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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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Firefly Optimization Algorithm

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Firefly algorithm is a swarm-based metaheuristic algorithm that was introduced by Yang. Firefly Algorithm is inspired by the FLASHING Behavior of Fireflies. 

Assumptions

  • Fireflies are attracted to each other.
  • Attractiveness is proportional to BRIGHTNESS. 
  • Less Brighter Firefly is attracted to the Brighter Firefly.
  • Attractiveness decrease as the distance between 2 fireflies increase.
  • If brightness for both is the same, fireflies move randomly.
  • New Solutions are generated by Random walks & the Attraction of fireflies.

Firefly Optimization Algorithm Steps
  1. Initialize Parameters.
  2. Generate Population of n Fireflies.
  3. Calculate Fitness Value for Each Firefly.
  4. Check stopping criteria if (CurrentIteration := 1 to MaximumIteration ).
  5.  Update Position and Light Intensity for Each Firefly.
  6. Report the Best Solution.
Initialize Parameters, Population of Fire Fly Swarm.
Population Size (n) = 20;
Maximum Iteration (Maxt) = 50;
Dimension (d) = 10;
Upper Bound [UB] = 100;
Lower Bound [LB] = -100;

Calculate Fitness Value [Light Intensity] for Each FireFly.
The light intensity of Firefly (i.e., 𝐼_𝑖) at 𝑥_𝑖 is computed by the Value of the Objective Function.

Firefly Position Updated as:
For i = 1 to n -1;
For j = i + 1 to n;
  IF ( 𝑰_𝒋 > 𝑰_𝒊 )
      Update Position. [move Firefly i towards Firefly j ];
    End IF
  End For
 End For

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