Search alternatives:
learning algorithm » learning algorithms (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
level learning » deep learning (Expand Search)
ii algorithm » rd algorithm (Expand Search), _ algorithms (Expand Search)
learning algorithm » learning algorithms (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
level learning » deep learning (Expand Search)
ii algorithm » rd algorithm (Expand Search), _ algorithms (Expand Search)
-
41
FPGA-Based Network Traffic Classification Using Machine Learning
Published 2020“…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. …”
Get full text
article -
42
An efficient approach for textual data classification using deep learning
Published 2022“…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”
-
43
FPGA-Based Network Traffic Classification Using Machine Learning
Published 2019Get full text
doctoralThesis -
44
The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…</p><h3>Objective</h3><p dir="ltr">This review aims to explore the machine learning algorithms used for the detection and diagnosis of bipolar disorder and its subtypes.…”
-
45
Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
Published 2024“…Furthermore, this study also focuses on different Machine learning algorithms that are used to secure wireless sensor networks. …”
-
46
AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics
Published 2022“…AGEomics biomarkers have been used in diagnostic algorithms using machine learning methods. In this review, I describe the utility of AGEomics biomarkers and provide evidence why these are close to the phenotype of a condition or disease compared to other metabolites and metabolomic approaches and how to train and test algorithms for clinical diagnostic and screening applications with high accuracy, sensitivity and specificity using machine learning approaches.…”
-
47
Developing a UAE-Based Disputes Prediction Model using Machine Learning
Published 2022Get full text
doctoralThesis -
48
Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
doctoralThesis -
49
-
50
Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data
Published 2024“…The analysis examined an eLearning lesson with 153 records and 51 participants, it concluded that blooms-level and pre-assessments are reliable predictors of student performance. …”
Get full text
-
51
-
52
Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper
Published 2025“…</p><h3>Results</h3><p dir="ltr">Machine learning models can potentially enhance healthcare patient–nurse assignments by considering skill integration, acuity level assessment and cultural and language barrier awareness. …”
-
53
Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
Published 2017Get full text
doctoralThesis -
54
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. …”
-
55
Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering
Published 2024“…A self-organizing map is one of the well-known unsupervised neural network algorithms used for preserving typologies during mapping from the input space (high-dimensional) to the display (low-dimensional).An algorithm called Local Adaptive Receptive Field Dimension Selective Self-Organizing Map 2 is a modified form of a self-organizing Map to cater different data types in the dataset. …”
-
56
Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework
Published 2022“…Firstly, the DL agent prioritizes caching contents via self organizing maps (SOMs) algorithm, and secondly, the prioritized contents are stored in QMM using a Two-Level Spin Quantum Phenomenon (TLSQP). …”
-
57
A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…<p dir="ltr">Regular monitoring of glycated hemoglobin (HbA1c) levels is important for the proper management of diabetes. …”
-
58
Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…Statistical analysis and machine learning can play a vital role in detecting the anomalies in the data, which enhances the security level of the smart home IoT system which is the goal of this paper. …”
-
59
A Survey of Data Clustering Techniques
Published 2023“…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
Get full text
Get full text
Get full text
masterThesis -
60
Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”