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Il y a 4 modules dans ce cours
Welcome to AI Applications: Computer Vision and Speech Recognition, where you will gain hands-on expertise in using cutting-edge technologies to process visual data and interpret human speech. This course equips you with practical skills to address real-world challenges in computer vision and speech analysis.
By the end of this course, you will be able to:
- Analyze speech waveforms using advanced audio signal processing techniques.
- Develop a strong understanding of computer vision principles and applications.
- Perform morphological operations on images and videos within a customized environment.
- Implement advanced audio and video processing techniques.
- Apply OpenCV functionalities to build robust solutions for image and video analysis.
This course is ideal for AI enthusiasts, data scientists, and developers aiming to expand their skills in computer vision and speech recognition.
Prior experience with Python programming and a basic understanding of machine learning concepts is recommended for optimal learning.
Master the skills required to build intelligent systems in the evolving field of artificial intelligence with this focused course.
This module is designed to help learners understand the history of AI and how its ongoing development has led to the creation of image and video processing tools like OpenCV. Learn to perform various image processing such as morphological operations.
Inclus
32 vidéos5 lectures5 devoirs2 sujets de discussion
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32 vidéos•Total 166 minutes
Course Introduction•4 minutes
Industrial Breakthrough in Audio and Speech Recognition •2 minutes
Speech Recognition Technology•5 minutes
Computer Vision Application•5 minutes
Computer Vision Applications: Medical and Plant Disease•6 minutes
AI Responsibility Pyramid•7 minutes
Evolution of Computer Vision and Speech Analysis•5 minutes
Evolution of Speech Analysis•5 minutes
What is OpenCV?•6 minutes
Installing OpenCV on Windows •4 minutes
Installing OpenCV on Windows: Handling Libraries in Jupyter•5 minutes
Installing Integrated Libraries - NumPy, Matplotlib, SciPy, and Pillow•6 minutes
Installing Integrated Libraries - Dlib, Scikit, and Pytorch•5 minutes
Operations on OpenCV•3 minutes
Demonstration: Loading the Image and Encoding Image to RGB•6 minutes
Demonstration: Resizing, Rotating and Flipping the Image•7 minutes
Demonstration: Gaussian Blur•7 minutes
Demonstration: Edge Detection and Conversion•6 minutes
Demonstration: Opening (Dilation and Erosion)•6 minutes
Demonstration: Closing and Morphological Gradient •6 minutes
Blackhat and Whitehat Transformations•5 minutes
Demonstration: Whitehat/Tophat•4 minutes
Demonstration: Blackhat•6 minutes
Summary of Computer Vision with OpenCV•7 minutes
5 lectures•Total 40 minutes
Welcome to AI Applications: Computer Vision and Speech Recognition•10 minutes
Exploring Technologies for Computer Vision•10 minutes
Ethical Considerations in Computer Vision•10 minutes
LBPH Algorithm: Local Binary Patterns Histogram•5 minutes
Watershed Algorithm for Image Processing•5 minutes
5 devoirs•Total 54 minutes
Knowledge Check : Computer Vision with OpenCV•30 minutes
Practice Quiz : Evolution of AI and Computer Vision•6 minutes
Practice Quiz : Setting Up Environment•6 minutes
Practice Quiz : Image Processing•6 minutes
Practice Quiz : Morphological Operations•6 minutes
2 sujets de discussion•Total 20 minutes
Introduce Yourself•10 minutes
Simplifying OpenCV Environment Setup•10 minutes
Video Processing using OpenCV
Module 2•3 heures à terminer
Détails du module
In the second module of this course, you'll delve deeper into OpenCV functionalities for video preprocessing. You'll learn how to play videos using OpenCV, extract and combine frames, and demonstrate the use of Haar cascades and their integration with OpenCV.
Inclus
28 vidéos2 lectures3 devoirs1 sujet de discussion
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28 vidéos•Total 137 minutes
Video Processing•3 minutes
Demonstration: Implementing Frame by Frame Video Processing•4 minutes
Demonstration: Exiting the Processing Operation•3 minutes
Demonstration: Initializing the Video Frames•6 minutes
Demonstration: Saving the Frames•7 minutes
Demonstration: Loading the Data •5 minutes
Demonstration: Reading and Writing Operations •6 minutes
Demonstration: Histogram Matching•7 minutes
Demonstration: Matching Source and Reference Images•5 minutes
Demonstration: Cumulative Distribution Function•5 minutes
Demonstration: Differences in Images•4 minutes
Haar Cascade•2 minutes
Haar Cascade: Algorithm Overview•6 minutes
Haar Cascade Application and Limitation•2 minutes
Demonstration: Implementation of Haar Cascade Algorithm•7 minutes
Demonstration: Face Detection Code for Static Image•4 minutes
Demonstration: Implementing Boundary Box for Face Detection•6 minutes
Demonstration: Applying Face Detection on Images•6 minutes
Introduction to Face Recognition•6 minutes
Demonstration: Setting Up Pre-requisite Libraries and Loading the Image•2 minutes
Demonstration: Face Recognition and Detection•5 minutes
Demonstration: Facial Landmark Detection with File Loading and Library Setup•5 minutes
Demonstration: Adjusting Video details through OpenCV•6 minutes
Demonstration: Implementing Facial Landmarks on Images•4 minutes
Demonstration: Implementing Facial Landmarks on Videos•5 minutes
Summary of Video Processing with OpenCV•6 minutes
2 lectures•Total 20 minutes
Marker-Based Augmented Reality (AR)•10 minutes
Pros and Cons of OpenCV’s Haar cascade Face Detector•10 minutes
3 devoirs•Total 42 minutes
Knowledge Check : Video Processing with OpenCV•30 minutes
Practice Quiz : Video Processing Using OpenCV•6 minutes
Practice Quiz : Exploring Various Techniques for Face Detection and Recognition•6 minutes
1 sujet de discussion•Total 10 minutes
The Future of Face Recognition and Security: Opportunities and Challenges•10 minutes
Speech Recognition and Audio Analysis
Module 3•3 heures à terminer
Détails du module
In the third module of this course, you will learn the fundamental structure of speech and how it is organized. Process speech by analyzing waveforms and applying various techniques to manipulate them effectively.
Inclus
27 vidéos2 lectures3 devoirs1 sujet de discussion
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27 vidéos•Total 137 minutes
Introduction to Speech: Audio Data •4 minutes
Introduction to Speech: Human Computer Interaction and Applications•5 minutes
Processing Speech •6 minutes
Speech Production•7 minutes
Difficulties in Analyzing Speech•7 minutes
Working of Sound Waves•5 minutes
ADC and Sample Rate, Bit Rate•3 minutes
Conversion of ADC (Analog to Digital Converter) to DAC (Digital to Analog Converter)•5 minutes
Demonstration: Generating Sound•7 minutes
Demonstration: Spectrogram•6 minutes
Demonstration: Signal Frequencies Over Time•4 minutes
Summary of Audio File Analysis•2 minutes
Demonstration: Converting a Sound File into Waveform•7 minutes
Human Speech•7 minutes
Speech Waveform•5 minutes
Digital Signal Processing•7 minutes
MFCC (Mel Frequency Cepstral Coefficient)•6 minutes
Windowing Formula and Cepstrum•5 minutes
Demonstration: Computing the Spectrogram•4 minutes
Demonstration: Digitizing the Audio Data•5 minutes
Demonstration: Converting Fragmented Parts of Audio File for Speech Recognition•4 minutes
Voice Onset, Voice Offset, Tremor, and Noise Detection•6 minutes
Understanding the Concepts of Voice Onset and Offset•3 minutes
Summary of Speech Recognition and Audio Analysis•5 minutes
2 lectures•Total 20 minutes
Speech Analysis In Cyber Security•10 minutes
Speech Processing - Interactive Creation and Evaluation (SPICE) Toolkit•10 minutes
3 devoirs•Total 42 minutes
Knowledge Check : Speech Recognition and Audio Analysis•30 minutes
Practice Quiz : Speech and it's Variation•6 minutes
Practice Quiz : Digitizing and Analyzing Speech•6 minutes
1 sujet de discussion•Total 10 minutes
The Role of Speech Analysis in Modern AI Applications•10 minutes
Course Wrap-Up and Assessment
Module 4•1 heure à terminer
Détails du module
This module is designed to assess an individual on the various concepts and teachings covered in this course. Answer a comprehensive quiz which marks you as a learner who is confident in working with Computer Vision and OpenCV.
Inclus
1 vidéo1 lecture1 devoir1 sujet de discussion
Afficher les informations sur le contenu du module
1 vidéo•Total 4 minutes
Summary for AI Applications: Computer Vision and Speech Recognition•4 minutes
1 lecture•Total 10 minutes
Practice Project - Vehicle Tracking and Detection•10 minutes
1 devoir•Total 30 minutes
Knowledge Check : AI Applications: Computer Vision and Speech Recognition•30 minutes
1 sujet de discussion•Total 10 minutes
Describe Your Learning Journey•10 minutes
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A basic understanding of Python programming and machine learning concepts is recommended.
Do I need any specific software or tools for this course?
Yes, you'll need to set up Python, OpenCV, and other relevant libraries for image, video, and speech processing.
Are the course materials suitable for beginners?
While the course is beginner-friendly, prior Python knowledge and basic understanding of machine learning concepts will enhance your learning experience.
What programming languages and tools are used in this course?
You’ll primarily use Python with libraries and machine learning frameworks for computer vision and speech tasks.
Do I need prior experience in AI or machine learning?
No prior AI or ML experience is required. Basic programming skills in Python are recommended to follow along effectively.
What career opportunities can AI skills in vision and speech open up?
These skills prepare you for roles in AI engineering, computer vision development, speech technology, and data science.
Will I earn a certificate after completing the course?
Yes, you’ll receive a Coursera certificate that validates your AI skills and can be showcased on LinkedIn or to employers.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.