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Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images
Published 2023“…Considering these shortcomings, computational methods especially machine learning and deep learning algorithms are leveraged as an alternative to accelerate the accurate detection of CT scans as cancerous, and non-cancerous. …”
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS-A proposes a dynamic algorithm to compute the exact time for nodes cleansing states and restricts the exposure window of the nodes. …”
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Positive Unlabelled Learning to Recognize Dishes as Named Entity
Published 2019“…This research has the potential to be extended to other topics other than food and dish names, also it acts as a framework and algorithm independent.…”
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PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits
Published 2022“…Implications are that toxicity trigger detection algorithms can leverage generic approaches but must also tailor detections to specific communities.…”
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
Published 2023“…DL algorithms require data labeling and high-performance computers to effectively analyze and understand surveillance data recorded from fixed or mobile cameras installed in indoor or outdoor environments. …”
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Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures
Published 2017“…Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. …”
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Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques
Published 2024“…Various Deep Learning algorithms, including Convolution Neural Network (CNN), LeNet, and Inception-V3 are implemented to classify the records and extract various patterns. …”
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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…”
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Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices
Published 2024“…We conducted a comparative analysis of various models and algorithms used in the related works. The results indicated that our proposed approach outperforms others, showcasing its effectiveness in both detecting and mitigating DDoS attacks within SDNs. …”
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Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties
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Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic
Published 2025“…</p><h3>Methods</h3><p dir="ltr">Using Python® programming language, this study employed various supervised machine-learning algorithms, including parametric probabilistic models, such as logistic regression, and non-parametric models, including decision trees, random forest (RF), extra trees, AdaBoost, and k-nearest neighbours (KNN), using a dataset of non-transported patients (refused transport and did not receive treatment versus those who refused transport and received treatment) between 2018 and 2022. …”
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A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques
Published 2022“…Amongst the range of classification algorithms, support vector machines (SVMs) are heavily utilised for detecting phishing emails. …”
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From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors
Published 2021“…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. …”
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Nested ensemble selection: An effective hybrid feature selection method
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization
Published 2023“…In particular, the Proximity Policy Optimization (PPO) reinforcement algorithm is used to discover a policy for sensor selection that results in optimum sensor resource allocation. …”
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CEAP
Published 2016“…To reduce the overhead of the proposed detection model and make it feasible for the resource-constrained nodes, we reduce the size of the training dataset by (1) restricting the data collection, storage, and analysis to concern only a set of specialized nodes (i.e., Multi-Point Relays) that are responsible for forwarding packets on behalf of their clusters; and (2) migrating only few tuples (i.e., support vectors) from one detection iteration to another. We propose as well a propagation algorithm that disseminates only the final decisions (instead of the whole dataset) among clusters with the aim of reducing the overhead of either exchanging results between each set of vehicles or repeating the detection steps for the already detected malicious vehicles. …”
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Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases
Published 2024“…These AI algorithms are effective non-invasive biomarkers for cardiovascular illnesses because they can identify subtle patterns and signals in the ECG that may not be readily apparent to human interpreters. …”
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Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications
Published 2025“…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …”