Hyperbolic geometry enhanced feature filtering network for industrial anomaly detection by Yanjun Feng, Jun Liu, Yonggang Gai

“…The visual perception algorithms have become extensively utilized in surface defect detection, progressively replacing manual inspection methods. …”
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Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection by Yu Wang, Hailan Huang, Bin Wu

“…Watershed segmentation and optimal thresholding algorithms were applied to extract the road network data of these five cities. …”
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Isfahan Artificial Intelligence Event 2023: Macular Pathology Detection Competition by Farnaz Sedighin, Maryam Monemian, Zahra Zojaji, Ahmadreza Montazerolghaem, Mohammad Amin Asadinia, Seyed Mojtaba Mirghaderi, Seyed Amin Naji Esfahani, Mohammad Kazemi, Reza Mokhtari, Maryam Mohammadi, Mohadese Ramezani, Mahnoosh Tajmirriahi, Hossein Rabbani

“…Researchers tested their algorithms and competed for the best classification results. …”
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Tree Slicing in Clone Detection: Syntactic Analysis Made (Semi)-Semantic by Marat Akhin, Vladimir Itsykson

“…We propose to reinforce traditional tree-based clone detection algorithms by using additional information about variable slices. …”
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Image-based maturity detection for selective cauliflower harvesting in field condition by Ajay Kushwah, P.K. Sharma, H.L. Kushwaha, Brij Bihari Sharma, Naseeb Singh, Ramineni Harsha Nag, Manojit Chowdhury, Nrusingh Charan Pradhan, Gopal Carpenter, Silpa Mandal, Ali Salem

“…The present study developed a cauliflower curd maturity detection system for a selective cauliflower harvester. …”
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An optimized ensemble model with advanced feature selection for network intrusion detection by Afaq Ahmed, Muhammad Asim, Irshad Ullah, Zainulabidin, Abdelhamied A. Ateya

“…To address this challenge, our study presents the “Optimized Random Forest (Opt-Forest),” an innovative ensemble model that combines decision forest approaches with genetic algorithms (GAs) for enhanced intrusion detection. The genetic algorithms based decision forest construction offers notable benefits by traversing a wider exploration space and mitigating the risk of becoming stuck in local optima, resulting in the discovery of more accurate and compact decision trees. …”
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NSDLib: A comprehensive python library for network source detection and evaluation by Damian Frąszczak, Edyta Frąszczak

“…It is easy to integrate and offers a range of algorithms for source detection, including evaluating node importance, identifying outbreaks, and reconstructing propagation graphs. …”
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NOVEL METHODS FOR AUTOANTIBODY DETECTION IN LABORATORY DIAGNOSTICS OF AUTOIMMUNE RHEUMATIC DISEASES by D. Roggenbuck, P. Schierac, U. Sack, S. V. Lapin, A. V. Mazing, Areg A. Totolian

“…Autoantibodies are well-established biomarkers of autoimmune rheumatic diseases. Their detection in the routine clinical laboratory provides key information for early and differential diagnosis, prognosis, and monitoring of disease-activity. …”
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Policy conflict detection in software defined network by using deep learning by Chuanhuang LI, Cheng CHENG, Xiaoyong YUAN, Lijie CEN, Weiming WANG

“…In OpenFlow-based SDN(software defined network),applications can be deployed through dispatching the flow polices to the switches by the application orchestrator or controller.Policy conflict between multiple applications will affect the actual forwarding behavior and the security of the SDN.With the expansion of network scale of SDN and the increasement of application number,the number of flow entries will increase explosively.In this case,traditional algorithms of conflict detection will consume huge system resources in computing.An intelligent conflict detection approach based on deep learning was proposed which proved to be efficient in flow entries’ conflict detection.The experimental results show that the AUC (area under the curve) of the first level deep learning model can reach 97.04%,and the AUC of the second level model can reach 99.97%.Meanwhile,the time of conflict detection and the scale of the flow table have a linear growth relationship.…”
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Optimizing Convolution Operations for YOLOv4-based Object Detection on GPU by Guerrouj Fatima Zahra, Rodríguez Flórez Sergio, El Ouardi Abdelhafid, Abouzahir Mohamed, Ramzi Mustapha

“…Real-time object detection is crucial for autonomous vehicles, and YOLO (You Only Look Once) algorithms have demonstrated their effectiveness for this purpose. …”
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Moving Vehicles Detection and Tracking on Highways and Transportation System for Smart Cities by Manoj Kumar, Susmita Ray, Dileep Kumar Yadav

“…Various machine learning and artificial intelligence based techniques are evolving with numerous advancement in this domain. These algorithms are efficient and very less time consuming. …”
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The Effects of Motion on Distributed Detection in Mobile Ad Hoc Sensor Networks by Xusheng Sun, Edward J. Coyle

“…These results allow rapid characterization of the time-dependence of distributed detection algorithms that are executed in mobile sensor networks.…”
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Method for Vocal Fold Paralysis Detection Based on Perceptual and Acoustic Assessment by Rafał HALAMA, Krzysztof SZKLANNY, Danijel KORŽINEK

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Emergent Technologies in Human Detection for Disaster Response: A Critical Review by Sajjad Ahmed

“…These methods are specifically designed to detect human presence in disaster scenarios by leveraging principles from electromagnetic, acoustic, AI-based algorithms, gas sensors, and optical detection. …”
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Dual-modal edible oil impurity dataset for weak feature detection by Huiyu Wang, Qianghua Chen, Jianding Zhao, Liwen Xu, Ming Li, Ying Zhao, Qinpei Zhao, Qin Lu

“…To prove the usability of the dataset, four object detection algorithms are applied and compared.…”
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Enhancing cyber threat detection with an improved artificial neural network model by Toluwase Sunday Oyinloye, Micheal Olaolu Arowolo, Rajesh Prasad

“…Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems (IDS). Data labeling difficulties, incorrect conclusions, and vulnerability to malicious data injections are only a few drawbacks of using machine learning algorithms for cybersecurity. …”
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A network intrusion detection method designed for few-shot scenarios by Weichen HU, Congyuan XU, Yong ZHAN, Guanghui CHEN, Siqing LIU, Zhiqiang WANG, Xiaolin WANG

“…Existing intrusion detection techniques often require numerous malicious samples for model training.However, in real-world scenarios, only a small number of intrusion traffic samples can be obtained, which belong to few-shot scenarios.To address this challenge, a network intrusion detection method designed for few-shot scenarios was proposed.The method comprised two main parts: a packet sampling module and a meta-learning module.The packet sampling module was used for filtering, segmenting, and recombining raw network data, while the meta-learning module was used for feature extraction and result classification.Experimental results based on three few-shot datasets constructed from real network traffic data sources show that the method exhibits good applicability and fast convergence and effectively reduces the occurrence of outliers.In the case of 10 training samples, the maximum achievable detection rate is 99.29%, while the accuracy rate can reach a maximum of 97.93%.These findings demonstrate a noticeable improvement of 0.12% and 0.37% respectively, in comparison to existing algorithms.…”
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Detecting and Explaining Postpartum Depression in Real-Time with Generative Artificial Intelligence by Silvia García-Méndez, Francisco de Arriba-Pérez

“…Consequently, the rapid detection of PPD and their associated risk factors is critical for in-time assessment and intervention through specialized prevention procedures. …”
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Embedded Vision System for Thermal Face Detection Using Deep Learning by Isidro Robledo-Vega, Scarllet Osuna-Tostado, Abraham Efraím Rodríguez-Mata, Carmen Leticia García-Mata, Pedro Rafael Acosta-Cano, Rogelio Enrique Baray-Arana

“…Face detection technology is essential for surveillance and security projects; however, algorithms designed to detect faces in color images often struggle in poor lighting conditions. …”
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Research on the Computed Tomography Pebble Flow Detecting System for HTR-PM by Xin Wan, Ximing Liu, Jichen Miao, Peng Cong, Yuai Zhang, Zhifang Wu

“…Algorithms to automatically locate the three-dimensional coordinates of tracer pebbles and to rebuild the trajectory of each tracer pebble were presented and verified. …”
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