Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…Comparative analysis shows that DLECA outperforms Random Walk and Bayesian Optimization in multimodal fake news detection, offering a more efficient and accurate solution.…”
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A Lightweight Intrusion Detection System with Dynamic Feature Fusion Federated Learning for Vehicular Network Security by Junjun Li, Yanyan Ma, Jiahui Bai, Congming Chen, Tingting Xu, Chi Ding

“…The traditional Intrusion Detection System (IDS) makes it difficult to effectively deal with the dynamics and complexity of emerging threats. …”
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Infrared Small Target Detection Based on Approximate Background Regularization and Bimodal Slice Based Graph Constraints by Xiaoling Ge, Zipeng Fu, Xuelian Yu, Weixian Qian, Kan Ren, Minjie Wan, Guohua Gu

“…Experimental results show that the proposed method outperforms state-of-the-art approaches in both detection performance and efficiency while demonstrating greater robustness in complex scenarios.…”
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Multi-Signal Induction Motor Broken Rotor Bar Detection Based on Merged Convolutional Neural Network by Tianyi Wang, Shiguang Wen, Shaotong Sheng, Huimin Ma

“…Traditional methods face challenges in motor broken rotor bar (BRB) detection: model-driven methods are difficult to apply accurately in complex and changing environments, while data-driven methods usually require sophisticated feature extraction and classification processes. …”
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A Novel Approach to Classify Brain Tumor with an Effective Transfer Learning based Deep Learning Model by Hafiz Muhammad Tayyab Khushi, Tehreem Masood, Arfan Jaffar, Sheeraz Akram

“…We need an autonomous, intelligent system to detect brain cancers early and accurately. This study proposes a pre-trained EfficientNetb4 model with an adjusttable learning rate and custom callback to efficiently classify tumors. …”
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Intelligent Stress Detection Using ECG Signals: Power Spectrum Imaging with Continuous Wavelet Transform and CNN by Rodrigo Mateo-Reyes, Irving A. Cruz-Albarran, Luis A. Morales-Hernandez

“…The proposed approach is characterized by its ability to transform ECG signals into time–frequency representations by means of short duration sampling, achieving an accurate classification of stress states without the need for complex feature extraction processes. This model is an efficient and accurate tool for stress analysis from biomedical signals.…”
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An Optimally Oriented Coherence Attribute Method and Its Application to Faults and Fracture Sets Detection in Carbonate Reservoirs by Shuai Chen, Shengjun Li, Qi Ma, Lu Qin, Sanyi Yuan

“…Overall, the OOCA method offers a geologically consistent and computationally efficient solution for high-resolution fault interpretation and drilling risk prediction in structurally complex carbonate reservoirs.…”
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Evaluating YOLO Variants With Transfer Learning for Real-Time UAV Obstacle Detection in Simulated Forest Environments by Shouthiri Partheepan, Farzad Sanati, Jahan Hassan

“…The results offer practical guidance for selecting YOLO architectures in UAV-based obstacle detection tasks, balancing accuracy, speed, and deployment feasibility in complex environments.…”
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A Lightweight Remote-Sensing Image-Change Detection Algorithm Based on Asymmetric Convolution and Attention Coupling by Enze Zhang, Yan Li, Haifeng Lin, Min Xia

“…In recent years, breakthroughs in satellite sensor technology have generated vast volumes of data and complex scenes, presenting significant challenges for change-detection algorithms. …”
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Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices by Muhammad Bisri Musthafa, Samsul Huda, Tuy Tan Nguyen, Yuta Kodera, Yasuyuki Nogami

“…Deep learning techniques offer promising solutions for such detection due to their superior complex pattern recognition and anomaly detection capabilities in large datasets. …”
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MonoDFM: Density Field Modeling-Based End-to-End Monocular 3D Object Detection by Gang Liu, Xinrui Huang, Xiaoxiao Xie

“…Moreover, compared with more complex approaches like Neural Radiance Fields (NeRF), MonoDFM provides a streamlined and efficient prediction process. …”
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YS3AM: Adaptive 3D Reconstruction and Harvesting Target Detection for Clustered Green Asparagus by Si Mu, Jian Liu, Ping Zhang, Jin Yuan, Xuemei Liu

“…Extracting precise stem details in complex spatial arrangements is a challenge. This paper explored the YS3AM (Yolo-SAM-3D-Adaptive-Modeling) method for detecting green asparagus and performing 3D adaptive-section modeling using a depth camera, which could benefit harvesting path planning for selective harvesting robots. …”
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Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes by Karolina Buka, Zofia Parteka-Tojek, Abhishek Agarwal, Michał Denkiewicz, Sevastianos Korsak, Mateusz Chiliński, Krzysztof H. Banecki, Dariusz Plewczynski

“…Using comprehensive bioinformatic analysis, we show that a dual chromatin fixation method compared to the standard formaldehyde-only method, results in a substantially better signal-to-noise ratio, increased ChIP efficiency and improved detection of chromatin loops and architectural stripes. …”
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DSAT: a dynamic sparse attention transformer for steel surface defect detection with hierarchical feature fusion by Shouluan Wu, Hui Yang, Liefa Liao, Chao Song, Yating Fang, Jianglong Fu, Tan Li

“…These defects exhibit diverse morphological characteristics and complex patterns, which pose substantial challenges to traditional detection models, particularly regarding multi-scale feature extraction and information retention across network depths. …”
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Improved Reduced-Order Fault Detection Filter Design for Polytopic Uncertain Discrete-Time Markovian Jump Systems with Time-Varying Delays by Lihong Rong, Xiuyan Peng, Liangliang Liu, Biao Zhang

“…Under meeting the control precision requirements of the complex systems, the reduced-order fault detection filter can improve the efficiency of the fault detection. …”
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Research on Lightweight Open-Pit Mine Driving Obstacle Detection Algorithm Based on Improved YOLOv8s by Bo Xu, Wubin Xu, Bing Li, Hanwen Zhang, Yuanbin Xiao, Weixin Zhou

“…Improving the accuracy and speed of obstacle detection during driving is of great significance to ensuring the safety of mine automation construction and improving the efficiency of overall unmanned operations. …”
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Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification by Heba G. Mohamed, Fadwa Alrowais, Fahd N. Al-Wesabi, Mesfer Al Duhayyim, Anwer Mustafa Hilal, Abdelwahed Motwakel

“…The presented MCOBC-HDDC method provides an efficient and accurate disease diagnosis, utilizing a system that depends on DL techniques. …”
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Development of eco-friendly and cost-effective electrochemical sensor for the simultaneous detection of 4-aminophenol and paracetamol in water by Antía Fdez-Sanromán, Najib Ben Messaoud, Marta Pazos, Emilio Rosales, Raquel Barbosa Queirós

“…It was successfully tested in real freshwater samples, demonstrating high accuracy even in complex matrices. This innovative methodology provides a rapid, cost-effective, and portable analytical tool for routine monitoring of pharmaceutical contaminants, enabling more accurate environmental risk assessments and supporting the implementation of more efficient management strategies.…”
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Deep learning-based dual monitoring system for power forecasting and fault detection in nuclear power applications by Mingzhe Lyu, Helin Gong, Zhang Chen, Jiangyu Wang, Mingxiao Zhong, Zhiyong Wang, Qing Li, Zefei Pan

“…For fault diagnosis, the dual-monitoring system reduces the false negative rate to 18.73% and improves recall to 81.27%, demonstrating strong anomaly detection under complex conditions. By combining short-term fluctuation sensitivity with long-term trend stability, the proposed approach offers a robust and generalizable solution for intelligent monitoring. …”
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Automated lumbar intervertebral disc identification and herniation detection in MR images using cascade CNN architecture by Md Abu Sayed, Ashiqur Rahman, Sadman Mohammad Nasif, Sudipto Halder, Akram Hossain, Hasan Ahmed, Muhammad Abdul Kadir

“…This study aims to develop an automated, accurate, and efficient system for the detection and classification of lumbar intervertebral disc herniation using deep learning models applied to axial and sagittal MR images. …”
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