Video Link Multi-Block Local Binary Pattern || Calculate LBP Corner Pixel Values || https://youtu.be/o8qfJWQ_FG0 Local Binary Patterns (LBP) is a simple and efficient technique used in image processing to describe the texture or patterns within an image. LBP is widely used for applications like face recognition and texture classification since it is easy to compute and very effective at capturing the texture in photos. Step How LBP WORKS: For each pixel in the image, LBP looks at the pixel’s neighbors, typically the 8 pixels surrounding it in a 3x3 grid. LBP compares each of these neighboring pixels with the center pixel. If the neighboring pixel has a value greater than or equal to the center pixel, it's marked as 1; otherwise, it's marked as 0. This comparison forms a binary number for the pixel. The binary number is then converted into a decimal value. This value represents the texture pattern at that pixel. By doing this for every pixel in the image, LBP creates a new
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BAT ALGORITHM || PYTHON CODE || ~xRay Pixy
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Learn Bat Algorithm Implementation in Python. Video Chapters: Bat Algorithm 00:00 Introduction 00:42 Bat Algorithm Key Concepts 01:58 Bat Algorithm Pseudocode 02:35 Objective Function 02:49 Parameters 03:09 Python Code 06:30 BA Main Loop Start 12:30 Result The Bat Algorithm is a nature-inspired optimization algorithm developed by Xin-She Yang in 2010. It is based on the echolocation behavior of bats. Bats use echolocation to detect prey, avoid obstacles, and navigate in the dark. The algorithm simulates this behavior to find optimal solutions in complex optimization problems. Applications: The Bat Algorithm has been used in various fields, including engineering design, image processing, data mining, and robotics, for solving complex optimization problems. PYTHON CODE: import numpy as np # Define the objective function def objective_function(x): return np.sum(x**2) # Initialize the bat population def initialize_bats(n_bats, dim, lower_bound, upper_bound, f_min, f_max, A0, r0):
Deep Learning in Robotics || Smart Robotics || ~xRay Pixy
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Marine Robotics and Metaheuristics || Deep Exploration || ~xRay Pixy
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Learn the role of Metaheuristics in Advanced Solutions in Marine Robotics. Video Chapters: Marine Robotics 00:00 Introduction 00:25 Marine Robots 02:11 Marine Robotics Applications 04:14 Marine Robotics Technologies 05:46 Marine Robotics Challenges 06:21 Marine Robotics Algorithms 10:30 Metaheuristic Algorithms in Marine Robotic 13:09 Conclusion
How to Create Objective Function for Real-Life Problems || PART 08 || ~x...
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Hyperparameter Optimization || Numerical Example Using PSO || PART 2 ||...
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Hyperparameter Optimization || Deep Learning + PSO || Hybrid Approach
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Learn how to Optimize Hyperparameters in Deep Learning Using Particle Swarm Optimization (PSO) Video Chapters: Deep Learning + Particle Swarm Optimization 00:00 Introduction 00:59 Deep Learning 03:05 ANN Example 06:55 Deep Learning Applications 07:55 How to use Deep Learning 10:55 Deep Learning Tools 11:15 Hyperparameter Optimization Example 14:04 Hyperparameter 14:22 Conclusion
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
Hybrid Approaches - Artificial Intelligence and Metaheuristic Algorithm ...
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Learn Artificial Intelligence and Metaheuristic Algorithm Real Life Applications Video Chapters: AI and Metaheuristics 00:00 Introduction 00:55 Metaheuristics 01:49 Artificial Intelligence 03:11 AI and Metaheuristics Collaboration 05:21 Robot Path Planning EXAMPLE 1 09:51 Route Optimization EXAMPLE 2 12:10 Outro
Multi-Objective Particle Swarm Optimization || Numerical Example || Step...
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Learn Multi-Objective Particle Swarm Optimization Step-By-Step. Video Chapters: Multi-Objective PSO 00:00 Introduction 00:46 Multi-Objective Optimization 02:55 MOO Applications 04:00 Example 1 Multi-Objective Optimization Problem 07:26 Example 2 Multi-Objective Optimization Problem 08:25 Methods for Multi-Objective Optimization 09:50 Multi-Objective Particle Swarm Optimization 12:00 Example 3 Multi-Objective Optimization Problem 17:58 STEPS for Multi-Objective Particle Swarm Optimization 21:55 Conclusion
Capuchin Search Algorithm || Step-By-Step || with Example ~xRay Pixy
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Firefly Algorithm In Python || Step-By-Step || ~xRay Pixy
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Cuckoo Search Using Python Code || Step-By-Step || ~xRay Pixy
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Prairie Dog Optimization Algorithm || Step-By-Step || ~xRay Pixy
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Learn Prairie Dog Optimization (PDO) Algorithm Step-By-Step with Example Video Chapters: PDO Algorithm 00:00 Introduction 00:30 PDO Inspiration 01:19 PDO Benefits 02:07 About Prairie Dogs 03:34 PDO Process 04:15 PSO Mathematical Models 05:56 4 Time Periods in PDO 06:31 PDO Steps 13:43 Levy Distribution 17:43 Conclusion 18:09 Outro
Levy Flight Numerical Example || Step-By-Step || ~xRay Pixy
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Cheetah Optimizer || STEP-BY-STEP || ~xRay Pixy
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Learn the Cheetah Optimization Algorithm Step-By-Step with examples. Video Chapters: Cheeta Optimizer 00:00 Introduction 01:11 Topics Covered 02:00 About Cheetah 03:20 Cheetah Hunting Strategies 06:51 Cheeta Optimizer Step-By-Step 15:51 Mathematical Models 16:16 Search Mode 17:41 Attack Mode 18:36 Sit-And-Wait Mode 19:38 Outro