Three Machine Learning Techniques for Melanoma Cancer Detection by Hadi Naghavipour, GholamReza Zandi, Abdulaziz Al-Nahari

“…This paper provides an open-source tutorial on the performance of an algorithm that helps to diagnose melanoma by extracting features from dermatoscopic images and their classification. …”
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Fire and Smoke Detection Based on Improved YOLOV11 by Zhipeng Xue, Lingyun Kong, Haiyang Wu, Jiale Chen

“…Traditional object detection methods rely more on manually designed features and rules. …”
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XFP-recognizer: detecting cross-file browser fingerprinting by Xiaoxi Wang, Zhenxu Liu, Chunyang Zheng, Xinyu Liu, Wei Liu, Yuling Liu, Qixu Liu

“…The dispersion of files and features in XFP effectively circumvents detection methods that primarily focus on single-file tracking. …”
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An Unsupervised Moving Object Detection Network for UAV Videos by Xuxiang Fan, Gongjian Wen, Zhinan Gao, Junlong Chen, Haojun Jian

“…UAV moving object detection focuses on identifying moving objects in images captured by UAVs, with broad applications in regional surveillance and event reconnaissance. …”
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Risk averse reproduction numbers improve resurgence detection. by Kris V Parag, Uri Obolski

“…Applying E-optimal experimental design theory, we develop a weighting algorithm to minimise these issues, yielding the risk averse reproduction number E. …”
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Generic, scalable and decentralized fault detection for robot swarms. by Danesh Tarapore, Anders Lyhne Christensen, Jon Timmis

“…Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. …”
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Toward Salient Key Phrase for Candidate Topic Detection by Yasser S. Jude, Wafaa Al-Hameed

“…These results highlight the algorithm's ability to extract relevant information from text documents.…”
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Neural models for detection and classification of brain states and transitions by Arnau Marin-Llobet, Arnau Manasanch, Leonardo Dalla Porta, Melody Torao-Angosto, Maria V. Sanchez-Vives

“…Here we introduce a pipeline to detect brain states and their transitions in the cerebral cortex using a dual-model Convolutional Neural Network (CNN) and a self-supervised autoencoder-based multimodal clustering algorithm. …”
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A novel EEG artifact removal algorithm based on an advanced attention mechanism by Rui Jiang, Shen Tong, Jiawei Wu, Haowei Hu, Ran Zhang, Heng Wang, Yan Zhao, Weixin Zhu, Shuyan Li, Xiao Zhang

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Multipath Suppression and High-precision Angle Measurement Method Based on Feature Game Preprocessing by Houhong XIANG, Yongliang WANG, Yuxi LI, Yufeng CHEN, Fengyu WANG, Xiaolu ZENG

“…The meter-wave radar, known for its wide beamwidth, often faces challenges in detecting low-elevation targets due to interference from multipath signals. …”
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Human Pose Estimation and Event Recognition via Feature Extraction and Neuro-Fuzzy Classifier by Muhammad Hanzla, Naif S. Alshammari, Shuaa S. Alharbi, Wasim Wahid, Nouf Abdullah Almujally, Ahmad Jalal, Hui Liu

“…Key point features are characterized through the degree of freedom, human landmark detection via the HSV algorithm, and angular point analysis using the media pipe algorithm. …”
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ML-Based Quantitative Analysis of Linguistic and Speech Features Relevant in Predicting Alzheimer’s Disease by Tripti Tripathi, Rakesh Kumar

“…The method employs speech data from DementiaBank’s Pitt Corpus, which is preprocessed and analyzed to extract pertinent acoustic features. The characteristics are subsequently used to educate five machine learning algorithms, namely k-nearest neighbors (KNN), decision tree (DT), support vector machine (SVM), XGBoost, and random forest (RF). …”
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Enhanced Atrous Spatial Pyramid Pooling Feature Fusion for Small Ship Instance Segmentation by Rabi Sharma, Muhammad Saqib, C. T. Lin, Michael Blumenstein

“…However, existing instance segmentation algorithms do not detect and segment them, resulting in inaccurate ship segmentation. …”
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Research on feature extraction and intelligent diagnosis method of reciprocating compressor bearing clearance fault by Feng Yan

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Feature Selection for Hypertension Risk Prediction Using XGBoost on Single Nucleotide Polymorphism Data by Lailil Muflikhah, Tirana Noor Fatyanosa, Nashi Widodo, Rizal Setya Perdana, Solimun, Hana Ratnawati

“…This study aims to develop a feature selection model using the XGBoost algorithm to identify specific single nucleotide polymorphisms (SNPs) as biomarkers for detecting hypertension risk. …”
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Frequency hopping modulation recognition based on time-frequency energy spectrum texture feature by Hongguang LI, Ying GUO, Ping SUI, Zisen QI

“…For frequency hopping modulation identification,a novel method based on time-frequency energy spectrum texture feature was proposed.Firstly,the time-frequency diagram of the frequency hopping signal was obtained by smoothed pseudo Wigner-Ville distribution,and the background noise of the time-frequency diagram was removed by two-dimensional Wiener filtering to improve the resolution of the time-frequency diagram under low SNR conditions.Then,the connected-domain detection algorithm was used to extract the time-frequency energy spectrum of each hop signal and convert it into a time-frequency gray-scale image.The histogram statistical features and the gray-scale co-occurrence matrix feature were combined to form a 22-dimensional eigenvector.Finally,the feature set was trained,classified and identified by optimized support vector machine classifier.Simulation experiments show that the multi-dimensional feature vector extracted by the algorithm has strong representation ability and avoids the misjudgment caused by the similarity of single features.The average recognition accuracy of the six modulation methods of frequency hopping signals BPSK,QPSK,SDPSK,QASK,64QAM and GMSK is 91.4% under the condition of -4 dB SNR.…”
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Feature-Based Classification of Amino Acid Substitutions outside Conserved Functional Protein Domains by Branislava Gemovic, Vladimir Perovic, Sanja Glisic, Nevena Veljkovic

“…There are more than 500 amino acid substitutions in each human genome, and bioinformatics tools irreplaceably contribute to determination of their functional effects. We have developed feature-based algorithm for the detection of mutations outside conserved functional domains (CFDs) and compared its classification efficacy with the most commonly used phylogeny-based tools, PolyPhen-2 and SIFT. …”
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Anxiety Detection System Based on Galvanic Skin Response Signals by Abeer Al-Nafjan, Mashael Aldayel

“…The KNN algorithm achieved the highest accuracy in both the statistical and automatic feature extraction approaches, with results of 96.9% and 98.2%, respectively. …”
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TBM Enclosure Rock Grade Prediction Method Based on Multi-Source Feature Fusion by Yong Huang, Xiewen Hu, Shilong Pang, Wei Fu, Shuaipeng Chang, Bin Gao, Weihua Hua

“…Aiming to mitigate engineering risks such as tunnel face collapse and equipment jamming caused by poor geological conditions during the construction of tunnel boring machines (TBMs), this study proposes a TBM surrounding rock grade prediction method based on multi-source feature fusion. Firstly, a multi-source dataset is established by systematically integrating TBM tunnelling parameters, horizontal acoustic profile (HSP) detection data and three-dimensional geological spatial information. …”
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Weighted Hybrid Random Forest Model for Significant Feature prediction in Alzheimer’s Disease Stages by M. Rohini, D. Surendran

“…As a consequence of this challenge discussed, whether all the mild cognitively impaired people change to AD cohorts or remain in normal cognition and identification of the structural and functional features remains underexplored. Thus, the proposed Weighted Hybrid Random Forest algorithm (WHBM) utilized the 63 features that comprise the whole brain volume. …”
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