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Avascular Necrosis (AVN) || Early Detection, Better Outcomes || ~xRay Pixy

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Avascular Necrosis (AVN) is a condition where blood flow to the bone is reduced, causing bone cells to die. This leads to pain, joint damage, and difficulty in movement, especially in the hip. Early diagnosis and proper treatment can prevent permanent bone damage and improve quality of life. Video Chapter: AVN 00:00 Introduction 00:45 What is AVN? 01:55 About Bone Tissue 02:49 AVN Causes 03:38 AVN Symptoms 04:11 AVN Diagnosis 04:56 AVN of femoral head 05:33 How AVN Develops 07:28 Conclusions #optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python #optimizationproblem #optimizationalgorithms 
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Crow Search Algorithm (CSA) / Crow Search Optimization (CSO) Algorithm

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What is the Crow search algorithm?

Crow search algorithm (CSA) is a population-based algorithm. Crow search algorithm is similar to Particle Swarm Optimization (PSO) algorithm. Crow search algorithm mimics the crow's intellegent behavior. CSA is based on crow's intelligent behavior. 

Key Point About Crow's

Crows live in large families and care for younger ones. They eat insects, worms, nuts, fruits, food, birds, non-insects, etc. They can hide excess food in hiding places and retrieve it when needed. Age: 14-17 years.

Crow can memorize the hiding place positions.

They follow each other to steal their food.

Crows protect their hiding places from attackers.

Two main parameters used in the CSA algorithm:

Flights Length,

Awareness Probability. 

Crow Search Optimization Algorithm Main Concepts 

Crow store excess food in hiding places and retrieve it when needed. 

Crow cheat each other (i.e., they steal each other food).


Crow Search Algorithm Step-by-Step with Example ~xRay Pixy

Crow search algorithm Video Link : Crow search algorithm

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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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Particle Swarm Optimization (PSO)

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

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

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

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GWO Python Code || Grey Wolf Optimizer in Python || ~xRay Pixy

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