Iterative Assessment of Edge Criticality: Efficiency Enhancement or Hidden Insufficiency Detection by Vasily Lubashevskiy, Hamza Ejjbiri, Ihor Lubashevsky

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Automatic Pairwise Coarse Registration of Terrestrial Point Clouds Using 3D Line Features by Yongjian Fu, Zongchun Li, Feng Xiong, Hua He, Yong Deng, Wenqi Wang

“…Here, an automatic algorithm for pairwise coarse registration of TLS point clouds using 3D line features is proposed. …”
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A Hybrid Mechanism to Detect DDoS Attacks in Software Defined Networks by ÙAfsaneh Banitalebi Dehkordi, MohammadReza Soltanaghaei, Farsad Zamani Boroujeni

“…Given the importance of this issue,the purpose of this paper is to increase the accuracy of DDoS attack detection using the second order correlation coefficient technique based on â…-entropy according to source IP and selection of optimal features.To select the best features, by examining the types of feature selection algorithms and search methods, the WrapperSubsetEval feature selection algorithm, the BestFirst search method, and the best effective features were selected. …”
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Performance of predictive algorithms in estimating the risk of being a zero-dose child in India, Mali and Nigeria by Sebastian Bauhoff, John Tucker, Arpita Biswas

“…Furthermore, the algorithmic approach was able to detect ZD children across 176 more areas as compared with the geographical rule, for the same number of children targeted.Interpretation Predictive algorithms applied to existing data can effectively identify ZD children and could be deployed at low cost to target interventions to reduce ZD prevalence and inequities in vaccination coverage.…”
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Real-Time Fire Object Detection System Using Machine Learning by Akuthota Venkata Bhargavi., Syed Khadar Basha., Ramineni Dhanush., Guduru Vikram.

“…This paper introduces a fire object detection system that employs machine learning algorithms to enhance early detection of fire breakout and response to the same. …”
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Automatic Detection and Unsupervised Clustering-Based Classification of Cetacean Vocal Signals by Yinian Liang, Yan Wang, Fangjiong Chen, Hua Yu, Fei Ji, Yankun Chen

“…The proposed method automatically removes about 75% of clutter data from 1581.3MB of data in audio files and extracts 75.75 MB of the features detected by our algorithm. Four classical unsupervised clustering algorithms are performed on the datasets we made for verification and obtain an average accuracy rate of 84.83%.…”
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Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…Abstract Numerous contemporary computer-aided disease detection methodologies predominantly depend on feature engineering techniques; yet, they possess several drawbacks, including the presence of redundant features and excessive time consumption. …”
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Pengenalan Barang Pada Kereta Belanja Menggunakan Metode Scale Invariant Feature Transform (SIFT) by Ronny Makhfuddin Akbar, Nani Sunarmi

“…The algorithm proposed to detect and identify several items with image matching using Scale Invariant Feature Transform (SIFT). …”
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A Benchmark Dataset for Aircraft Detection in Optical Remote Sensing Imagery by Jianming Hu, Xiyang Zhi, Bingxian Zhang, Tianjun Shi, Qi Cui, Xiaogang Sun

“…The problem is that existing aircraft detection datasets rarely simultaneously consider the diversity of target features and the complexity of environmental factors, which has become an important factor restricting the effectiveness and reliability of aircraft detection algorithms. …”
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Radiomics-based machine learning for automated detection of Pneumothorax in CT scans. by Hanieh Alimiri Dehbaghi, Karim Khoshgard, Hamid Sharini, Samira Jafari Khairabadi, Farhad Naleini

“…This study addresses the pressing need for improved diagnostic accuracy in CT scans by developing an intelligent model that leverages radiomics features and machine learning techniques. By enhancing the detection of pneumothorax, this research aims to mitigate diagnostic errors and accelerate the process of image interpretation, ultimately improving patient outcomes. …”
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Cloud-edge collaborative data anomaly detection in industrial sensor networks. by Tao Yang, Xuefeng Jiang, Wei Li, Peiyu Liu, Jinming Wang, Weijie Hao, Qiang Yang

“…Second, there are complex spatial and temporal features in industrial sensor data. The full extraction of such features plays a key role in improving detection performance. …”
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IoT enabled health monitoring system using rider optimization algorithm and joint process estimation by J. Prabin Jose, G. Jaffino, Mohammed Al Awadh, Koppula Srinivas Rao, Yan Yafang, Krishna Moorthy Sivalingam

“…Abstract The timely detection of abnormal health conditions is crucial in achieving successful medical intervention and enhancing patient outcomes. …”
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RQPool: A Novel Multi-Branch Graph-Level Anomaly Detection by Aaron Alex Philip, Ziad Kobti

“…Moreover, existing Graph Neural Network (GNN) algorithms focus primarily on spatial domain features while neglecting spectral properties. …”
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Early Detection of Parkinson’s Disease Using AI Techniques and Image Analysis by Marilena Ianculescu, Corina Petean, Virginia Sandulescu, Adriana Alexandru, Ana-Mihaela Vasilevschi

“…The most innovative aspects of the presented approaches are related to the employed feature extraction techniques that convert hand-drawn spirals into a frequency spectra, so that frequency features may be extracted and utilized as inputs for various classification algorithms. …”
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Handling Class Imbalanced Data in Sarcasm Detection with Ensemble Oversampling Techniques by Ya-Han Hu, Ting-Hsuan Liu, Chih-Fong Tsai, Yu-Jung Lin

“…Traditional sentiment analysis struggles with sarcasm detection and class imbalance. To address this, we introduce Synthetic Ensemble Oversampling methods (SEO) that effectively leverage the strengths of various oversampling algorithms. …”
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An improved deep learning approach for automated detection of multiclass eye diseases by Feudjio Ghislain, Saha Tchinda Beaudelaire, Romain Atangana, Tchiotsop Daniel

“…In this study, we introduce a new lightweight algorithm based on CNNs for the classification of multiple categories of eye diseases, using discrete wavelet transforms to enhance feature extraction. …”
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An explainable transformer model for Alzheimer’s disease detection using retinal imaging by Saeed Jamshidiha, Alireza Rezaee, Farshid Hajati, Mojtaba Golzan, Raymond Chiong

“…These findings are compared to existing clinical studies on detecting AD using retinal biomarkers, allowing us to identify the most important features for AD detection in each imaging modality. …”
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Towards Effective Parkinson’s Monitoring: Movement Disorder Detection and Symptom Identification Using Wearable Inertial Sensors by Umar Khan, Qaiser Riaz, Mehdi Hussain, Muhammad Zeeshan, Björn Krüger

“…The proposed pipeline employs and evaluates manual feature crafting for classical machine learning algorithms, as well as an RNN-CNN-inspired deep learning model that does not require manual feature crafting. …”
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RF-Based UAV Detection and Identification Enhanced by Machine Learning Approach by Yash Vasant Ahirrao, Rana Pratap Yadav, Sunil Kumar

“…Machine learning algorithms are trained to make decisions based on these extracted features. …”
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GSB: GNGS and SAG-BiGRU network for malware dynamic detection. by Zhanhui Hu, Guangzhong Liu, Xinyu Xiang, Yanping Li, Siqing Zhuang

“…For solving the problem, this study proposed the GNGS algorithm to construct a new balance dataset for the model algorithm to pay more attention to the feature learning of the minority attacks' malware to improve the detection rate of attacks' malware. …”
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