A Novel Two-Stage Deep Learning Model for Network Intrusion Detection: LSTM-AE by Vanlalruata Hnamte, Hong Nhung-Nguyen, Jamal Hussain, Yong Hwa-Kim

“…Machine learning and deep learning techniques are widely used to evaluate intrusion detection systems (IDS) capable of rapidly and automatically recognizing and classifying cyber-attacks on networks and hosts. …”
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Intelligent Cyber-Attack Detection in IoT Networks Using IDAOA-Based Wrapper Feature Selection by Mohammed Abdullah, Ryna Svyd

“…This study presents an innovative framework that integrates the Improved Dynamic Arithmetic Optimization Algorithm (IDAOA) with a Bagging technique to enhance the performance of intelligent cyber intrusion detection systems. …”
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A Fast Recognition Method for Dynamic Blasting Fragmentation Based on YOLOv8 and Binocular Vision by Ming Tao, Ziheng Xiao, Yulong Liu, Lei Huang, Gongliang Xiang, Yuanquan Xu

“…The YOLOv8 instance segmentation model is employed to detect and classify rock fragments. By integrating binocular vision-based automatic image capture with Welzl’s algorithm, the actual particle size of each rock fragment is calculated. …”
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Dynamic Handwriting Features for Cognitive Assessment in Inflammatory Demyelinating Diseases: A Machine Learning Study by Jiali Yang, Chaowei Yuan, Yiqiao Chai, Yukun Song, Shuning Zhang, Junhui Li, Mingying Lan, Li Gao

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Temporal Dynamics in Short Text Classification: Enhancing Semantic Understanding Through Time-Aware Model by Khaled Abdalgader, Atheer A. Matroud, Ghaleb Al-Doboni

“…This limitation reduces their ability to accurately classify time-sensitive texts, where understanding context, detecting trends, and addressing semantic shifts over time are critical. …”
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DDoS attack detection in intelligent transport systems using adaptive neuro-fuzzy inference system by G. Usha, H. Karthikeyan, Kumar Gautam, Nikhil Pachauri

“…The system demonstrated low false positive rates and high detection reliability, ensuring suitability for real-world Intelligent Transportation Systems security. …”
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Bi-Modal Multiperspective Percussive (BiMP) Dataset for Visual and Audio Human Fall Detection by Joe Dibble, Michael C. F. Bazzocchi

“…Typical fall detection systems classify a fall event using either inertial- or vision-based data. …”
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Automatic eddy detection in Antarctic marginal ice zone using Sentinel-1 SAR data by Nikita Sandalyuk, Eduard Khachatrian, Ekaterina Marchuk

“…By fine-tuning YOLOv11 on a specialized dataset representing the dynamic Antarctic MIZ, we achieved robust detection of submesoscale and mesoscale eddies. …”
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A Swarm-Based Multi-Objective Framework for Lightweight and Real-Time IoT Intrusion Detection by Hessah A. Alsalamah, Walaa N. Ismail

“…PSO optimizes convergence speed, model complexity, and classification accuracy by dynamically adjusting the weights and thresholds of the deployed classifiers. …”
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Improving robotic grasping accuracy through oriented bounding box detection with YOLOv11-OBB by Vo Duy Cong, Le Hoai Phuong

“…The proposed approach not only improves grasp detection performance but also ensures real-time feasibility, with an inference time of 29 ms, making it highly suitable for robotic applications in dynamic environments.…”
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Evaluation of Associated Structural and Chromosomal Abnormalities in Patients with Fetal Cerebral Ventriculomegaly Detected in Ultrasonographic Imaging by Erkan Cagliyan, Samican Ozmen, Sureyya Saridas Demir, Ceren Aydin, Egehan Bilen, Handan Guleryuz, Elif Yasar, Derya Ercal, Elcin Bora, Tufan Cankaya

“…CONCLUSIONS: Fetal cerebral ventriculomegaly is a dynamic process. The etiology is multifactorial and abnormalities can be detected during follow-up. …”
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An FPGA Prototype for Parkinson’s Disease Detection Using Machine Learning on Voice Signal by Mujeev Khan, Abdul Moiz, Gani Nawaz Khan, Mohd Wajid, Mohammed Usman, Jabir Ali

“…This paper proposes an efficient machine learning model for PD detection using voice-based features, which offer a non-invasive, cost-effective, and accessible alternative to complex imaging methods. …”
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The Use of Hybrid CNN-RNN Deep Learning Models to Discriminate Tumor Tissue in Dynamic Breast Thermography by Andrés Munguía-Siu, Irene Vergara, Juan Horacio Espinoza-Rodríguez

“…Our findings show that hybrid CNN-RNN models outperform stand-alone CNN models, indicating that temporal data recovery from dynamic breast thermographs is possible without significantly compromising classifier runtime.…”
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The TouCAN Codebook: Detecting textual misunderstanding in doctor-patient communication with the philosophy of language tools. by Monica Consolandi, Mara Floris, Cristina Ganz, Noemi Paciscopi

“…This paper introduces a novel approach to detecting and analyzing such misunderstandings in clinical interactions by drawing on concepts from the philosophy of language. …”
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In-context learning for propaganda detection on Twitter Mexico using large language model meta AI by C.A. Piña-García

“…This study explores the application of Large Language Models (LLMs) for detecting political propaganda on Twitter, focusing on manipulative political narratives during the 2018 Mexican presidential election. …”
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Enhanced early detection of dysarthric speech disabilities using stacking ensemble deep learning model by Jagat Chaitanya Prabhala, Ravi Ragoju, Venkatanareshbabu Kuppili, Christophe Chesneau

“…Unlike conventional stacking methods that use fixed meta-classifiers, this study employs a Genetic Algorithm (GA)-based optimization strategy to dynamically determine optimal weight contributions of the base models, enhancing classification robustness and adaptability.The preprocessing pipeline converts speech signals from the time domain to the frequency domain by using a Short-Time Fourier Transform (STFT). …”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…After feature selection, an echo-state network (ESN) classifier is employed for detection and prediction. …”
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Enhancing Detection of Control State for High-Speed Asynchronous SSVEP-BCIs Using Frequency-Specific Framework by Yufeng Ke, Jiale Du, Shuang Liu, Dong Ming

“…The FS framework sequentially incorporated task-related component analysis (TRCA)-based SSVEP identification and a classifier bank containing multiple FS control state detection classifiers. …”
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Real-Time jamming detection using windowing and hybrid machine learning models for pre-saturation alerts by J. Sormayli, M. Darvishi, K. Zarrinnegar, M. R. Mosavi

“…This work’s key contribution is integrating a windowing mechanism for pre-saturation alerts and early activation of jamming detection which enhances system reliability by distinguishing between high-credibility and low-credibility GNSS data under static and dynamic jamming conditions. …”
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DynseNet: A Dynamic Dense-Connection Neural Network for Land–Sea Classification of Radar Targets by Jingang Wang, Tong Xiao, Kang Chen, Peng Liu

“…However, existing radar target detection algorithms predominantly achieve binary detection (i.e., determining the presence or absence of a target) and are unable to accurately classify target types. …”
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