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AI and Deep Learning for Ear Infection Detection ~xRay Pixy

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Learn how AI and deep learning revolutionize ear infection detection, enabling accurate, fast, and automated diagnosis using advanced image processing and machine learning techniques. Video Chapters: Ear Infection Detection using AI and DL 00:00 Introduction 00:14 My Experience with Ear Infections 01:15 Topics Covered 02:24 Ear Infections 02:48 Ear Infection Signs 03:55 Ear Infection Preventions 04:29 Ear Infection Types 05:19 Ear Infection Causes 06:14 How Bacteria and Fungus Grow in Ear 07:26 My Mistakes 08:49 Doctors Advise after Ear Infection 09:45 Ear Infection Common Symptoms 10:37 Automated Ear Infection Detection with Deep Learning AI 15:09 Smartphone Otoscopes 16:04 Conclusion Ear fungus, also known as otomycosis , is a fungal infection of the outer ear canal. If an ear infection is not treated on time, it can lead to serious complications.  Hearing Loss – Persistent infections can damage the eardrum and middle ear structures, leading to partial or permanent hearing loss....
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Linear Congruential Generator | Modeling and Simulation |

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Random Number Generator Methods in Modeling and Simulation
1.) Middle Square Method for Random Number Generation (discussed before)
        Middle Square Method for Random Number Generation
2.) Linear Congruential Generator
        Linear Congruential generator |Modeling and Simulation|~xRay Pixy
Linear Congruential Generator is the most widely used method for Random Number Generation. Linear Congruential Generator Produce a sequence of integers between 0 and m-1.

Generate a Sequence of Random Numbers for (a, c, m) = (1, 5, 13) and Z0=1


Question For you


Video : Linear Congruential generator |Modeling and Simulation|~xRay Pixy
Video Link
https://youtu.be/h0qCg8hBfcE

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PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

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Cuckoo Search Algorithm for Optimization Problems

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 Particle swarm optimization (PSO) What is meant by PSO? PSO is a computational method that Optimizes a problem. It is a Population-based stochastic search algorithm. PSO is inspired by the Social Behavior of Birds flocking. n Particle Swarm Optimization the solution of the problem is represented using Particles. [Flocking birds are replaced with particles for algorithm simplicity]. Objective Function is used for the performance evaluation for each particle / agent in the current population. PSO solved problems by having a Population (called Swarms) of Candidate Solutions (Particles). Local and global optimal solutions are used to update particle position in each iteration. How PSO will optimize? By Improving a Candidate Solution. How PSO Solve Problems? PSO solved problems by having a Population (called Swarms) of Candidate Solutions (Particles). The population of Candidate Solutions (i.e., Particles). What is Search Space in PSO? It is the range in which the algorithm computes th...
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how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

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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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Whale Optimization Algorithm Code Implementation || WOA CODE || ~xRay Pixy

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