CUNet-CLSTM: A Novel Fusion of CUNet and CLSTM for Superior Liver Cancer Detection in CT Scans by K. Vijayaprabakaran, Padmanaban Ramalingam, Rajakumar Ramalingam, A. Ilavendhan, R. Vedhapriyavadhana

“…Despite the triumph of convolutional neural networks in medical image analysis, challenges such as overfitting, limited labeled data, and complex tumor morphology hinder accurate detection of liver cancer. …”
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YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes by Yiliang Zeng, Xiuhong Wang, Jinlin Zou, Hongtao Wu

“…To tackle the challenge of wake waves from moving ships obscuring small targets, we introduce a gradient flow mechanism that improves detection efficiency under dynamic conditions. The Tail Wave Detection Method synergistically integrates gradient computation with target detection techniques. …”
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A Dual-Branches Multiscale Dynamic Partial Convolutional Attention Network for Remote Sensing Change Detection by Wenbin Tang, Shuli Cheng, Anyu Du

“…In addition, a bottom-up training strategy is applied to strengthen the completeness of change detection. Extensive experiments on three publicly available datasets demonstrate that, compared to other methods, our proposed approach achieves superior performance and detection results, while reducing parameters and computational complexity.…”
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Real-time driver drowsiness detection using transformer architectures: a novel deep learning approach by Osama F. Hassan, Ahmed F. Ibrahim, Ahmed Gomaa, M. A. Makhlouf, B. Hafiz

“…This represents a significant advancement over existing methods, demonstrating the effectiveness of transformer-based architectures in capturing complex spatial dependencies and extracting relevant features for drowsiness detection. …”
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Universal Method for Detecting Violations in the Integrity of a Digital Image Based on Analysis of Blocks of its Matrix by Bobok I., Kobozeva A.

“…Thus, the aim of the work is to increase the efficiency of identifying the fact of violation of image integrity by developing a universal expert method with low computational complexity. …”
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Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm by El-Sayed M. El-Kenawy, Nima Khodadadi, Marwa M. Eid, Ehsaneh Khodadadi, Ehsan Khodadadi, Doaa Sami Khafaga, Amel Ali Alhussan, Abdelhameed Ibrahim, Mohamed Saber

“…Abstract With the advancement of medical technology, a large amount of complex data on cancers is produced for diagnosing and treating cancers. …”
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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

“…In modern power systems, insulators, as key components of transmission lines, are crucial for defect detection for the safe operation of power grids. Aiming at the problems of low efficiency of traditional manual detection, the vulnerability of traditional image processing methods to environmental interference, and the insufficient ability of existing deep learning models to detect small target defects under complex backgrounds, this paper proposes an improved target detection model based on YOLOv10n, which is the first time to integrate the spatial channel attention mechanism (SEAttention) with the up-sampling expansion operation (Patch Expanding) in the Neck part of the model. …”
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A Review of Machine Learning and Transfer Learning Strategies for Intrusion Detection Systems in 5G and Beyond by Kinzah Noor, Agbotiname Lucky Imoize, Chun-Ta Li, Chi-Yao Weng

“…Naive Bayes (NB) stands out for its computational efficiency despite moderate performance in other areas. …”
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A Full-Scale Shadow Detection Network Based on Multiple Attention Mechanisms for Remote-Sensing Images by Lei Zhang, Qing Zhang, Yu Wu, Yanfeng Zhang, Shan Xiang, Donghai Xie, Zeyu Wang

“…Therefore, this model offers an efficient solution for shadow detection in aerial imagery.…”
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VMMCD: VMamba-Based Multi-Scale Feature Guiding Fusion Network for Remote Sensing Change Detection by Zhong Chen, Hanruo Chen, Junsong Leng, Xiaolei Zhang, Qi Gao, Weiyu Dong

“…Moreover, the former also leads to a reduction in speed. To guarantee the efficiency of change detection, encompassing both speed and accuracy, a VMamba-based Multi-scale Feature Guiding Fusion Network (VMMCD) is proposed. …”
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Sustainable phytoprotection: a smart monitoring and recommendation framework using Puma Optimization for potato pathogen detection by Amal H. Alharbi, Faris H. Rizk, Khaled Sh. Gaber, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Pushan Kumar Dutta, Doaa Sami Khafaga

“…In contrast, convergence analysis demonstrated PO-RBM’s computational efficiency relative to PSO, GWO, and GA alternatives. …”
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Enhanced Performance of Asymmetrically Clipped DC-Biased Optical OFDM Systems Using Adjacent Symbol Detection by Wei-Wen Hu

“…Compared to the direct current (DC) biased optical OFDM (DCO-OFDM) and asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) schemes, the asymmetrically clipped DC biased optical OFDM (ADO-OFDM) has demonstrated a better balance between optical power efficiency and spectrum efficiency. However, both the traditional ADO-OFDM and ADO-OFDM with iteration receiver suffer from an error floor issue when a lower DC bias is allocated to the DCO-OFDM branch. …”
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Inter-observational analysis of computed tomography parameters to predict nonobvious posterior ligament complex injury in neurologically intact patients with thoracolumbar trauma by Joana Araújo de Azevedo, Carolina Garcez Martins, Nuno Oliveira, Pedro Varanda, Bruno Direito-Santos

“…Introduction: Assessing the integrity of the posterior ligament complex (PLC), as a key element in the characterization of an unstable Thoracolumbar fracture (TLF), is challenging, but crucial in the choice of treatment. …”
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A Real-Time Cotton Boll Disease Detection Model Based on Enhanced YOLOv11n by Lei Yang, Wenhao Cui, Jingqian Li, Guotao Han, Qi Zhou, Yubin Lan, Jing Zhao, Yongliang Qiao

“…To mitigate false negatives and false positives encountered by the original YOLOv11n model during detection, the EMA (efficient multi-scale attention) mechanism is introduced to enhance the weights of important features and suppress irrelevant regions, thereby improving the detection accuracy of the model. …”
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Detection and functional assessment of structural variants using whole-genome re-sequencing data in Nellore cattle by Natalia A. Marín-Garzón, Lucio F. M. Mota, Giovana Vargas, Leonardo M. Arikawa, Larissa F. S. Fonseca, Gerardo A. Fernandes Júnior, Roberto Carvalheiro, Lucia G. Albuquerque

“…Abstract Ongoing advances in genome sequencing technologies have enabled the identification of numerous structural variants (SVs) in livestock genomes, which are the main determinants of complex traits due to their impact on gene expression. …”
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LDDFSF-YOLO11: A Lightweight Insulator Defect Detection Method Focusing on Small-Sized Features by Peng Shen, Keyu Mei, Huiqiong Cao, Yongxiang Zhao, Guoqing Zhang

“…This study proposes a lightweight insulator defect detection method (LDDFSF-YOLO11) that focuses on small-sized features to efficiently detect and identify insulator defects. …”
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Research on multi class pests identification and detection based on fusion attention mechanism with Mask-RCNN-CBAM by Xingwang Wang, Xingwang Wang, Xingwang Wang, Can Hu, Xufeng Wang, Hainie Zha, Xueyong Chen, Shanshan Yuan, Jing Zhang, Jianfeng Liao, Zhangying Ye

“…This study addresses challenges in agricultural pest detection, such as false positives and missed detections in complex environments, by proposing an enhanced Mask-RCNN model integrated with a Convolutional Block Attention Module (CBAM). …”
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Detection and Segmentation of Glioma Tumors Using an Improved Visual Geometry Group (IVGG) Deep Learning Structure by Parameswari Alagarsamy, Vinoth Kumar Kalimuthu, Bhavani Sridharan

“…Analysis of the performance efficiency has been done in relation to the Jaccard index, recall, precision, and detection rate.…”
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Improved Building Information Modeling Based Method for Prioritizing Clash Detection in the Building Construction Design Phase by Iman Bitaraf, Ali Salimpour, Pedram Elmi, Ali Akbar Shirzadi Javid

“…The proposed method substantially improves clash detection and prioritization efficiency and accuracy, yielding considerable benefits in project management and resource allocation.…”
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SAG-YOLO: A Lightweight Real-Time One-Day-Old Chick Gender Detection Method by Yulong Chang, Rongqian Sun, Zheng Yang, Shijun Li, Qiaohua Wang

“…This study proposes an improved SAG-YOLO method for chick sex detection. Firstly, the model reduces both parameter size and computational complexity by replacing the original feature extraction with the StarNet lightweight Backbone. …”
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