CGDU-DETR: An End-to-End Detection Model for Ship Detection in Day–Night Transition Environments by Wei Wu, Xiyu Fan, Zhuhua Hu, Yaochi Zhao

“…To address the limitations of traditional methods in complex lighting conditions (e.g., strong reflections, low light), we designed a novel CG-Net model based on cascaded group attention and introduced a dynamic feature upsampling algorithm, effectively enhancing the model’s ability to extract multi-scale features and detect targets in complex backgrounds. …”
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A review of deep learning in blink detection by Jianbin Xiong, Weikun Dai, Qi Wang, Xiangjun Dong, Baoyu Ye, Jianxiang Yang

“…Compared with traditional methods, the blink detection method based on deep learning offers superior feature learning ability and higher detection accuracy. …”
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Fault Detection System of Photovoltaic Based on Artificial Neural Network by Ali Salman Zamzeer, Mansour S. Farhan, Haider TH. ALRikabi

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Cloud Detection in Remote Sensing Images Based on a Novel Adaptive Feature Aggregation Method by Wanting Zhou, Yan Mo, Qiaofeng Ou, Shaowei Bai

“…The HCAM extracts multi-scale features to enhance global representation while matching channel importance weights to focus on features that are more critical to the detection task. …”
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Enhanced Fall Detection and Prediction Using Heterogeneous Hidden Markov Models in Indoor Environment by Oumaima Guendoul, Hamd Ait Abdelali, Youness Tabii, Rachid Oulad Haj Thami, Omar Bourja

“…This study employs an Heterogenous Hidden Markov Model (HHMM) that utilizes 3D vision-based body articulation data to propose an innovative method for fall detection and prediction. To ensure the precision and reliability of our model, we preprocessed the data to eliminate noise and extract pertinent features. …”
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Enhanced intrusion detection model based on principal component analysis and variable ensemble machine learning algorithm by Ayuba John, Ismail Fauzi Bin Isnin, Syed Hamid Hussain Madni, Farkhana Binti Muchtar

“…First, PCA is combined with the AdaBoost ensemble machine learning algorithm, which acts as stagewise additive modelling to compensate for PCA's deficiency in feature selection in network traffic by minimizing the exponential loss function. …”
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Sea Clutter Suppression Method Based on Correlation Features by Zhen Li, Huafeng He, Liyuan Wang, Tao Zhou, Yizhe Sun, Yaomin He

“…Then, it uses these speckle components to derive the feature subspace of the sea clutter and applies this subspace in an orthogonal projection suppression algorithm, thereby achieving effective suppression of the sea clutter. …”
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Bird Species Detection Net: Bird Species Detection Based on the Extraction of Local Details and Global Information Using a Dual-Feature Mixer by Chaoyang Li, Zhipeng He, Kai Lu, Chaoyang Fang

“…Currently, most deep learning algorithms focus on designing local feature extraction modules while ignoring the importance of global information. …”
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Drunk Driver Detection Using Thermal Facial Images by Chin-Heng Chai, Siti Fatimah Abdul Razak, Sumendra Yogarayan, Ramesh Shanmugam

“…This study aims to investigate and propose a machine learning approach that can accurately detect alcohol consumption by analyzing the thermal patterns of facial features. …”
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GU-Net3+: A Global-Local Feature Fusion Algorithm for Building Extraction in Remote Sensing Images by Yali Liu, Cui Ni, Peng Wang, Dongqing Yang, Hexin Yuan, Chao Ma

“…In this study, we propose a building detection method that integrates global and local features. …”
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Dim and Small Target Detection Based on Local Feature Prior and Tensor Train Nuclear Norm by Anqing Wu, Xiangsuo Fan, Lei Min, Wenlin Qin, Ling Yu

“…When faced with complex scenes containing strong edge contours and noise, there are still more background residuals in the detection results of traditional algorithms, leading to a high false alarm rate. …”
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A complex roadside object detection model based on multi-scale feature pyramid network by Zhihao Zheng, Jianguang Zhao, Jingjing Fan, Ruirui Bai, Jiana Zhao, Jianan Liu

“…Combining the weighted Bi-directional Feature Pyramid Network (BCFPN) for feature fusion incorporates deep, shallow, and original features, reinforces feature integration, minimizes information loss during convolution processes, and enhances target detection accuracy. …”
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Infrared Small Target Detection Based on Compound Eye Structural Feature Weighting and Regularized Tensor by Linhan Li, Xiaoyu Wang, Shijing Hao, Yang Yu, Sili Gao, Juan Yue

“…Current single-aperture small target detection algorithms fail to exploit the spatial relationships among compound eye apertures, thereby underutilizing the inherent advantages of compound eye imaging systems. …”
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Research on Visual–Inertial Measurement Unit Fusion Simultaneous Localization and Mapping Algorithm for Complex Terrain in Open-Pit Mines by Yuanbin Xiao, Wubin Xu, Bing Li, Hanwen Zhang, Bo Xu, Weixin Zhou

“…It integrates an enhanced Line Segment Detection (LSD) algorithm with short segment culling and approximate line merging techniques. …”
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PFRNet: A Small Object Detection Method Based on Parallel Feature Extraction and Attention Mechanism by Hai Lin, Ji Wang, Jingguo Li

“…Results demonstrate that PFRNet achieves outstanding detection accuracy, markedly outperforming other algorithms, particularly in small object detection. …”
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Ground Segmentation Algorithm for Sloped Terrain and Sparse LiDAR Point Cloud by Victor Jimenez, Jorge Godoy, Antonio Artunedo, Jorge Villagra

“…Distinguishing obstacles from ground is an essential step for common perception tasks such as object detection-and-tracking or occupancy grid maps. Typical approaches rely on plane fitting or local geometric features, but their performance is reduced in situations with sloped terrain or sparse data. …”
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Malware Detection and Classification in Android Application Using Simhash-Based Feature Extraction and Machine Learning by Wafaa Al-Kahla, Eyad Taqieddin, Ahmed S. Shatnawi, Rami Al-Ouran

“…Then, we use Simhash to encode the selected parts of the analysis files to create feature vectors. These vectors are then used to train different Machine Learning algorithms for detecting and classifying malware. …”
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Singular Value Decomposition Based Features for Automatic Tumor Detection in Wireless Capsule Endoscopy Images by Vahid Faghih Dinevari, Ghader Karimian Khosroshahi, Mina Zolfy Lighvan

“…This method will utilize the advantages of the discrete wavelet transform (DWT) and singular value decomposition (SVD) algorithms to extract features from different color channels of the WCE images. …”
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Performance Analysis of Eye Movement Event Detection Neural Network Models with Different Feature Combinations by Birtukan Adamu Birawo, Pawel Kasprowski

“…Combining velocity and direction with acceleration and/or jerk demonstrated significant performance improvement compared to other feature combinations. The results show that the proposed method, using a combination of velocity and direction with acceleration and/or jerk, improves PSO identification performance, which has been difficult to distinguish from short saccades, fixations, and SPs using classic algorithms. …”
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A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization by Zeinab Hassani, vahid Hajihashemi, Keivan Borna, Iman Sahraei Dehmajnoonie

“…Nonetheless, in spam detection, there are a large number of features to attend as they play an essential role in detection efficiency. …”
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