Search Results - (( java segmentation using algorithm ) OR ( program reducing learning algorithm ))
Search alternatives:
- learning algorithm »
- java segmentation »
- reducing learning »
- program reducing »
- using algorithm »
-
1
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
Get full text
Get full text
Get full text
Get full text
Thesis -
2
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
Get full text
Get full text
Get full text
Book -
3
Development of seven segment display recognition using TensorFlow on Raspberry Pi
Published 2022Get full text
Get full text
Get full text
Get full text
Proceeding Paper -
4
A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…A matheuristic approach based on a reduced two-stage Stochastic Integer Linear Programming (SILP) model is presented. …”
Get full text
Get full text
Article -
5
Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network
Published 2019“…As the number of 2SAT clauses increased, the efficiency and effectiveness of the learning phase in HNN deteriorates. Swarm intelligence metaheuristic algorithm has been introduced to reduce the learning complexity of the network. …”
Get full text
Get full text
Thesis -
6
Developing an intelligent system to acquire meeting knowledge in problem-based learning environments
Published 2006“…MALESAbrain1-3 is an intelligent algorithm which originally is designed for problem-based learning (PBL) environment. …”
Get full text
Get full text
Get full text
Article -
7
Enhancing programming language learning with 3D game-based programming for MSU students: codadventure / Abdullah Adib Aditia Wirawan and Nur Suhana Mohd Redzo
Published 2024“…The project's objective is to reduce the common difficulties MSU students face in learning programming languages. …”
Get full text
Get full text
Conference or Workshop Item -
8
Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…The collected data is processed by a Gaussian filtering approach that eliminates irrelevant information, reducing the overfitting issues. Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
Get full text
Get full text
Article -
9
Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi
Published 2022“…The CNN method has been used in this study to detect children because the method can automatically learn pattern features and reduce the incompleteness caused by artificial design features. …”
Get full text
Get full text
Thesis -
10
Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail
Published 2021“…Python is an open source of programming software that conducted programming-based technique using the Scikit-Learn module to do the extraction of building from Land used land cover (LULC) and the result was 86.233% for overall accuracy. …”
Get full text
Get full text
Thesis -
11
Fuzzy rules reduction using rough set approach
Published 2003“…The purpose of modeling the student is to evaluate the students conceptual understanding (i.e. performance level and learning efficiency) in learning C programming language. …”
Get full text
Conference or Workshop Item -
12
A review on security and privacy issues in E-learning and the MapReduce aproach
Published 2019“…Then, we proposed e-Learning using MapReduce algorithm in protecting the security and privacy of eLearning. …”
Get full text
Get full text
Get full text
Article -
13
Evaluation of the accuracy of soft computing learning algorithms in performance prediction of tidal turbine
Published 2021“…This study shows that the application of the new procedure resulted in confident generality performance and learns faster than orthodox learning algorithms. In conclusion, the assessment indicated that the advanced Extreme Learning Machine simulation was capable as a promising alternative to existing numerical methods for computing the coefficient of performance for turbines. …”
Get full text
Get full text
Article -
14
Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
15
Learning analytic framework for students’ academic performance and critical learning pathways
Published 2024“…By providing a holistic perspective of student performance and course interactions, the proposed learning analytics framework holds great promise for educational institutions seeking data-driven strategies to enhance student outcomes and optimize learning experiences.…”
Get full text
Get full text
Get full text
Article -
16
Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments
Published 2017“…The problem of determining a smooth and collision-free path with maximum possible speed for a Mobile Robot (MR) which is chasing a moving target in a dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. …”
Get full text
Get full text
Article -
17
Deep Reinforcement Learning For Control
Published 2021“…To generate the visual simulation in the simulator, the Python programming language is employed. The improved algorithm will help encourage the real-world implementation of DRL in many autonomous driving applications.…”
Get full text
Get full text
Monograph -
18
-
19
-
20
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
Get full text
Get full text
Thesis
