Multimodal Data Fusion for Precise Lettuce Phenotype Estimation Using Deep Learning Algorithms by Lixin Hou, Yuxia Zhu, Mengke Wang, Ning Wei, Jiachi Dong, Yaodong Tao, Jing Zhou, Jian Zhang

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Robust outdoor trajectory mapping using CNN features and loop closure optimization by Kamran Kazi, Arbab Nighat Kalhoro, Farida Memon, Tarique Rafique Memon, Azam Rafique Memon

“…This paper introduces a robust framework for outdoor trajectory mapping that synergizes deep learning-based feature extraction with loop closure detection and optimization to address these limitations. …”
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Predictive modeling for rework detection in sustainable building projects by AbdulLateef Olanrewaju, Kafayat Shobowale

“…The dataset consisted of 75 responses, with 17 rework predictors. Feature scaling and normalisation were performed across the dataset to standardise the features. …”
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Crop row centerline extraction method based on regional feature point clustering by Baofeng Ji, Hang Wang, Chunhong Dong, Song Chen, Hongtao Chen, Fazhan Tao, Ji Zhang, Huitao Fan

“…Next, Harris corner detection technology is used to extract crop feature points, and these feature points are clustered using the DBSCAN algorithm, marking each crop row with a different color. …”
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Evaluation of different spectral indices for wheat lodging assessment using machine learning algorithms by Shikha Sharda, Sumit Kumar, Raj Setia, Prince Dhiman, N. R. Patel, Brijendra Pateriya, Ali Salem, Ahmed Elbeltagi

“…This study presented a systematic approach for detecting the wheat lodging occurred during the end of March and April 2023 in the Ludhiana district of Punjab (India) from multi-temporal Sentinel-2 data using the machine learning algorithms. …”
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On the effect of sampling frequency on the electricity theft detection performance by Fatemeh Soleimani Nasab, Foad Ghaderi

“…However, based on technological and operational limitations, the rate of metre reading is too low in many countries, which can affect detection performance. To investigate the effect of sampling frequency on the performance of detection methods, we designed a processing framework to evaluate different classification algorithms on versions of a challenging dataset obtained by down‐sampling the original data at various rates. …”
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A New Approach for Clustered MCs Classification with Sparse Features Learning and TWSVM by Xin-Sheng Zhang

“…Then we designed the sparse feature learning based MCs classification algorithm using twin support vector machines (TWSVMs). …”
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Detecting Textual Propaganda Using Machine Learning Techniques by Akib Mohi Ud Din Khanday, Qamar Rayees Khan, Syed Tanzeel Rabani

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Concrete Crack Skeleton Analysis: A Machine Vision Approach to Feature Extraction by Rui Wang, Xinxin Guo, Jiaxuan Liu, Yu Wan

“…The crack feature is the key to crack recognition in concrete surface crack detection systems based on machine vision. …”
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Automatic Fall Risk Detection Based on Imbalanced Data by Yen-Hung Liu, Patrick C. K. Hung, Farkhund Iqbal, Benjamin C. M. Fung

“…In this paper, we propose a pose estimation-based fall detection algorithm to detect fall risks. We use body ratio, acceleration and deflection as key features instead of using the body keypoints coordinates. …”
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Effects of data transformation and model selection on feature importance in microbiome classification data by Zuzanna Karwowska, Oliver Aasmets, Estonian Biobank research team, Tomasz Kosciolek, Elin Org

“…However, while different transformations resulted in comparable classification performance, the most important features varied significantly, which highlights the need to reevaluate machine learning–based biomarker detection. …”
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Image Processing Using Feature-Based Segmentation Techniques for the Analysis of Medical Images by Christodoss Prasanna Ranjith, Krishnamoorthy Natarajan, Sindhu Madhuri, Mahesh Thylore Ramakrishna, Chandrasekhar Rohith Bhat, Vinoth Kumar Venkatesan

“…Unlike classic K-means, which requires you to choose the number of clusters before executing the algorithm, adaptive K-means identifies the best number of clusters based on the features of the data. …”
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Prediabetes detection in unconstrained conditions using wearable sensors by Dimitra Tatli, Vasileios Papapanagiotou, Aris Liakos, Apostolos Tsapas, Anastasios Delopoulos

“…Future directions involve expanding the study to a larger, more diverse population and exploring the integration of CGM and smartwatch functionalities into a unified device. Automated eating detecting algorithms can also be used.…”
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GE-YOLO for Weed Detection in Rice Paddy Fields by Zimeng Chen, Baifan Chen, Yi Huang, Zeshun Zhou

“…It introduces the Neck network with the Gold-YOLO feature aggregation and distribution network to enhance the network’s ability to fuse multi-scale features and detect weeds of different sizes. …”
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A Deep Learning Method for Automatic Coronal Mass Ejection Feature Identification by P. Yang, H. S. Fu, J. B. Cao, F. Shen

“…As space activities become increasingly frequent and infrastructure more reliant on space-based systems, the rapid and accurate detection and tracking of CMEs is critical. Here, we present a deep learning–based algorithm for automated CME feature extraction, comprising four key stages: image preprocessing, segmentation, tracking, and feature extraction. …”
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THE METHOD OF ADAPTIVE STATISTICAL CODING TAKING INTO ACCOUNT THE STRUCTURAL FEATURES OF VIDEO IMAGES by Volodymyr Barannik, Dmytro Havrylov, Serhii Pantas, Yurii Tsimura, Tatayna Belikova, Rimma Viedienieva, Vasyl Kryshtal

“…The technology is based on the detection of key information at several stages of video data processing. …”
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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…The results of these tests will help researchers make decisions and early detection, effectively defense against malware. This work compares and reports a classification of malware detection work based on deep learning algorithms. …”
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Deep Belief Network-Based Multifeature Fusion Music Classification Algorithm and Simulation by Tianzhuo Gong

“…In this paper, the multifeature fusion music classification algorithm and its simulation results are studied by deep confidence networks, the multifeature fusion music database is established and preprocessed, and then features are extracted. …”
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Keypoint Detection Based on Curvature Grouping and Adaptive Sampling by Bifu Li, Yu Cheng, Weitong Li

“…In the keypoint detection algorithm, the farthest point sampling methods and random sampling methods are usually used to select candidate points, then keypoints are screened out from the neighborhood of the candidate points. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…A key innovation of this study is the development of an algorithm that processes low-amplitude high-frequency signals, which are often difficult to detect with conventional methods. …”
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