Face Recognition project made in matlab using PCA algorithm
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Updated
Jan 23, 2014 - MATLAB
Face Recognition project made in matlab using PCA algorithm
This Repository contains scratch implementation of Soft Computing Lab practicals
application of neural networks
The cancer like lung, prostrate, and colorectal cancers contribute up to 45% of cancer deaths. So it is very important to detect or predict before it reaches to serious stages. If cancer predicted in its early stages, then it helps to save the lives. Statistical methods are generally used for classification of risks of cancer i.e. high risk or l…
int-246-project-Twinkle0799 created by GitHub Classroom
Academic softcomputing projects - traffic signs recognition with MLP, genetic algorithm.
With the aim of create a powerful trade-off between the concepts of exploitation and exploration, and rectify the complexity of their structural parameters in the standard IPO, a modified version of IPO (called MIPO) is introduced as an efficient optimization algorithm for digital infinite-impulse-response (IIR) filters model identification. The…
introduction to Soft Computing using Python Exercises
Design and modeling of adaptive IIR filtering systems using a weighted sum - variable length particle swarm optimization
Lab assignments of AI and Soft computing
A “Fuzzy Logic Toolbox” provides functions and apps for designing and simulating fuzzy logic systems. It lets the user specify and configure input variables, output variables, membership functions, rules and defuzzification methods.
In this paper, an attempt is made to leverage on novel metaheuristic optimization approaches for designing integrated navigation systems. For this purpose, a simplified version of the inclined planes system optimization (called SIPO) algorithm
LifeAI- Multiple Disease Detection Software
CSC703: Artificial Intelligence and Soft Computing [AISC] & CSL703: Artificial Intelligence and Soft Computing Lab [AISC Lab] <Semester VII>
Curated GitHub repository showcasing Data Science journals, covering diverse topics in data science and machine learning for exploration
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