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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 Algorithm Step-by-Step with Numerical Example [PART - 2]

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Firefly Algorithm


Firefly algorithm is a swarm-based metaheuristic algorithm that was introduced by Yang. Firefly algorithm is used for solving optimization problems. In this video, you will learn the Firefly algorithm with an example.
Firefly Algorithm is inspired by the FLASHING Behavior of Fireflies.
For simplicity certain Assumptions used in Firefly Optimization Algorithm: -
1.) Fireflies are attracted to each other. 2) Attractiveness is proportional to BRIGHTNESS. 3.) Less Brighter Firefly is attracted to the Brighter Firefly. 4.) Attractiveness decrease as the distance between 2 fireflies increase. 5.) If the brightness for both is the same, fireflies move randomly. 6.) New Solutions are generated by Random walks & the Attraction of fireflies.

Firefly Optimization Algorithm Steps:
Initialize Parameters
Initialize Population randomly in the search space.
Compute Fitness values and select the best solution.
Check Stopping Criteria.
While Current Iteration = 1:Maximum Iteration for i=1:Population Size for j=1:Population Size If ( Light Intensity(j) < Light Intensity(i) Move Firefly i towards j. Else Move i Randomly. End If Update New Position and Light Intensity. end end Check new solutions are within bound or not. Merge Population Sort Population Rank Fireflies according to their light intensity Find Best Solution Ever Found Damp Mutation Ratio end

#Metaheuristic #Algorithms
Meta-heuristic Algorithms
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