LitePipeNet: Research on a Lightweight and Efficient Segmentation Model for UAV Pipeline Inspection in Mining Areas by Huang Yong, Xiao Shengwang, Xia Xing, Huang Qiu

“…In response to the challenges of UAV-based pipeline inspection in mining areas—including difficulties in small object detection, limited adaptability to complex environments, and constraints on efficient edge deployment—this paper proposes LitePipeNet, a lightweight segmentation model tailored for edge computing. …”
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Efficient Stereo Visual Odometry on FPGA Featuring On-Chip Map Management and Pipelined Descriptor-Based Block Matching by Yuki Ichikawa, Kazushi Kawamura, Masato Motomura, Thiem van Chu

“…These irregular patterns arise from the dynamic and non-uniform nature of feature detection, stereo matching, and map management, which vary significantly with scene complexity and camera movement. …”
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Modern Trends and Recent Applications of Hyperspectral Imaging: A Review by Ming-Fang Cheng, Arvind Mukundan, Riya Karmakar, Muhamed Adil Edavana Valappil, Jumana Jouhar, Hsiang-Chen Wang

“…Environmental applications include PM2.5 pollution detection with 85.93% accuracy and marine plastic waste detection with 70–80% accuracy. …”
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Prototyping a graph-based approach for efficient vehicle tracking in a cluster controlled CCTV surveillance systems by Apurva NARAYAN, Charumathi PARIVALLAL, Olirva MAHESWARAN, Sarath CHANDRAN KALATHILPARAMBIL RAMACHANDRAN

“…Addressing the growing challenges of vehicle density and traffic complexity, the system employs state-of-the-art deep learning techniques for real-time vehicle detection, tracking, and route analysis. …”
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A Lightweight Pavement Defect Detection Algorithm Integrating Perception Enhancement and Feature Optimization by Xiang Zhang, Xiaopeng Wang, Zhuorang Yang

“…To address the current issue of large computations and the difficulty in balancing model complexity and detection accuracy in pavement defect detection models, a lightweight pavement defect detection algorithm, PGS-YOLO, is proposed based on YOLOv8, which integrates perception enhancement and feature optimization. …”
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Comprehensive Outlier Detection in Wireless Sensor Network with Fast Optimization Algorithm of Classification Model by Haiqing Yao, Heng Cao, Jin Li

“…Since the nonstationary distribution of the detected objects is general in the real world, the accurate and efficient outlier detection for data analysis within wireless sensor network (WSN) is a challenge. …”
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FEMNet: A Feature-Enriched Mamba Network for Cloud Detection in Remote Sensing Imagery by Weixing Liu, Bin Luo, Jun Liu, Han Nie, Xin Su

“…Accurate and efficient cloud detection is critical for maintaining the usability of optical remote sensing imagery, particularly in large-scale Earth observation systems. …”
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NevusCheck: A Dysplastic Nevi Detection Model Using Convolutional Neural Networks by Andreluis Ingaroca-Torres, Lucía Heredia-Moscoso, Alvaro Aures-García

“…Therefore, the research aims to develop a model to diagnose dysplastic nevi using a deep learning network whose classification is based on the pre-trained architecture EfficientNet-B7, which was selected for its high classification accuracy and low computational complexity. …”
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TinyML-enabled fuzzy logic for enhanced road anomaly detection in remote sensing by Amna Khatoon, Weixing Wang, Mengfei Wang, Limin Li, Asad Ullah

“…Abstract Advanced techniques for detecting and classifying road anomalies are crucial due to road networks’ rapid expansion and increasing complexity. …”
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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

“…Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  …”
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Ambient Intelligence to Detect Misuse of Electricity Consumption Based on IoT Using Blockchain Technology by Soiful Hadi, Wahyul Amien Syafei, Adi Wibowo

“…Electricity abuse and energy inefficiencies are still open issues in smart grid systems, demanding high-performance anomaly detection mechanisms. In this paper, we propose an IoT-enabled electricity monitoring system that combines machine learning (LightGBM) and blockchain (Polygon network) for real-time anomaly detection, secure data storage, and transparent energy tracking. …”
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A Real-Time Lane Detection Algorithm Based on Intelligent CCD Parameters Regulation by Ping-shu Ge, Lie Guo, Guo-kai Xu, Rong-hui Zhang, Tao Zhang

“…Lane detection is one of the key techniques for LDWS. To overcome the contradiction between complexity of algorithm and the real-time requirement for vehicle onboard system, this paper introduces a new lane detection method based on intelligent CCD parameters regulation. …”
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Design and Validation of a Lightweight Entropy-Based Intrusion Detection Algorithm for Automotive CANs by Jiacheng Chen, Zhifu Wang

“…This work provides a resource-efficient security framework compatible with existing CAN infrastructures, effectively balancing attack detection efficacy with the operational constraints of automotive embedded systems.…”
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Fish Detection in Fishways for Hydropower Stations Using Bidirectional Cross-Scale Feature Fusion by Junming Wang, Yuanfeng Gong, Wupeng Deng, Enshun Lu, Xinyu Hu, Daode Zhang

“…This paper proposes a fish detection model for accurate and efficient fish detection. …”
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Geometric Shaping for Distortion-Limited Intensity Modulation/Direct Detection Data Center Links by Ethan M. Liang, Joseph M. Kahn

“…Intra-data center links are subject to transmission impairments that pose challenges for efficient scaling of per-wavelength data rates beyond 100 Gb/s. …”
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AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system by C. Rajathi, P. Rukmani

“…However, the vast amount of  network data requires an efficient processing approach. Among various studies from existing literature, Machine Learning (ML) algorithms provide a viable solution to detecting intrusion in voluminous data. …”
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Enhanced Anomaly Detection in IoT Networks Using Deep Autoencoders with Feature Selection Techniques by Hamza Rhachi, Younes Balboul, Anas Bouayad

“…Compared to some IoT-based anomaly detection models, the experimental results reveal that the suggested model is more efficient at enhancing the accuracy of detecting malicious data. …”
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Real-Time Power System Event Detection: A Novel Instance Selection Approach by Gabriel Intriago, Yu Zhang

“…This study presents a novel adaptation of the Hoeffding Adaptive Tree (HAT) classifier with an instance selection algorithm that detects and identifies cyber and non-cyber contingencies in real time to enhance the situational awareness of cyber-physical power systems (CPPS). …”
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Cutting-Edge Phishing Detection Using Novel Features and Hybrid Machine Learning Techniques by Jin Zhang

“…Classification Information Mining (DM) strategies are highly effective tools for identifying and detecting e-banking phishing websites. This study introduces a novel approach to address the challenges and complexities associated with predicting and identifying such websites. …”
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Deep learning-based ensemble stacking for enhanced intrusion detection in IoT-edge platforms by P. R. Chithra Rani, K. Baalaji

“…This research contributes a scalable, efficient, and resource-aware intrusion-detection approach to extending the resilience of IoT-edge systems in distributed computing environments.…”
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