A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach by Srikanth Meda, Vangipuram Sesha Srinivas, Killi Chandra Bhushana Rao, Repudi Ramesh, Narasimha Rao Yamarthi

“…To improve the effectiveness of the classification approach, the hyperparameters present in the SHQCNN model are fine-tuned using the shuffled shepherd optimization algorithm (SSOA). Results In the post-deployment phase, the URL is encoded using Optimized Bidirectional Encoder Representations from Transformers (OptBERT), after which the features are extracted. …”
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Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection by Tuğçe Öznacar, Tunç Güler

“…Conclusions: This study highlights the importance of choosing appropriate machine learning algorithms and feature selection techniques for ovarian cancer diagnosis. …”
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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. …”
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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. …”
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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. …”
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Diagnosis and Classification of Two Common Potato Leaf Diseases (Early Blight and Late Blight) Using Image Processing and Machine Learning by H. Koroshi Talab, D. Mohammad Zamani, M. Gholami Parashkoohi

“…The most effective features for disease detection were identified using a combination of all three feature sets. …”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…By examining the timing between packets and other statistical features, we detected patterns of malicious activity, allowing early and effective DoS threat mitigation. …”
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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. …”
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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. …”
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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. …”
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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.…”
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Landslide Identification from Post-Earthquake High-Resolution Remote Sensing Images Based on ResUNet–BFA by Zhenyu Zhao, Shucheng Tan, Yiquan Yang, Qinghua Zhang

“…The integration of deep learning and remote sensing for the rapid detection of landslides from high-resolution remote sensing imagery plays a crucial role in post-disaster emergency response. …”
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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.…”
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Protecting digital assets using an ontology based cyber situational awareness system by Tariq Ammar Almoabady, Yasser Mohammad Alblawi, Ahmad Emad Albalawi, Majed M. Aborokbah, S. Manimurugan, Ahmed Aljuhani, Hussain Aldawood, P. Karthikeyan

“…The Isolation Forest algorithm excels in anomaly detection in high-dimensional datasets, while autoencoders provide nonlinear detection capabilities and adaptive feature learning. …”
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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. …”
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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. …”
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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. …”
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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. …”
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Moving Object Detection for Video Surveillance by K. Kalirajan, M. Sudha

“…In this paper, a novel approach of object detection for video surveillance is presented. The proposed algorithm consists of various steps including video compression, object detection, and object localization. …”
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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. …”
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