Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI by Tassilo Wald, Benjamin Hamm, Julius C. Holzschuh, Rami El Shafie, Andreas Kudak, Balint Kovacs, Irada Pflüger, Bastian von Nettelbladt, Constantin Ulrich, Michael Anton Baumgartner, Philipp Vollmuth, Jürgen Debus, Klaus H. Maier-Hein, Thomas Welzel

“…HAQ alone achieves about 40% of the performance improvements seen with SPACE images as input, allowing for fast and accurate, fully automated detection of small (< 1 cm) BMs. Relevance statement Training with higher-quality annotations, created using the SPACE sequence, improves the detection and delineation sensitivity of DL methods for the detection of brain metastases (BMs)on MPRAGE images. …”
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Sql injection detection using Naïve Bayes classifier: A probabilistic approach for web application security by Lu Zhexi

“…Using the Naive Bayes classifier, a probabilistic model specifically developed for text classification tasks, this work introduces a novel method for detecting SQL injection vulnerabilities.The process begins by collecting and organizing a comprehensive dataset, which includes both harmful and non-malicious SQL queries. …”
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SARS-COV-2 viral RNA detection through oligonucleotide-capped nanoporous anodic alumina supports. by Alba López-Palacios, María Nieves Aranda, Isabel Caballos, Andy Hernández-Montoto, Eva Calabuig, María Dolores Gómez-Ruiz, María Ángeles Tormo-Mas, Javier Pemán, Félix Sancenón, Ramón Martínez-Máñez, Elena Aznar, Estela Climent

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MLHI-Net: multi-level hybrid lightweight water body segmentation network for urban shoreline detection by Jianhua Ye, Pan Li, Yunda Zhang, Ze Guo, Shoujin Zeng, Youji Zhan

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Detection Schemes With Low-Resolution ADCs and Spatial Oversampling for Transmission With Higher-Order Constellations in Terahertz Band by Christian Forsch, Peter Zillmann, Osama Alrabadi, Stefan Brueck, Wolfgang Gerstacker

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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

“…Particle Swarm Optimization with Neural Network is being deployed to improve the efficiency of the detection method by more accurately predicting COVID-19 detection. …”
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LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers by Durmus Ozkan Sahin, Sedat Akleylek, Erdal Kilic

Subjects: “…permission-based android malware detection…”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

Subjects: “…Early diabetes detection…”
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How to Dissect Honey Bees (Apis mellifera L.) to Detect Tracheal Mites (Acarapis woodi Rennie) by John Bonkowski, Ashley N. Mortensen, James D. Ellis

“…ENY-164/IN1072: How to Dissect Honey Bees (Apis mellifera L.) to Detect Tracheal Mites (Acarapis woodi Rennie) (ufl.edu) …”
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Human milk whey proteins: Constituents, influencing factors, detection methods, and comparative analysis with other sources by Xing Li, Xiaomei Zhang, Minghui Zhang, Xiaojia Liu, Ziyue Gao, Junying Zhao, Weicang Qiao, Lijun Chen

“…Thirdly, it discusses detection methods for HM whey proteins, covering the principles, advantages, and limitations of different technical means. …”
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Design and Prototype of an Automatic Device Which Can Detect a Distribution Transformer that has Gone Off. by Ssebuma, Alex

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Automatic cervical lymph nodes detection and segmentation in heterogeneous computed tomography images using deep transfer learning by Wenjun Liao, Xiangde Luo, Lu Li, Jinfeng Xu, Yuan He, Hui Huang, Shichuan Zhang

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Development of a Sensitive Quantum Dot-Linked Immunoassay for the Multiplex Detection of Biochemical Markers in a Microvolumeric Format by Kalvaityte U, Bagdonas E, Kirdaite G, Kausaite-Minkstimiene A, Uzieliene I, Ramanaviciene A, Popov A, Butkiene G, Karabanovas V, Denkovskij J, Mobasheri A, Bernotiene E

“…The QLISA detection method included the formation of complexes consisting of analyte antigens, biotinylated antibodies and streptavidin-coated QDs. …”
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Environmental surveillance of SARS-CoV-2 for outbreak detection in hospital: A single centre prospective study by Hania Siddiqui, Alexandra M.A. Hicks, Aaron Hinz, Prachi Ray, Jennie Johnstone, Derek R. MacFadden, Jason A. Moggridge, Michael Fralick

“…Objective: To determine whether results from the environmental detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) from floor swabs could be provided to the Infection Prevention and Control (IPAC) team in near real-time. …”
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Analisis Kinerja Intrusion Detection System Berbasis Algoritma Random Forest Menggunakan Dataset Unbalanced Honeynet BSSN by Kuni Inayah, Kalamullah Ramli

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Sensitive ratiometric detection of Fumonisin B1 using a reusable Ag-pSi SERS platform by Narsingh R. Nirala, Sudharsan Sadhasivam, Rohit Kumar Singh, Edward Sionov, Giorgi Shtenberg

“…The bioassay included direct detection of fumonisin B1 (FB1), an abundant and widespread contaminant, by a specific aptamer sequence immobilized on the porous transducer. …”
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A ribodepletion and tagging protocol to multiplex samples for RNA-seq based virus detection: application to the cassava virome by Daniel H. Otron, Justin S. Pita, Murielle Hoareau, Fidèle Tiendrébéogo, Jean-Michel Lett, Pierre Lefeuvre

“…Nevertheless, the development of next generation sequencing (NGS) methods has revolutionized plant virus detection and identification. One NGS method that has been successfully used in virus detection and identification is ribodepleted RNA sequencing. …”
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SARS-CoV-2 not detected in pus from forearm abscess in a COVID-19-infected patient by Aprine Tan, Keng Lin Wong, Hamid Rahmatullah Bin Abd Razak, Biauw-Chi Ong, Merng Koon Wong

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A data-driven impedance estimation and matching method for high impedance fault detection and location of distribution networks by Zhenyu Zhang, Yong Li, Zhiyu Wang, Junle Liu, An Chen, Yijia Cao

Subjects: “…High impedance fault detection…”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…Challenges for credit card fraud monitoring include highly imbalanced datasets and the need for advanced models to detect fraud patterns. This paper introduced federated learning and discussed a few federated learning algorithms applied to the problem—these methods include Federated Graph Attention Network with Dilated Convolution Neural Network (FedGAT-DCNN), FedAvg with Convolutional Neural Network (CNN), and Federated Averaging with Distance-based Weighted Aggregation (FedAvg-DWA) with Random Forest (RF). …”
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