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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A Novel YOLOv10-Based Algorithm for Accurate Steel Surface Defect Detection by Liefa Liao, Chao Song, Shouluan Wu, Jianglong Fu

“…The system uses only 2.67 million parameters, demonstrating efficiency. It excels in identifying complex defects like ’rolled in scale’ and ’inclusion’. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…However, this task remains challenging due to variable high-altitude viewpoints, complex environmental interference, and limitations in algorithmic efficiency. …”
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Lane and Traffic Sign Detection for Autonomous Vehicles: Addressing Challenges on Indian Road Conditions by H. S. Gowri Yaamini, Swathi K J, Manohar N, Ajay Kumar G

“…Accurate and precise detection of lanes and traffic signs is predominant for the safety and efficiency of autonomous vehicles and these two significant tasks should be addressed to handle Indian traffic conditions. …”
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Research on a UAV-View Object-Detection Method Based on YOLOv7-Tiny by Yuyang Miao, Xihan Wang, Ning Zhang, Kai Wang, Lianhe Shao, Quanli Gao

“…In addition, introducing the Dilated Weighted Residual (DWR) attention module optimizes the information processing flow, enhancing the algorithm’s ability to capture key information, especially in complex backgrounds. These enhancements collectively enable the model to balance high detection accuracy and computational efficiency, making it well-suited for resource-constrained UAV platforms. …”
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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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Passion Fruit Disease Detection Using Sparse Parallel Attention Mechanism and Optical Sensing by Yajie He, Ningyi Zhang, Xinjin Ge, Siqi Li, Linfeng Yang, Minghao Kong, Yiping Guo, Chunli Lv

“…The experiments show that the sparse parallel attention mechanism offers significant advantages in disease detection with multi-scale and complex backgrounds. …”
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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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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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A lightweight remote sensing image detection model with feature aggregation diffusion network by Xiaohui Cheng, Xukun Wang, Yun Deng, Qiu Lu, Yanping Kang, Jian Tang, Yuanyuan Shi, Junyu Zhao

“…However, existing deep learning models often face challenges in balancing detection accuracy and computational efficiency, especially for small objects in complex scenes. …”
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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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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The increasing penetration of renewable energy into power systems has intensified transient power quality (PQ) disturbances, demanding efficient detection and classification methods to enable timely operational decisions. …”
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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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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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Real-Time Interference Mitigation for Reliable Target Detection with FMCW Radar in Interference Environments by Youlong Weng, Ziang Zhang, Guangzhi Chen, Yaru Zhang, Jiabao Chen, Hongzhan Song

“…In this paper, we propose an efficient solution for real-time radar interference mitigation. …”
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Streamlined Bearing Fault Detection Using Artificial Intelligence in Permanent Magnet Synchronous Motors by Javier de las Morenas, Lidia M. Belmonte, Rafael Morales

“…Permanent magnet synchronous motors (PMSMs) are widely used in industrial applications due to their high efficiency and reliability. However, bearing faults remain a critical issue, necessitating robust fault detection strategies. …”
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A Rotation Target Detection Network Based on Multi-Kernel Interaction and Hierarchical Expansion by Qi Wang, Guanghu Xu, Donglin Jing

“…Through multi-scale feature interaction and direction-aware optimization, MIHE-Net effectively addresses the challenges posed by scale gradation and direction diversity in remote sensing target detection, providing an efficient and feasible solution for high-precision remote sensing target detection.…”
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PlantNet: Scalable Convolutional Neural Network for Image-Based Plant Disease Detection by Sinha Anupa, Kumaraswamy Balasubramaniam

“…By leveraging deep learning techniques, PlantNet processes large-scale image datasets to detect disease symptoms with high precision. The model employs transfer learning, utilizing pre-trained networks on vast image repositories before fine-tuning on a specialized plant disease dataset, thereby enhancing feature extraction while minimizing computational complexity. …”
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