Context-Aware Adaptive Encryption: Integrating Sensitive Data Detection and Network intrusion detection for Dynamic Data Security and Encryption by Leonardo C. Lawrence, Ramin Giovanni, Cynthia Calongne, Abdullah Alshboul

“…This research project develops and evaluates a novel context-aware adaptive encryption system that integrates sensitive data detection, network intrusion detection, and dynamic encryption techniques to enhance data security. …”
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A Low-Complexity Approach for Improving the Accuracy of Sensor Networks by Angelo Coluccia

“…Remarkably, the resulting cooperative algorithm does not require prior knowledge of the (hyper)parameters and is able to provide a “denoised” version of the monitored field without losing accuracy in detecting extreme (less frequent) values, which can be very important for a number of applications. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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Fast Photon-Counting Imaging With Low Acquisition Time Method by Kangjian Hua, Bo Liu, Zhen Chen, Huachuang Wang, Liang Fang, Jiang Yun

“…In this paper, we proposed a low acquisition time photon-counting imaging method based on two single element SPADs and pixel scanning structure. …”
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MODERN METHODS OF AUTOMATIC RECTANGLE OBJECTS DETECTION by E. S. Matusevich, I. E. Kheidorov

“…Low-level and high-level feature extraction methods and algorithms for the image formation of a rectangular object were considered. …”
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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.…”
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Lightweight blasthole image detection and positioning method by Shan PAN, Ting YU, Zhongwen YUE, Zijian TIAN, Qingyu JIN

“…To tackle the issues of large parameter size and low frames per second (FPS) in the blasthole image detection and localization algorithm network model, a lightweight Sc_C2f module is proposed to optimize the network structure. …”
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Low-dimensional multiscale fast SAR image registration method by Jiamu Li, Wenbo Yu, Zijian Wang, Jiaxin Xie, Xiaojie Zhou, Yabo Liu, Zhongjun Yu, Meng Li, Yi Wang

“…First, the candidate points are detected in the modulus map of phase congruency (PC). …”
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Fracture Detection in Traumatic Pelvic CT Images by Jie Wu, Pavani Davuluri, Kevin R. Ward, Charles Cockrell, Rosalyn Hobson, Kayvan Najarian

“…Manual detection of bone fracture from computed tomography (CT) images is very challenging due to low resolution of the images and the complex pelvic structures. …”
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Robustness evaluation of commercial liveness detection platform by Pengcheng WANG, Haibin ZHENG, Jianfei ZOU, Ling PANG, Hu LI, Jinyin CHEN

“…Liveness detection technology has become an important application in daily life, and it is used in scenarios including mobile phone face unlock, face payment, and remote authentication.However, if attackers use fake video generation technology to generate realistic face-swapping videos to attack the living body detection system in the above scenarios, it will pose a huge threat to the security of these scenarios.Aiming at this problem, four state-of-the-art Deepfake technologies were used to generate a large number of face-changing pictures and videos as test samples, and use these samples to test the online API interfaces of commercial live detection platforms such as Baidu and Tencent.The test results show that the detection success rate of Deepfake images is generally very low by the major commercial live detection platforms currently used, and they are more sensitive to the quality of images, and the false detection rate of real images is also high.The main reason for the analysis may be that these platforms were mainly designed for traditional living detection attack methods such as printing photo attacks, screen remake attacks, and silicone mask attacks, and did not integrate advanced face-changing detection technology into their liveness detection.In the algorithm, these platforms cannot effectively deal with Deepfake attacks.Therefore, an integrated live detection method Integranet was proposed, which was obtained by integrating four detection algorithms for different image features.It could effectively detect traditional attack methods such as printed photos and screen remakes.It could also effectively detect against advanced Deepfake attacks.The detection effect of Integranet was verified on the test data set.The results show that the detection success rate of Deepfake images by proposed Integranet detection method is at least 35% higher than that of major commercial live detection platforms.…”
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Concealed Weapon Detection Using Thermal Cameras by Juan D. Muñoz, Jesus Ruiz-Santaquiteria, Oscar Deniz, Gloria Bueno

“…Key contributions include a lightweight algorithm optimized for low-end embedded devices, making it suitable for wearable and mobile applications, and the creation of a tailored thermal dataset for controlled concealment scenarios. …”
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Multiscale Convolutional Neural Networks for Hand Detection by Shiyang Yan, Yizhang Xia, Jeremy S. Smith, Wenjin Lu, Bailing Zhang

“…Developed from the region-based CNN (R-CNN) model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. …”
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Complex Indoor Human Detection with You Only Look Once: An Improved Network Designed for Human Detection in Complex Indoor Scenes by Yufeng Xu, Yan Fu

“…However, the complex indoor environment and background pose challenges to the detection task. The YOLOv8 algorithm is a cutting-edge technology in the field of object detection, but it is still affected by indoor low-light environments and large changes in human scale. …”
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MRP-YOLO: An Improved YOLOv8 Algorithm for Steel Surface Defects by Shuxian Zhu, Yajie Zhou

“…This study proposes a novel method for steel defect detection based on the YOLO v8 algorithm, which improves detection accuracy while maintaining low computational complexity. …”
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DETECTION OF SOMATIC MUTATIONS IN THE BRAF GENE BY PYROSEQUENCING by O. P. Dribnokhodova, E. A. Dunaeva, G. V. Leshkina, E. A. Yarygina, A. Yu. Bukharina, Ya. A. Voiciehovskaya, E. V. Borisova, S. K. Bormotova, A. I. Daoud, V. N. Khlavich, K. O. Mironov

“…The pyrogram signal values for samples without mutations ranged from 0 to 19.5 % for different mutations. An analysis algorithm was developed to confirm the presence and differentiation of mutations in the 600 codon at a low proportion of the mutant allele based on the signals ratio on the pyrogram. …”
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Accurate and efficient insulator maintenance: A DETR algorithm for drone imagery. by Yanfeng Tian, Rodina Binti Ahmad, Nor Aniza Binti Abdullah

“…To address these challenges and achieve a more accurate inspection system, this manuscript introduces an insulator defect detection algorithm tailored for the low-quality images collected by drone-based imaging systems. …”
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Quantifying the Impact of Environmental Factors on the Methane Point-Source Emission Algorithm by Zixuan Wang, Linxin Wang, Ding Li, Lingjing Yang, Lixue Cao, Qin He, Kai Qin

“…The results offer critical insights for refining CH₄ detection algorithms and enhancing the precision of satellite-based inversions for low-concentration CH₄ point-source emissions.…”
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Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNs by Joon-Ik Kong, Jin-Woo Kim, Doo-Seop Eom

“…In this paper, we propose an energy-efficient clustering algorithm that can respond rapidly to unexpected events with increased energy efficiency, because each sensor node detects events individually and creates clusters using a regional competition scheme. …”
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INTERACTIVE ALGORITHM FOR SELECTION OF LINEAR OBJECTS ON AERIAL PHOTOGRAPHS AND SATELLITE IMAGES by Э. Н. Seredin, B. A. Zalesky

“…The algorithm provides fast detection of linear objects,it is easy tuned and convenient for practical use. …”
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Fibre tracing in biomedical images: An objective comparison between seven algorithms. by Youssef Arafat, Cristina Cuesta-Apausa, Esther Castellano, Constantino Carlos Reyes-Aldasoro

“…Trace Ridges is a fully automatic and fast algorithm that combines a series of image-processing algorithms including filtering, watershed transform and edge detection to obtain an accurate delineation of the fibre-like structures in a rapid time. …”
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