Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring by Ruipu Ji, Shokrullah Sorosh, Eric Lo, Tanner J. Norton, John W. Driscoll, Falko Kuester, Andre R. Barbosa, Barbara G. Simpson, Tara C. Hutchinson

“…A feature point tracking-based algorithm for square checkerboard patterns and a Hough Transform-based algorithm for concentric circular patterns are developed to ensure reliable detection and tracking of image features. …”
Get full text

Pulmonary hemorrhage in oncologic patients – a diagnostic algorithm by R. S. Kiselev, E. A. Tarabrin, Z. G. Berikkhanov, V. A. Savelieva, Yu. V. Kutilin, M. Yu. Ivanova

“…It is necessary to conduct multicenter studies in order to develop and implement a unified algorithm assessing all etiopathogenetic features of pulmonary hemorrhage in oncologic patients.…”
Get full text

Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method by Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou

“…In the fiber position detection system, after the fiber view camera (FVC) detects the positions of the light spots from the robotic fiber positioners (RFPs), these positions must be mapped to the RFPs individually to complete subsequent calculations of their operational data. …”
Get full text

Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

“…Multi-feature-based maritime radar target detection algorithms often rely on statistical models to accurately characterize sea clutter variations. …”
Get full text

Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu, Baijuan Wang

“…The network leverages Space-to-Depth Convolution to enhance its capability in detecting small insect targets. The Convolutional Block Attention Module is employed to improve feature representation and attention focus. …”
Get full text

On-line Identification Method of Pantograph Anomaly Based on Feature Analysis by WANG Junping, MAO Huihua, SHEN Yunbo, LI Miaocheng, CHEN Xin'an

“…There are three common inspection methods, including manual visual inspection, fixed-point image detection and on-board image detection. Due to the small number of pantograph fault samples that can be obtained, the present pantograph anomaly identification algorithms based on deep learning perform poorly. …”
Get full text

Does the FARNet neural network algorithm accurately identify Posteroanterior cephalometric landmarks? by Merve Gonca, İbrahim Şevki Bayrakdar, Özer Çelik

“…Abstract Background We explored whether the feature aggregation and refinement network (FARNet) algorithm accurately identified posteroanterior (PA) cephalometric landmarks. …”
Get full text

A New Approach Based on Metaheuristic Optimization Using Chaotic Functional Connectivity Matrices and Fractal Dimension Analysis for AI-Driven Detection of Orthodontic Growth and D... by Orhan Cicek, Yusuf Bahri Özçelik, Aytaç Altan

“…To effectively model the nonlinear dynamics, chaotic maps were generated, representing a significant advance over traditional methods. Feature selection was performed using a wrapper-based approach combining k-nearest neighbors (kNN) and the Puma optimization algorithm, which efficiently handles the chaotic and computationally complex nature of cervical vertebrae images. …”
Get full text

Generating Deeply-Engineered Technical Features for Basketball Video Understanding by Shaohua Fang, Guifeng Wang, Yongbin Li, Yue Yu, Jun Li

“…Our main contributions include: 1) an LSTM-based deep learning architecture for player action recognition and prediction; 2) a clustering-based algorithm for basketball court and line detection; and 3) a keyframe selection technique for basketball videos based on spatial-temporal scoring. …”
Get full text

Random Oversampling-Based Diabetes Classification via Machine Learning Algorithms by G. R. Ashisha, X. Anitha Mary, E. Grace Mary Kanaga, J. Andrew, R. Jennifer Eunice

“…The proposed model consists of the random oversampling method to balance the range of classes, the interquartile range technique-based outlier detection to eliminate outlier data, and the Boruta algorithm for selecting the optimal features from the datasets. …”
Get full text

Classification of Lung Nodule Using Hybridized Deep Feature Technique by Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham

“…The hybridization has been carried out between handcrafted features and deep features. The machine learning algorithms such as SVM and Logistic Regression have been used to classify the nodules based on the features. …”
Get full text

Explainability Feature Bands Adaptive Selection for Hyperspectral Image Classification by Jirui Liu, Jinhui Lan, Yiliang Zeng, Wei Luo, Zhixuan Zhuang, Jinlin Zou

“…Hyperspectral remote sensing images are widely used in resource exploration, urban planning, natural disaster assessment, and feature classification. Aiming at the problems of poor interpretability of feature classification algorithms for hyperspectral images, multiple feature dimensions, and difficulty in effectively improving classification accuracy, this paper proposes a feature band adaptive selection method for hyperspectral images. …”
Get full text

RGB-T Object Detection With Failure Scenarios by Qingwang Wang, Yuxuan Sun, Yongke Chi, Tao Shen

“…Currently, RGB-thermal (RGB-T) object detection algorithms have demonstrated excellent performance, but issues such as modality failure caused by fog, strong light, sensor damage, and other conditions can significantly impact the detector's performance. …”
Get full text

Fish Detection Using Deep Learning by Suxia Cui, Yu Zhou, Yonghui Wang, Lujun Zhai

“…An advanced system with more computing power can facilitate deep learning feature, which exploit many neural network algorithms to simulate human brains. …”
Get full text

Hybrid machine learning algorithms accurately predict marine ecological communities by Luciana Erika Yaginuma, Luciana Erika Yaginuma, Fabiane Gallucci, Danilo Cândido Vieira, Paula Foltran Gheller, Simone Brito de Jesus, Thais Navajas Corbisier, Gustavo Fonseca

“…In the supervised stage, these associations were modeled as a function of the environmental features by five supervised algorithms (Support Vector Machine, Random Forest, k-Nearest Neighbors, Naive Bayes, and Stochastic Gradient Boosting), using 80% of the samples for training, leaving the remaining for testing. …”
Get full text

Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities by Nourhan Zayed, Heba A. Elnemr

“…In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others.…”
Get full text

Breast lesion detection through MammoWave device: Empirical detection capability assessment of microwave images' parameters. by Lorenzo Sani, Alessandro Vispa, Riccardo Loretoni, Michele Duranti, Navid Ghavami, Daniel Alvarez Sánchez-Bayuela, Stefano Caschera, Martina Paoli, Alessandra Bigotti, Mario Badia, Michele Scorsipa, Giovanni Raspa, Mohammad Ghavami, Gianluigi Tiberi

“…In this paper, we propose to generate, for each breast, a set of conductivity weighted microwave images by using different values of conductivity in the Huygens Principle imaging algorithm. Next, microwave images' parameters, i.e. features, are introduced to quantify the non-homogenous behaviour of the image. …”
Get full text

Feature Point Extraction from the Local Frequency Map of an Image by Jesmin Khan, Sharif Bhuiyan, Reza Adhami

“…The results prove the efficacy of the proposed feature point detection algorithm. Moreover, in terms of repeatability rate; the results show that the performance of the proposed method with respect to different aspect is compatible with the existing methods.…”
Get full text

On Guaranteed Detectability for Surveillance Sensor Networks by Yanmin Zhu

“…In this paper, we propose a fully distributed algorithm GAP for energy-efficient event detection for surveillance applications. …”
Get full text

About Detection of Code Reuse Attacks by Yury V. Kosolapov

“…A feature of the algorithm is that it is focused on identifying all currently known techniques of re-execution of the code. …”
Get full text