Exploring unsupervised feature extraction algorithms: tackling high dimensionality in small datasets by Hongqi Niu, Gabrielle B. McCallum, Anne B. Chang, Khalid Khan, Sami Azam

“…Furthermore, we compared these algorithms in terms of transformation approach, goals, parameters, and computational complexity. Finally, we evaluated each algorithm against state-of-the-art research using various datasets to assess their accuracy, highlighting which algorithm is most appropriate for specific scenarios. …”
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Partial feature reparameterization and shallow-level interaction for remote sensing object detection by Minh Tai Pham Nguyen, Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Minh Khue Phan Tran, Tadashi Nakano, Thi Hong Tran

“…Firstly, an extraction block is proposed called PRepConvBlock that leverages reparameterization convolution and partial feature utilization to effectively reduce the complexity in convolution operations, allowing for the utilization of larger kernel sizes in order to form the longer interactions between features and significantly expand receptive fields. …”
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A Reparameterization Feature Redundancy Extract Network for Unmanned Aerial Vehicles Detection by Shijie Zhang, Xu Yang, Chao Geng, Xinyang Li

“…This module generates more feature maps with fewer parameters. Additionally, we introduce reparameterization techniques to compensate for potential feature loss while further improving the model’s inference speed. …”
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FGBNet: A Bio-Subspecies Classification Network with Multi-Level Feature Interaction by Yang Yuan, Danping Huang, Bingbin Cai, Yang Shen, Jingdan Wang, Jiale Xv, Siyu Chen

“…Through experimentation and optimization, the ConvNeXt is selected as the backbone network for FGBNet feature extraction, and the effectiveness of the multi-level feature interaction method is verified. …”
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Application of Fast Kurtosis Spectrum in Fault Feature Extraction of Compound Planetary Gear by Wu Shoujun Feng Fuzhou Wu Chunzhi Ding Chuang

“…Fast kurtosis specturm has fast detection ability for transient impulse signal and is widely used in fault feature extraction of rotating machinery. A process of extracting mechanical fault feature based on fast computation of kurtogram is proposed and which is applied to the fault feature extraction of composite planetary gears of a tank gearbox. …”
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Breast Cancer Diagnosis Using Bagging Decision Trees with Improved Feature Selection by Deepak Dudeja, Ajit Noonia, S. Lavanya, Vandana Sharma, Varun Kumar, Sumaiya Rehan, R. Ramkumar

“…The random forest method used bagging techniques for selecting data points, and feature optimization was also carried out. Through our experiments, it has been found that the results obtained with the bagging trees algorithm outperform the result obtained with the best decision tree parameters. …”
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Visual Object Tracking in RGB-D Data via Genetic Feature Learning by Ming-xin Jiang, Xian-xian Luo, Tao Hai, Hai-yan Wang, Song Yang, Ahmed N. Abdalla

“…Visual object tracking is a fundamental component in many computer vision applications. Extracting robust features of object is one of the most important steps in tracking. …”
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Perceptual Quality Assessment for Pansharpened Images Based on Deep Feature Similarity Measure by Zhenhua Zhang, Shenfu Zhang, Xiangchao Meng, Liang Chen, Feng Shao

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Machine Learning-Driven Acoustic Feature Classification and Pronunciation Assessment for Mandarin Learners by Gulnur Arkin, Tangnur Abdukelim, Hankiz Yilahun, Askar Hamdulla

“…Based on acoustic feature analysis, this study systematically examines the differences in vowel pronunciation characteristics among Mandarin learners at various proficiency levels. …”
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Optimal Statistical Feature Subset Selection for Bearing Fault Detection and Severity Estimation by Chhaya Grover, Neelam Turk

“…The performance of bearing fault detection systems based on machine learning techniques largely depends on the selected features. Hence, selection of an ideal number of dominant features from a comprehensive list of features is needed to decrease the number of computations involved in fault detection. …”
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Feature fusion based deep learning model for Alzheimer's neurological disorder classification by Arhath Kumar, S. Pradeep, Kumud Arora, G. Sreeram, A. Pankajam, Trupti Patil, Aradhana Sahu

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Multimodal Feature-Driven Deep Learning for the Prediction of Duck Body Dimensions and Weight by Wenbo Xiao, Qiannan Han, Gang Shu, Guiping Liang, Hongyan Zhang, Song Wang, Zhihao Xu, Weican Wan, Chuang Li, Guitao Jiang, Yi Xiao

“…The proposed method innovatively employs PointNet++ to extract key feature points from point clouds, extracts and computes corresponding 3D geometric features, and fuses them with multi-view convolutional 2D features. …”
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Autism Spectrum disorder Detection in Toddlers and Adults Using Deep Learning by Abbas Sidra, Ojo Stephen, Krichen Moez, Alamro Meznah A., Mihoub Alaeddine, Vilcekova Lucia

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Optical wave features and sensitivity analysis of a coupled fractional integrable system by Jan Muhammad, Usman Younas, D.K. Almutairi, Aziz Khan, Thabet Abdeljawad

“…In addition, a variety of plots demonstrating the effect of fractional derivatives are provided to observe the physical behavior of the derived solutions by the assistance of the parameters. The outcomes obtained indicate that the implemented computational strategies are proficient, succinct, effective and they can be combined with representative computations to tackle more intricate phenomena.…”
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Implementation features of the third-party DLL connection mechanism in the information system «Channel» by Nadezhda S. Mogilevskaya, Konstantin A. Chugunniy

“…The system “Channel” allows simulating the noise-immune digital communication channels and solving the problem of matching the communication channel and the algebraic method of the jamproof protection of this channel. The main feature of the system is that it can be used not only by the researchers who do not have programming skills, but also by experts in the computing aids programming. …”
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Reminder and Online Booking Features at Android-Based Motorcycle Repair Shop Marketplace by Wayan Dony Mahendra, I Made Sukarsa, AA.Kt. Agung Cahyawan

“…The results of the UAT test (user acceptance testing) from 20 users show 55,8% answered agree to the display, features and flow of the system, 39,5% answered strongly agree to the three question parameters, and 4,7% answered disagree with the flow and display of the system.…”
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A triple-mode bandpass filter featured with hybrid integration and tiny size by Ma Hanyang, Zhou Yujin, Zhou Jun

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Online LiDAR-Camera Extrinsic Calibration Using Selected Semantic Features by Ping-Tzu Lin, Ying-Shiuan Huang, Wen-Chieh Lin, Chieh-Chih Wang, Huei-Yung Lin

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Soybean Weed Detection Based on RT-DETR with Enhanced Multiscale Channel Features by Hua Yang, Yanjie Lyu, Yunpeng Jiang, Feng Jiang, Taiyong Deng, Lihao Yu, Yuanhao Qiu, Hao Xue, Junying Guo, Zhaoqi Meng

“…To solve the missed and wrong detection problems of the object detection model in identifying soybean companion weeds, this paper proposes an enhanced multi-scale channel feature model based on RT-DETR (EMCF-RTDETR). First, we designed a lightweight hybrid-channel feature extraction backbone network, which consists of a CGF-Block module and a FasterNet-Block module working together, aiming to reduce the amount of computation and the number of parameters while improving the efficiency of feature extraction. …”
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Impacts of oxytactic microorganisms and viscous dissipation in Carreau nanoliquid featuring ferromagnetic nanoparticles by Muhammad Tabrez, I. Hussain, W.A. Khan, S.U. Khan, M. Waqas, Rzgar Farooq Rashid, M.I. Anwar, Mohamed Ben Ammar, Nurnadiah Zamri, Ruzimurod Abiyev, Hakim AL Garalleh

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