificial intelligence for obstructive sleep apnea detection: a systematic review by Sara Haghighat, Muhammed Joghatayi, Julien Issa, Sarina Azimian, Janet Brinz, Ali Ashkan, Akhilanand Chaurasia, Zahra Rahimian, Linda Sangalli

“…Artificial intelligence (AI) algorithms can facilitate diagnosis by detecting patients’ signs and symptoms. …”
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Predictive analysis of clinical features for HPV status in oropharynx squamous cell carcinoma: A machine learning approach with explainability by Emily Diaz Badilla, Ignasi Cos, Claudio Sampieri, Berta Alegre, Isabel Vilaseca, Simone Balocco, Petia Radeva

“…This study aims to provide a comprehensive method based on pre-treatment clinical data for predicting the patient’s HPV status over a large OPSCC patient cohort and employing explainability techniques to interpret the significance and effects of the features. Materials and Methods:: We employed the RADCURE dataset clinical information to train six Machine Learning algorithms, evaluating them via cross-validation for grid search hyper-parameter tuning and feature selection as well as a final performance measurement on a 20% sample test set. …”
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L2R-MLP: a multilabel classification scheme for the detection of DNS tunneling by Emmanuel Oluwatobi Asani, Mojiire Oluwaseun Ayoola, Emmanuel Tunbosun Aderemi, Victoria Oluwaseyi Adedayo-Ajayi, Joyce A. Ayoola, Oluwatobi Noah Akande, Jide Kehinde Adeniyi, Oluwambo Tolulope Olowe

“…To address this issue, we propose a Lebesgue-2 regularized multilayer perceptron (L2R-MLP) algorithm for detecting DNS tunneling attacks. The DNS dataset was carefully curated from a publicly available repository, and relevant features, such as packet size and count, were selected using the recusive feature elimination technique. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. …”
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Detection of Apple Sucrose Concentration Based on Fluorescence Hyperspectral Image System and Machine Learning by Chunyi Zhan, Hongyi Mao, Rongsheng Fan, Tanggui He, Rui Qing, Wenliang Zhang, Yi Lin, Kunyu Li, Lei Wang, Tie’en Xia, Youli Wu, Zhiliang Kang

“…This study used FHIS combined with machine learning (ML) to predict SC at the apple’s equatorial position. Primary features were extracted using variable importance projection (VIP), the successive projection algorithm (SPA), and extreme gradient boosting (XGBoost). …”
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The diagnostic efficacy of seven autoantibodies in early detection of ground-glass nodular lung adenocarcinoma by Hua Guo, Wei Zhao, Chunsun Li, Zhen Wu, Ling Yu, Miaoyu Wang, Yuanhui Wei, Zirui Wang, Shangshu Liu, Yue Yin, Zhen Yang, Liangan Chen

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Fault Location on Radial Distribution Systems Using Wavelets and Artificial Neural Networks with a New Data Processing Feature by NERI Jr., A. L., MOREIRA, F. A., de SOUZA, B. A.

“…Using computational simulations, travelling waves theory, wavelet transform, a new data preprocessing feature, and artificial neural networks, this new algorithm tries to approximate the fault location using data provided by only one measurement point at the beginning of the feeder.…”
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Obstacle Feature Information-Based Motion Decision-Making Method for Obstacle-Crossing Motions in Lower Limb Exoskeleton Robots by Yuepeng Zhang, Guangzhong Cao, Jun Wu, Bo Gao, Linzhong Xia, Chen Lu, Hui Wang

“…A lower limb exoskeleton robot obstacle-crossing motion decision-making algorithm based on obstacle feature information is proposed by combining gait constraints and motion constraints, enabling it to select appropriate motion trajectories in the trajectory library. …”
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Optimized Demand Forecasting for Bike-Sharing Stations Through Multi-Method Fusion and Gated Graph Convolutional Neural Networks by Hebin Guo, Kexin Li, Yutong Rou

“…Additionally, user characteristics are included as node features, enabling a more comprehensive analysis. The study utilizes the 2020 dataset from Jersey City&#x2019;s bike-sharing system, starting with the application of the Isolation Forest algorithm to detect and filter anomalous data points. …”
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Application Research of Key Frames Extraction Technology Combined with Optimized Faster R-CNN Algorithm in Traffic Video Analysis by Zhi-guang Jiang, Xiao-tian Shi

“…On this basis, an improved algorithm for vehicle detection based on Faster R-CNN is proposed, and the Faster R-CNN network feature extraction layer is improved by using the principle of residual network, and a hole convolution is added to the network to filter out the redundant features of high-resolution video images to improve the problem of vehicle missed detection in the original algorithm. …”
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Lightweight Neural Network for Centroid Detection of Weak, Small Infrared Targets via Background Matching in Complex Scenes by Xiangdong Xu, Jiarong Wang, Zhichao Sha, Haitao Nie, Ming Zhu, Yu Nie

“…The network mainly consists of a local feature aggregation module (LFAM), which uses multiple-sized convolution kernels to capture multi-scale features in parallel and integrates multiple spatial attention mechanisms to achieve accurate feature fusion and effective background suppression, thereby enhancing the ability to detect small targets. …”
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Vehicle Motion State Prediction Method Integrating Point Cloud Time Series Multiview Features and Multitarget Interactive Information by Ruibin Zhang, Yingshi Guo, Yunze Long, Yang Zhou, Chunyan Jiang

“…A vehicle motion state prediction algorithm integrating point cloud timing multiview features and multitarget interaction information is proposed in this work to effectively predict the motion states of traffic participants around intelligent vehicles in complex scenes. …”
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Enabling Predication of the Deep Learning Algorithms for Low-Dose CT Scan Image Denoising Models: A Systematic Literature Review by Muhammad Zubair, Helmi B. Md Rais, Fasee Ullah, Qasem Al-Tashi, Muhammad Faheem, Arfat Ahmad Khan

“…Eliminating these noises and artifacts while preserving critical features poses a significant challenge. Traditional CT denoising algorithms struggle with edge blurring and high computational costs, often generating artifacts in flat regions as noise levels increase. …”
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Classification and Recognition of Soybean Quality Based on Hyperspectral Imaging and Random Forest Methods by Man Chen, Zhichang Chang, Chengqian Jin, Gong Cheng, Shiguo Wang, Youliang Ni

“…Eight preprocessing methods, including baseline correction (BC), moving average (MA), Savitzky–Golay derivative (SGD), normalization, standard normal variate transformation (SNV), multiplicative scatter correction (MSC), first derivative (DS), and Savitzky–Golay smoothing (SGS), were applied to the raw spectral data to eliminate irrelevant information. Feature wavelengths were selected using the successive projections algorithm (SPA) and the competitive adaptive reweighted sampling (CARS) algorithm to reduce spectral redundancy and enhance model detection performance, retaining eight and ten feature wavelengths, respectively. …”
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