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Intelligent Traffic Management Using || AI & Metaheuristics || ~xRay Pixy

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Hybrid Artificial Intelligence and Metaheuristics for Smart City TRafci Management Problem Video Chapters: 00:00 Introduction 00:40 Smart Cities 01:14 Traditional Methods for Traffic Management 02:12 Hybrid Approach AI and Metaheuristics 02:47 STEPS for Hybrid  Traffic Management System 08:40 Advantages of Smart Traffic Management System 09:33 Conclusion
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What are the best algorithms for face detection in Matlab?

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The best algorithms for face detection in Matlab = Viola-Jones Algorithm
Face from the different digital images can be detected. The vision. CascadeObjectDetector uses the Viola-Jones algorithm to detect people’s Faces, Noses, Eyes, Mouth or upper body. The Cascade Object Detector build into MATLAB to detect the facial features from a digital image.
  • Detects the left and right eyes separately.
  • Detects the mouth.
  • Detect the objects using the viola jones algorithm.
  • Detect a pair of eyes.
  • Detects faces that are upright and forward-facing.
For Face detection:
faceDetector=vision.CascadeObjectDetector('FrontalFaceCART');
For Eyes detection:
faceDetector=vision.CascadeObjectDetector('EyePairBig’);
I Created a Face Detection system using Viola- Jones algorithm.
Book : Face and Facial Expression Recognition
LINK : Face Doctor - Viola Jones
LINK
Project | Face Detection using Polar Harmonic Transforms ~xRay Pixy

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PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

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Cuckoo Search Algorithm for Optimization Problems

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PSO Python Code || Particle Swarm Optimization in Python || ~xRay Pixy

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Particle Swarm Optimization Implementation in Python Video Chapters: 00:00 Introduction 02:01 Code 05:55 Position Initialization 08:06 PSO Main Loop 08:42 Velocity Calculation 10:02 Position Update 10:36 Fitness Evaluation 13:21 Objective Function 17:44 Result 19:00 Conclusion .....................................................SOURCE CODE......................................................................... import random import numpy as np from tkinter import messagebox #Define Class Particles class Particle: def __init__ (self,position): self.position=position self.velocity=np.zeros_like(position) self.best_position=position self.best_fitness=float('inf') def PSO(ObjF,Pop_Size,D,MaxT): swarm_best_position=None swarm_best_fitness=float('inf') particles=[] #Posotion Initialization position=np.random.uniform(-0.5,0.5,D) particle=Particle(position) particles.append(particle) #Fit
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Grey Wolf Optimization Algorithm

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how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

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Grey Wolf Optimization Algorithm Numerical Example

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