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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HPRT-DETR: A High-Precision Real-Time Object Detection Algorithm for Intelligent Driving Vehicles by Xiaona Song, Bin Fan, Haichao Liu, Lijun Wang, Jinxing Niu

“…This integration expands the model’s receptive field and enhances feature extraction without adding learnable parameters or complex computations, effectively minimizing missed detections of small targets. …”
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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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Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…Second, the G-Shuffle module is designed to significantly enhance feature extraction efficiency and interchannel information interaction, balancing computational complexity and detection accuracy. …”
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Uncrewed Aerial Vehicle-Based Automatic System for Seat Belt Compliance Detection at Stop-Controlled Intersections by Gideon Asare Owusu, Ashutosh Dumka, Adu-Gyamfi Kojo, Enoch Kwasi Asante, Rishabh Jain, Skylar Knickerbocker, Neal Hawkins, Anuj Sharma

“…The model was tested in real-world scenarios at a single-lane and a complex multi-lane stop-controlled intersection in Iowa. …”
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Advances in the Application of CRISPR-Cas-Based Detection Systems for Safety Monitoring and Control in the Food Supply Chain by WAN Wen-yuan, ZHANG Feng, LIU Zhi-yong, ZHAO Yu

“…CRISPR-Cas-based detection methods significantly improve detection efficiency, providing valuable technical support for food industry monitoring. …”
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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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Design of an Improved Model for Anomaly Detection in CCTV Systems Using Multimodal Fusion and Attention-Based Networks by V. Srilakshmi, Sai Babu Veesam, Mallu Shiva Rama Krishna, Ravi Kumar Munaganuri, Dulam Devee Sivaprasad

“…Long Short-Term Memory (LSTM) can capture long-range dependencies in sequential data, while Temporal Convolutional Network (TCN) efficiently models temporal patterns using convolutional layers and Transformer Networks fathom the relative importance of temporal features against one another through self-attention, thus improving their detection accuracy for anomalies that happen over a long duration. …”
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Real-Time Forest Fire Detection with Lightweight CNN Using Hierarchical Multi-Task Knowledge Distillation by Ismail El-Madafri, Marta Peña, Noelia Olmedo-Torre

“…The novelty of this approach lies in leveraging knowledge distillation to transfer the deeper insights learned by the DenseNet201 teacher model—specifically, the auxiliary task of recognizing the confounding elements responsible for false positives—into a lightweight student model, enabling it to achieve a similar robustness without the need for complex architectures. Using this distilled knowledge, we trained a MobileNetV3-based student model, which was designed to operate efficiently in real-time while maintaining a low computational overhead. …”
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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

“…This review systematically explores the application of machine learning (ML) models in the context of Intrusion Detection Systems (IDSs) for modern network security, particularly within 5G environments. …”
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YOLO-Tryppa: A Novel YOLO-Based Approach for Rapid and Accurate Detection of Small Trypanosoma Parasites by Davide Antonio Mura, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto

“…Early detection of Trypanosoma parasites is critical for the prompt treatment of trypanosomiasis, a neglected tropical disease that poses severe health and socioeconomic challenges in affected regions. …”
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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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Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding by Wasim Khan, Mohammad Ishrat, Ahmad Neyaz Khan, Mohammad Arif, Anwar Ahamed Shaikh, Mousa Mohammed Khubrani, Shadab Alam, Mohammed Shuaib, Rajan John

“…Attributed networks are prevalent in the current information infrastructure, where node attributes enhance knowledge discovery. Anomaly detection in attributed networks is gaining attention for its potential uses in cybersecurity, finance, and healthcare. …”
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Role of ^99mTc-pyrophosphate myocardial scintigraphy in assessing the efficiency of tafamidis therapy: a case series by A. A. Shoshina, A. A. Ansheles, S. N. Nasonova, I. V. Zhirov, V. B. Sergienko, S. N. Tereshchenko

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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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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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LIU-NET: lightweight Inception U-Net for efficient brain tumor segmentation from multimodal 3D MRI images by Gul e Sehar Shahid, Jameel Ahmad, Chaudary Atif Raza Warraich, Amel Ksibi, Shrooq Alsenan, Arfan Arshad, Rehan Raza, Zaffar Ahmed Shaikh

“…Its capability to efficiently and precisely segment brain tumors, especially in challenging-to-detect regions, distinguishes it from existing models. …”
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Design, construction and efficiency analysis of bagasse-based charcoal packed horizontal lab-scale wetland for the removal of antibiotic-resistant bacteria by Misbah Batool Aslam, Talmeez U. R. Rehman, Amina Farrukh Alavi, Abdul Haleem, Abdul Haq, Safia Ahmed, Wasim Sajjad, Mohammed Bourhia, Ousman B. Mahamat, Khalid S. Almaary, Mahwish Ali

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