Search alternatives:
processing algorithm » processing algorithms (Expand Search)
learning algorithm » learning algorithms (Expand Search)
method algorithm » mould algorithm (Expand Search)
data learning » deep learning (Expand Search)
element » elements (Expand Search)
processing algorithm » processing algorithms (Expand Search)
learning algorithm » learning algorithms (Expand Search)
method algorithm » mould algorithm (Expand Search)
data learning » deep learning (Expand Search)
element » elements (Expand Search)
-
121
Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
Published 2022“…Federated Learning (FL) is a novel distributed privacy-preserving learning paradigm, which enables the collaboration among several participants (e.g., Internet of Things devices) for the training of machine learning models. …”
Get full text
Get full text
Get full text
masterThesis -
122
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…In the initial phase, the proposed HNIDS utilizes hybrid EGA-PSO methods to enhance the minor data samples and thus produce a balanced data set to learn the sample attributes of small samples more accurately. …”
-
123
-
124
-
125
-
126
-
127
Unsupervised histogram based color image segmentation
Published 2003“…Histograms are then computed, smoothed and downsampled. A peak picking algorithm finds the predominant peaks in the histograms. …”
Get full text
Get full text
article -
128
-
129
Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu
Published 2024Subjects: -
130
-
131
Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection
Published 2024“…Although Evolutionary Algorithms (EAs) have shown promise in the literature for feature selection, creating EAs for high dimensions is still challenging. …”
-
132
-
133
The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”
-
134
Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting
Published 2019“…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …”
-
135
Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices
Published 2025“…Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …”
-
136
-
137
-
138
TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…However, high dimensional data present a significant challenge for machine learning techniques. …”
-
139
-
140
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. …”