Search alternatives:
learning algorithm » learning algorithms (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
past algorithm » jaya algorithm (Expand Search)
level learning » deep learning (Expand Search)
element » elements (Expand Search)
learning algorithm » learning algorithms (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
past algorithm » jaya algorithm (Expand Search)
level learning » deep learning (Expand Search)
element » elements (Expand Search)
-
1
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
Published 2022Get full text
doctoralThesis -
2
-
3
Estimating Construction Project Duration Using a Machine Learning Algorithm
Published 2024Get full text
Get full text
Get full text
masterThesis -
4
Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction
Published 2025“…The application of machine learning (ML) and deep learning (DL) models in the field of toxicity has gained burgeoning interest. …”
-
5
Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
-
6
Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic
Published 2021“…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. …”
Get full text
-
7
Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…According to the findings of several studies, the framework is significantly more effective than conventional methods in maintaining high levels of privacy. In addition, the framework outperforms conventional detection algorithms in words of detection rate, the rate of the false positive, and calculation time, respectively.…”
Get full text
Get full text
-
8
Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
Published 2021“…Each user participated in 500 trials at 10 different sessions (days) to replicate real-life signal variability. A machine learning classification pipeline is developed using multi-domain feature extraction (time, frequency, time-frequency), feature selection (Gini impurity), classifier design, and score level fusion. …”
-
9
Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”
-
10
Decision-level Gait Fusion for Human Identification at a Distance
Published 2014Get full text
doctoralThesis -
11
-
12
-
13
Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning
Published 2024Get full text
doctoralThesis -
14
Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”
-
15
-
16
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
Published 2023“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”
-
17
-
18
-
19
Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach
Published 2025“…The convolutional neural network is optimized using genetic algorithms, which dynamically tune hyper-parameters such as learning rate, batch size, and momentum to improve performance and generalizability across diverse environmental conditions. …”
-
20