Deep learning-assisted terahertz intelligent detection and identification of cancer tissue by Xingyu Wang, Yafei Xu, Rong Wang, Nuoman Tian, Zhengpeng Zhu, Shuting Fan, Liuyang Zhang, Ruqiang Yan, Xuefeng Chen

“…By combining the THz detection technique and artificial intelligence technique, here we propose a dense and efficient channel attention network (DECANet) framework-based THz diagnosis system for cancer prescreening. …”
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TARGE: large language model-powered explainable hate speech detection by Muhammad Haseeb Hashir, Memoona, Sung Won Kim

“…The proliferation of user-generated content on social networking sites has intensified the challenge of accurately and efficiently detecting inflammatory and discriminatory speech at scale. …”
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Anomaly detection in encrypted network traffic using self-supervised learning by Sadaf Sattar, Shumaila Khan, Muhammad Ismail Khan, Ainur Akhmediyarova, Orken Mamyrbayev, Dinara Kassymova, Dina Oralbekova, Janna Alimkulova

“…ET-SSL extends the use of SSL based traffic classification in order to improve detection performance while keeping computational complexity low through the maximization of the difference between normal and anomalous traffic. …”
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Multi-defect detection and classification for aluminum alloys with enhanced YOLOv8. by Ying Han, Xingkun Li, Gongxiang Cui, Jie Song, Fengyu Zhou, Yugang Wang

“…Experimental results show that the proposed method performs effectively in target detection and classification. The number of model parameters is reduced from more than 300,000 to 160,000, significantly reducing the complexity of the model. …”
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Lightweight Pepper Disease Detection Based on Improved YOLOv8n by Yuzhu Wu, Junjie Huang, Siji Wang, Yujian Bao, Yizhe Wang, Jia Song, Wenwu Liu

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A Lightweight and Rapid Dragon Fruit Detection Method for Harvesting Robots by Fei Yuan, Jinpeng Wang, Wenqin Ding, Song Mei, Chenzhe Fang, Sunan Chen, Hongping Zhou

“…To enhance detection accuracy and satisfy the deployment constraints of edge devices, we propose YOLOv10n-CGD, a lightweight and efficient dragon fruit detection method designed for robotic harvesting applications. …”
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LNT-YOLO: A Lightweight Nighttime Traffic Light Detection Model by Syahrul Munir, Huei-Yung Lin

“…Moreover, most of the recent works only focused on daytime scenarios, often overlooking the significantly increased risk and complexity associated with nighttime driving. To address these critical issues, this paper introduces a novel approach for nighttime traffic light detection using the LNT-YOLO model, which is based on the YOLOv7-tiny framework. …”
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AFENet: An Attention-Focused Feature Enhancement Network for the Efficient Semantic Segmentation of Remote Sensing Images by Jiarui Li, Shuli Cheng

“…The semantic segmentation of high-resolution remote sensing images (HRRSIs) faces persistent challenges in handling complex architectural structures and shadow occlusions, limiting the effectiveness of existing deep learning approaches. …”
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RRBM-YOLO: Research on Efficient and Lightweight Convolutional Neural Networks for Underground Coal Gangue Identification by Yutong Wang, Ziming Kou, Cong Han, Yuchen Qin

“…Coal gangue identification is the primary step in coal flow initial screening, which mainly faces problems such as low identification efficiency, complex algorithms, and high hardware requirements. …”
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Zwitterionic Poly(sulfobetaine methacrylate) Brushes Functionalized Threads for DNA Extraction from Complex Cell Lysates by Xianlong Shi, Liang Wu, Ke Ning, Xinmei Li, Lingke Feng, Yirong Chen, Ling Yu

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Effect of age on complexity and causality of the cardiovascular control: comparison between model-based and model-free approaches. by Alberto Porta, Luca Faes, Vlasta Bari, Andrea Marchi, Tito Bassani, Giandomenico Nollo, Natália Maria Perseguini, Juliana Milan, Vinícius Minatel, Audrey Borghi-Silva, Anielle C M Takahashi, Aparecida M Catai

“…We found that: 1) MF approaches are more efficient than the MB method when nonlinear components are present, while the reverse situation holds in presence of high dimensional embedding spaces; 2) the CE method is the least powerful in detecting age-related trends; 3) the association of HP complexity on age suggests an impairment of cardiac regulation and response to STAND; 4) the relation of SAP complexity on age indicates a gradual increase of sympathetic activity and a reduced responsiveness of vasomotor control to STAND; 5) the association from SAP to HP on age during STAND reveals a progressive inefficiency of baroreflex; 6) the reduced connection from HP to SAP with age might be linked to the progressive exploitation of Frank-Starling mechanism at REST and to the progressive increase of peripheral resistances during STAND; 7) at REST the diminished association from RESP to HP with age suggests a vagal withdrawal and a gradual uncoupling between respiratory activity and heart; 8) the weakened connection from RESP to SAP with age might be related to the progressive increase of left ventricular thickness and vascular stiffness and to the gradual decrease of respiratory sinus arrhythmia.…”
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Efficient collision-avoidance navigation strategy for autonomous surface vehicles in unstructured and constricted marine environments by Wenlong Meng, Rongdian Ku, Yanbo Pu, Xiaoxiao Shi, Ya Gong

“…In this study, we tackle the aforementioned complexities by incorporating progressive sampling and point cloud clustering, which jointly expedite the detection of constrained waterways in unstructured marine environments. …”
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Tunable Energy-Efficient Approximate Circuits for Self-Powered AI and Autonomous Edge Computing Systems by Shubham Garg, Kanika Monga, Nitin Chaturvedi, S. Gurunarayanan

“…Moreover, this problem becomes more complex while deploying computationally intensive heavy machine learning (ML) models on energy-constrained edge devices. …”
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Collaborative Optimization of Model Pruning and Knowledge Distillation for Efficient and Lightweight Multi-Behavior Recognition in Piglets by Yizhi Luo, Kai Lin, Zixuan Xiao, Yuankai Chen, Chen Yang, Deqin Xiao

“…In modern intensive pig farming, accurately monitoring piglet behavior is crucial for health management and improving production efficiency. However, the complexity of existing models demands high computational resources, limiting the application of piglet behavior recognition in farming environments. …”
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Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance by Mohsen Akbari, Ahmed Wasif Reza, Kamarul Ariffin Noordin, Kaharudin Dimyati, Mohsen Riahi Manesh, Mohammad Nour Hindia

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Efficient Gearbox Fault Diagnosis Based on Improved Multi-Scale CNN with Lightweight Convolutional Attention by Bin Yuan, Yaoqi Li, Suifan Chen

“…The framework extracts the multi-band features of vibration signals through the improved multi-scale convolutional neural network, which significantly enhances adaptability to complex working conditions (variable rotational speed, strong noise); at the same time, the lightweight convolutional attention mechanism is used to replace the multi-attention of the traditional Transformer, which greatly reduces computational complexity while guaranteeing accuracy and realizes highly efficient, lightweight local–global feature modeling. …”
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Image-Based Object Identification for Efficient Event-Driven Sensing in Wireless Multimedia Sensor Networks by Mohsin S. Alhilal, Adel Soudani, Abdullah Al-Dhelaan

“…This paper presents a contribution to the design of low complexity scheme based on object identification for efficient sensing of multimedia information in wireless multimedia sensor networks. …”
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A spoonful of L‐fucose—an efficient therapy for GFUS‐CDG, a new glycosylation disorder by René G Feichtinger, Andreas Hüllen, Andreas Koller, Dieter Kotzot, Valerian Grote, Erdmann Rapp, Peter Hofbauer, Karin Brugger, Christian Thiel, Johannes A Mayr, Saskia B Wortmann

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Enhanced pulmonary nodule detection using a transformer framework with dual fusion and gated mechanism by Kelei Sun, Yihang Wang, Huaping Zhou

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Research and optimization of a multilevel fire detection framework based on deep learning and classical pattern recognition techniques by Qi Liu, Hong Chen, Da Lin

“…Despite advancements in both traditional methodologies and modern deep learning models, challenges such as suboptimal accuracy and elevated false alarm rates persist, particularly in complex environmental scenarios. This paper introduces the Fire Focused Detection Network (FFDNet), a state-of-the-art flame detection framework that seamlessly integrates classical approaches with deep learning strategies. …”
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