Lightweight Pyramid Cross-Attention Network for No-Service Rail Surface Defect Detection by Sixu Guo, Jiyou Fei, Liying Wang, Hua Li, Xiaodong Liu

“…Vision-based rail defect detection plays a crucial role in ensuring the safety and efficiency of railway transportation systems. …”
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Crashing Fault Residence Prediction Using a Hybrid Feature Selection Framework from Multi-Source Data by Xiao Liu, Xianmei Fang, Song Sun, Yangchun Gao, Dan Yang, Meng Yan

“…This task plays a crucial role in software quality assurance by enhancing debugging efficiency and reducing testing costs. This study introduces SCM, a two-stage composite feature selection framework designed to address this challenge. …”
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Asynchronous Real-Time Federated Learning for Anomaly Detection in Microservice Cloud Applications by Mahsa Raeiszadeh, Amin Ebrahimzadeh, Roch H. Glitho, Johan Eker, Raquel A. F. Mini

“…Our FL approach updates the global model in an asynchronous manner to achieve accurate and efficient anomaly detection, addressing computational overhead across diverse edge clients, including those that experience delays. …”
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OW-YOLO: An Improved YOLOv8s Lightweight Detection Method for Obstructed Walnuts by Haoyu Wang, Lijun Yun, Chenggui Yang, Mingjie Wu, Yansong Wang, Zaiqing Chen

“…These improvements effectively reduced model complexity and significantly enhanced detection accuracy for obstructed walnuts. …”
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Detecting Alzheimer's Based on MRI Medical Images by Using External Attention Transformer by Farrel Ardannur Deswanto, Isman Kurniawan

“…It enhances image classification by using two shared external memories and an attention mechanism that filters out redundant information for improved performance and efficiency. The aim of this research is to evaluate and compare the performance of the baseline Convolutional Neural Network (CNN) model, the Vision Transformer (ViT) model, and the EAT model in detecting Alzheimer's using a dataset of 6400 brain MRI images. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…The unique characteristics of 5G networks, while enabling advanced communication, present challenges in distinguishing between legitimate and malicious traffic, making it more difficult to detect anonymous traffic. Current methodologies for intrusion detection within 5G communication exhibit limitations in accuracy, efficiency, and adaptability to evolving network conditions. …”
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LE-YOLO: A Lightweight and Enhanced Algorithm for Detecting Surface Defects on Particleboard by Chao He, Yongkang Kang, Anning Ding, Wei Jia, Huaqiong Duo

“…Compared with other models, the proposed approach not only improved detection precision but also effectively reduced model complexity, achieving a lightweight and efficient detection framework.…”
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Qseek: A data-driven Framework for Automated Earthquake Detection, Localization and Characterization by Marius Isken, Sebastian Heimann, Peter Niemz, Jannes Münchmeyer, Simone Cesca, Hannes Vasyura-Bathke, Torsten Dahm

“…The resolution of the search volume is iteratively refined toward the seismic source location; this strategy facilitates an efficient, fast, and accurate search. We present a user-friendly and high-performance open-source software framework based on established frameworks, featuring event detection in layered 1D and complex 3D velocity models and event feature extraction capabilities, such as moment and local magnitude calculation from peak ground motions. …”
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An algorithm for road target detection of autonomous vehicles based on improved YOLOv8 by Jianping Gao, Haotian Li, Zhe Li, Chengwei Xie, Xiaolei Ji, Yuzhuo Zhang

“…To address the issue of false alarms caused by close-range overlapping road targets, we propose a new C2f module, C2f-EFB, which combines an efficient channel attention (ECA) mechanism. To address the issue of missed detections in long-distance road target recognition, we have added a P2 small target detection layer for improvement. …”
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Enhancing lung cancer detection through integrated deep learning and transformer models by Revathi Durgam, Bharathi Panduri, V. Balaji, Adil O. Khadidos, Alaa O. Khadidos, Shitharth Selvarajan

“…These are SwiNet for segmented analysis, XLG CancerNet for precise classification of the cases, and DevLO that optimizes the parameters of the lung cancer detection system, making the system more sensible and efficient. …”
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Detection and Recognition of Underwater Acoustic Communication Signal Under Ocean Background Noise by Mengyi Li, Jilong Li, Haihong Feng

“…Non-cooperative underwater acoustic signal detection and recognition technologies occupy an important position in the marine communication environment. …”
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Empowering Quality of Recommendations by Integrating Matrix Factorization Approaches With Louvain Community Detection by Srilatha Tokala, Murali Krishna Enduri, T. Jaya Lakshmi, Ashu Abdul, Jenhui Chen

“…The efficient functioning of the recommendation system undergoes the scalability challenge in controlling large and varying datasets. …”
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Partial feature reparameterization and shallow-level interaction for remote sensing object detection by Minh Tai Pham Nguyen, Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Minh Khue Phan Tran, Tadashi Nakano, Thi Hong Tran

“…Abstract Remote sensing object detection has recently emerged as one of the challenging topics in the field of deep learning applications due to the demand for both high detection performance and computational efficiency. …”
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Novel Wavelet Convolutional Neural Networks for Signal Detection in OFDM-IM Systems by Yang Zhao, SI-YU Zhang, Yuexia Zhang, Gongpu Wang, Behnam Shahrrava

“…However, CNNs' limited receptive field growth poses a challenge in capturing long range dependencies. To achieve efficient deep learning based OFDM-IM detection, this paper proposes two novel OFDM-IM signal detection networks that integrate wavelet transforms with CNNs (WTConv). …”
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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…Automated video anomaly detection (VAD) is a challenging task due to its context-dependent and sporadic nature. …”
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Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…To monitor the drilling process in real time and enhance the efficiency of target detection at underground coal mine drill sites, an improved algorithm based on Yolov8n has been proposed, which offers advantages compared with the traditional detection methods. …”
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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…It has two primary types: one-stage detectors known for their high speed and efficiency, and two-stage detectors, which offer higher accuracy but are often slower due to their complex architecture. …”
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RT-DETR-Smoke: A Real-Time Transformer for Forest Smoke Detection by Zhong Wang, Lanfang Lei, Tong Li, Xian Zu, Peibei Shi

“…Unlike generic object detection, smoke detection faces unique challenges due to smoke’s semitransparent, fluid nature, which often leads to false positives in complex backgrounds and missed detections—particularly around smoke edges and small targets. …”
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Blockage detection in pipelines based on linear frequency modulated acoustic reflection method by Haiyuan Yao, Dan Li, Yan Li, Bo Yang, Yang Meng

“…This study proposes a novel acoustic-based structural health monitoring system integrating linear frequency modulated (LFM) signals with adaptive matched filtering, specifically designed for early blockage detection in complex pipeline networks, including those in built environments. …”
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A Comprehensive Study On Underwater Object Detection Using Deep Neural Networks by K. Samanth, Ramyashree Ramyashree, B. N. Anoop, S. Raghavendra

“…Identifying and removing submerged debris is challenging due to poor visibility, complex water conditions, and the inefficiency of traditional manual approaches. …”
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