Dynamically Tunable Multidimensional Feature Focusing and Diffusion Networks for Water Surface Debris Detection by Chong Zhang, Jie Yue, Jianglong Fu

“…However, challenges such as complex backgrounds, overlapping targets, and reflections on water surfaces often hinder effective waste detection, resulting in low model accuracy and unreliable recognition. …”
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Ground-Independent UAV Quantitative Mapping and In Situ Experimental Validation for Coral Reef Habitats by Enze Wang, Huaguo Zhang, Yunhan Ma, Han Tong, Juan Wang, Wenting Cao, Dongling Li

“…Optically shallow waters, which host ecosystems like coral reefs, are characterized by complex radiative transfer pathways. Surface reflectance derived from remote sensing in optically shallow waters is influenced by water depth, water quality, and bottom reflectance. …”
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FM-Net: Frequency-Aware Masked-Attention Network for Infrared Small Target Detection by Yongxian Liu, Zaiping Lin, Boyang Li, Ting Liu, Wei An

“…Infrared small target detection (IRSTD) aims to locate and separate targets from complex backgrounds. …”
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Real-time aerial fire detection on resource-constrained devices using knowledge distillation by Sabina Jangirova, Branislava Jankovic, Waseem Ullah, Latif U. Khan, Mohsen Guizani

“…The high accuracy and efficiency of the proposed model make it well-suited for deployment on satellites, UAVs, and IoT devices for effective fire detection. …”
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Novel transfer learning based acoustic feature engineering for scene fake audio detection by Ahmad Sami Al-Shamayleh, Hafsa Riasat, Ala Saleh Alluhaidan, Ali Raza, Sahar A. El-Rahman, Diaa Salama AbdElminaam

“…We have tuned hyperparameters of applied machine learning approaches, and cross-validation is applied to validate performance results. In addition, the complexity of the computation is measured. The proposed research aims to enhance the accuracy measure, and efficiency of identifying manipulated audio content, thereby contributing to the integrity and reliability of digital communications.…”
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SmartRipen: LSTM-GRU feature selection& XGBoost-CNN for fruit ripeness detection by Archana Ganesh Said, Bharti Joshi

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Research review on intelligent object detection technology for coal mines based on deep learning by Fan ZHANG, Jiarong ZHANG, Haixing CHENG

“…How to improve the accuracy, model adaptability, and computational efficiency of mine object detection is an urgent research topic in the field of mining artificial intelligence. …”
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CMCD: A Consistency Model-Based Change Detection Method for Remote Sensing Images by Xiongjie Li, Weiying Xie, Jiaqing Zhang, Yunsong Li

“…We also develop a pruning strategy of skip connections and a top–down feature aggregation module to improve feature utilization efficiency. Extensive experiments demonstrate that CMCD significantly reduces computational complexity and inference time compared to existing diffusion model-based methods. …”
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Hybrid Wavelet-Attention Model for Detecting Changes in High-Resolution Remote Sensing Images by Lhuqita Fazry, MGS M. Luthfi Ramadhan, Alif Wicaksana Ramadhan, Muhammad Febrian Rachmadi, Aprinaldi Jasa Mantau, Lukito Edi Nugroho, Chi-Hung Chi, Wisnu Jatmiko

“…However, this causes information loss, resulting in a trade-off between the effectiveness and efficiency of the method. To solve the problem, we developed a new change detection method called WaveCD. …”
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Multi-Scale Residual Convolutional Neural Network with Hybrid Attention for Bearing Fault Detection by Yanping Zhu, Wenlong Chen, Sen Yan, Jianqiang Zhang, Chenyang Zhu, Fang Wang, Qi Chen

“…This paper proposes an advanced deep convolutional neural network model for motor bearing fault detection that was designed to overcome the limitations of traditional models in feature extraction, accuracy, and generalization under complex operating conditions. …”
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A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM by Guoli Song, Zheng Huang, Yiwen Zhao, Xingang Zhao, Yunhui Liu, Min Bao, Jianda Han, Peng Li

“…However, it is a challenging task to detect the gliomas within the complex structure of the brain. …”
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Crystal structures of DCAF1-PROTAC-WDR5 ternary complexes provide insight into DCAF1 substrate specificity by Mark F. Mabanglo, Brian Wilson, Mahmoud Noureldin, Serah W. Kimani, Ahmed Mamai, Chiara Krausser, Héctor González-Álvarez, Smriti Srivastava, Mohammed Mohammed, Laurent Hoffer, Manuel Chan, Jamie Avrumutsoae, Alice Shi Ming Li, Taraneh Hajian, Sarah Tucker, Stuart Green, Magdalena Szewczyk, Dalia Barsyte-Lovejoy, Vijayaratnam Santhakumar, Suzanne Ackloo, Peter Loppnau, Yanjun Li, Almagul Seitova, Taira Kiyota, Jue George Wang, Gilbert G. Privé, Douglas A. Kuntz, Bhashant Patel, Vaibhavi Rathod, Anand Vala, Bhimsen Rout, Ahmed Aman, Gennady Poda, David Uehling, Jailall Ramnauth, Levon Halabelian, Richard Marcellus, Rima Al-awar, Masoud Vedadi

“…We report four DCAF1-based PROTACs with endogenous and exogenous WDR5 degradation effects and high-resolution crystal structures of the ternary complexes of DCAF1-PROTAC-WDR5. The structures reveal detailed insights into the interaction of DCAF1 with various WDR5-PROTACs, indicating a significant role of DCAF1 loops in providing needed surface plasticity, and reflecting the mechanism by which DCAF1 functions as a substrate receptor for E3 ligases with diverse sets of substrates.…”
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Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks by Ahmed Mateen Buttar, Zubair Shaheen, Abdu H. Gumaei, Mogeeb A. A. Mosleh, Mogeeb A. A. Mosleh, Indrajeet Gupta, Samah M. Alzanin, Muhammad Azeem Akbar

“…IntroductionNeurodegenerative diseases, including Parkinson’s, Alzheimer’s, and epilepsy, pose significant diagnostic and treatment challenges due to their complexity and the gradual degeneration of central nervous system structures. …”
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YOLOLS: A Lightweight and High-Precision Power Insulator Defect Detection Network for Real-Time Edge Deployment by Qinglong Wang, Zhengyu Hu, Entuo Li, Guyu Wu, Wengang Yang, Yunjian Hu, Wen Peng, Jie Sun

“…To address these issues, we propose YOLOLS, a lightweight and efficient detection model derived from YOLOv8n and optimized for real-time edge deployment. …”
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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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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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Real-Time Power System Event Detection: A Novel Instance Selection Approach by Gabriel Intriago, Yu Zhang

“…Wide-area monitoring, protection, and control (WAMPAC) systems allow system operators to operate CPPS more efficiently and reliably. WAMPAC systems use intelligent devices such as phasor measurement units (PMUs) to monitor the CPPS state. …”
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ABA-IDS: Attention-Based Autoencoder for Intrusion Detection in Assistive Mobility Robotic Network by Daniel Ayo Oladele, Elisha Didam Markus

“…This paper introduces ABA-IDS, a low-footprint IDS that uses a ConvLSTM autoencoder with an attention mechanism to detect anomalies in assistive mobility networks. The model’s design allows it to efficiently capture key spatial and temporal features of the network. …”
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Hybrid YOLOv8 and Fast R-CNN for Accurate Schematic Detection in Power Distribution Networks by Aviv Yuniar Rahman, Zuhaina Zakaria

“…Conventional edge detection methods often struggle with the complexity and scale of modern PDNs, while standalone deep learning approaches face challenges in balancing real-time performance and high precision. …”
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HSF-DETR: A Special Vehicle Detection Algorithm Based on Hypergraph Spatial Features and Bipolar Attention by Kaipeng Wang, Guanglin He, Xinmin Li

“…Experiments conducted on a self-built special vehicle dataset containing 2388 images demonstrate that HSF-DETR achieves mAP50 and mAP50-95 of 96.6% and 70.6%, respectively, representing improvements of 3.1% and 4.6% over baseline RT-DETR while maintaining computational efficiency at 59.7 GFLOPs and 18.07 M parameters. Cross-domain validation on VisDrone2019 and BDD100K datasets confirms the method’s generalization capability and robustness across diverse scenarios, establishing HSF-DETR as an effective solution for special vehicle detection in complex environments.…”
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