Molecular imprinting and nanomaterial synergy for lactate detection by Christopher Animashaun, Gymama Slaughter

“…Key fabrication strategies, such as electropolymerization, green nanomaterial synthesis, and surface imprinting, are critically examined for their roles in optimizing imprinting sensitivity and electron transfer efficiency. Application areas span real-time lactate monitoring in wearable health devices to environmental surveillance in complex matrices. …”
Get full text

Automated anomaly detection of IPTV user experience by Xiaomin TAN, Ai FANG, Duo JIN, Changjiang LI

“…The practice indicates that the algorithm with low calculation cost adapts to abnormal changes in the network and detect anomalies accurately and quickly, which reduces labor costs, improves operation efficiency and promotes intelligent operation.…”
Get full text

An overview of ahead geological detection technologies in tunnels by Dingchao Chen, Xiangyu Wang, Jianbiao Bai, Yuan Chu, Xian Wang, Jiaxin Zhao, Menglong Li

“…The rapid advancement of ahead geological detection technologies has been crucial to addressing the challenges posed by complex underground environments in tunnel construction. …”
Get full text

Research on lidar target detection for metro scene by PAN Wenbo, LI Cheng, YUAN Xiwen, LONG Teng, ZENG Xiang, XIE Guotao

“…Aiming at the problems of difficult real-time construction of train running forward boundary and complex cluster detection of unstructured track and road environment targets, a lidar based on target detection and forward boundary real-time construction system was proposed. …”
Get full text

A one-stage anchor-free keypoints detection model for fast electric vehicle charging port detection and pose extraction by Feifei Hou, Qiwen Meng, Xinyu Fan, Yijun Wang

“…Experiments demonstrate that in complex lighting scenarios, FasterEVPoints boasts 95% detection accuracy on a proprietary dataset with a positioning error of less than 2 cm at a 50 cm distance. …”
Get full text

Advanced Object Detection for Maritime Fire Safety by Fazliddin Makhmudov, Sabina Umirzakova, Alpamis Kutlimuratov, Akmalbek Abdusalomov, Young-Im Cho

“…To address the specific challenges of shipboard fire and smoke detection, such as varying lighting conditions, occlusions, and the complex structure of ships, we enhance the baseline DETR model by integrating EfficientNet-B0 as the backbone. …”
Get full text

BERT-based network for intrusion detection system by Yong Yang, Xing Peng

“…Abstract The rising complexity of cyberattacks poses significant challenges to traditional intrusion detection system (IDS). …”
Get full text

Anatomy of Deep Learning Image Classification and Object Detection on Commercial Edge Devices: A Case Study on Face Mask Detection by Dimitrios Kolosov, Vasilios Kelefouras, Pandelis Kourtessis, Iosif Mporas

“…Developing efficient on-the-edge Deep Learning (DL) applications is a challenging and non-trivial task, as first different DL models need to be explored with different trade-offs between accuracy and complexity, second, various optimization options, frameworks and libraries are available that need to be explored, third, a wide range of edge devices are available with different computation and memory constraints. …”
Get full text

Hierarchical Information-guided robotic grasp detection by Zeyao Hou, Yueran Zhao, Yutao Jin, Chao Yang, Zongyu He, Xiaoyan Chen

“…Abstract With the advancement of deep learning, robotic grasping has seen widespread application in fields, becoming a critical component in enhancing automation. Accurate and efficient grasping capabilities not only significantly boost productivity but also ensure safety and reliability in complex and dynamic environments. …”
Get full text

Research on YOLOv5 Oracle Recognition Algorithm Based on Multi-Module Fusion by Xinhang Zhang, Zhenhua Ma, Yaru Zhang, Huiying Ru

“…Detect_Efficient further improves the model’s detection and recognition capabilities. …”
Get full text

Intrusion detection method for IoT in heterogeneous environment by LIU Jing, MU Zelin, LAI Yingxu

“…In order to address the issue of inadequate training efficiency and subpar model performance encountered by Internet of things (IoT) devices when dealing with resource constraints and non-independent and identically distributed (Non-IID) data, a novel personalized pruning federated learning frame work for IoT intrusion detection was put forth. …”
Get full text

Optimized Faster R-CNN with Swintransformer for Robust Multi-Class Wildfire Detection by Sugi Choi, Sunghwan Kim, Haiyoung Jung

“…Wildfires are a critical global threat, emphasizing the need for efficient detection systems capable of identifying fires and distinguishing fire-related from non-fire events in their early stages. …”
Get full text

Detecting Signatures of Criticality Using Divergence Rate by Tenzin Chan, De Wen Soh, Christopher Hillar

“…In biology especially, these signatures of criticality are thought to be connected with efficient computation and information processing. Guided by the classical theory of rate–distortion (RD) from information theory, we propose a measure for detecting and characterizing such phenomena from data. …”
Get full text

Enhanced Multi-Class Detection of Fake News by Chih-yuan Li, Soon Ae Chun, James Geller

“…The result indicates notable limitations in ChatGPT's automated classification, which highlights the complexities of AI-based categorization. Our findings demonstrate the CNN model's efficiency and effectiveness, and show the intricacies of fake news detection. …”
Get full text

Steel Defect Detection Based on YOLO-SAFD by Feihong Yu, Jinshan Zhang, Dingdiao Mu

“…Experimental results on the NEU-DET dataset demonstrate that YOLO-SAFD achieves a detection precision of 0.83, a recall of 0.75, and an mAP50:95 of 0.43, outperforming the baseline YOLOv5 and highlighting its superior detection accuracy and efficiency for real-time industrial applications.…”
Get full text

Lightweight framework for misbehavior detection in internet of vehicles by Yujing Gong, Bin-Jie Hu

“…Despite LTC and CFC having significantly fewer parameters, making them less complex and more space-efficient than CNN-LSTM, the latter proves to be more time-efficient. …”
Get full text

Examining the Efficiency of Learning-Based Algorithms in the Process of Declaring Customs by Mustafa Günerkan, Ender Şahinaslan, Önder Şahınaslan

“…In the face of the diversity, dynamism, and complexity of the methods used in creating this declaration, human-induced declaration files are produced erroneously. …”
Get full text

Real-Time Stringing Detection for Additive Manufacturing by Oumaima Charia, Hayat Rajani, Inés Ferrer Real, Miquel Domingo-Espin, Nuno Gracias

“…To address data scarcity in training machine learning models, we also release a new dataset and improve upon the results achieved by the Obico server model, one of the most prominent tools for stringing detection. Our contributions aim to enhance process reliability, reduce material wastage, and optimize time efficiency in AM workflows.…”
Get full text

Audio Deepfake Detection Using Deep Learning by Ousama A. Shaaban, Remzi Yildirim

“…ABSTRACT This study introduces an enhanced Siamese convolutional neural network (Siamese CNN) architecture with a novel StacLoss function and self‐attention modules for efficient identification of audio deepfakes. Our module directly compares unprocessed original audio with modified audio by initially applying convolutional operations and dual branches to extract complex characteristics from raw audio signals. …”
Get full text

Pupil Detection Algorithm Based on ViM by Yu Zhang, Changyuan Wang, Pengbo Wang, Pengxiang Xue

“…This algorithm introduces weighted feature fusion, aiming to enable the model to adaptively learn the contribution of different feature patches to the pupil detection results; combines ViM with the MSA (multi-head self-attention) mechanism), aiming to integrate global features and improve the accuracy and robustness of pupil detection; and uses FFT (Fast Fourier Transform) to convert the time-domain vector outer product in MSA into a frequency–domain dot product, in order to reduce the computational complexity of the model and improve the detection efficiency of the model. …”
Get full text