What prior knowledge do I need for this course?

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.

AI Applications: Computer Vision and Speech Recognition

kurs ist nicht verfügbar in Deutsch (Deutschland)

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AI Applications: Computer Vision and Speech Recognition

Dieser Kurs ist Teil von Spezialisierung „Mastering AI: Neural Nets, Vision System, Speech Recognition“

Dozent: Edureka

Bei enthalten

Mehr erfahren

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Analyze speech waveforms and apply audio signal processing techniques.
Develop and implement computer vision algorithms using OpenCV.
Perform morphological operations on images and videos for data manipulation.
Apply speech recognition techniques for digitizing and analyzing audio signals.

Kompetenzen, die Sie erwerben

Kategorie: Digital Signal Processing
Kategorie: Applied Machine Learning
Kategorie: Computer Vision

Wichtige Details

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12 Aufgaben

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Dieser Kurs ist Teil der Spezialisierung Spezialisierung „Mastering AI: Neural Nets, Vision System, Speech Recognition“

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In diesem Kurs gibt es 4 Module

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.

Moduldetails

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.

Das ist alles enthalten

32 Videos5 Lektüren5 Aufgaben2 Diskussionsthemen

32 VideosInsgesamt 166 Minuten

Course Introduction4 Minuten
Industrial Breakthrough in Audio and Speech Recognition 2 Minuten
Speech Recognition Technology5 Minuten
Computer Vision Application5 Minuten
Computer Vision Applications: Medical and Plant Disease6 Minuten
AI Responsibility Pyramid7 Minuten
Evolution of Computer Vision and Speech Analysis5 Minuten
Evolution of Speech Analysis5 Minuten
What is OpenCV?6 Minuten
Installing OpenCV on Windows 4 Minuten
Installing OpenCV on Windows: Handling Libraries in Jupyter5 Minuten
Installing Integrated Libraries - NumPy, Matplotlib, SciPy, and Pillow6 Minuten
Installing Integrated Libraries - Dlib, Scikit, and Pytorch5 Minuten
Operations on OpenCV3 Minuten
Demonstration: Loading the Image and Encoding Image to RGB6 Minuten
Demonstration: Resizing, Rotating and Flipping the Image7 Minuten
Demonstration: Gaussian Blur7 Minuten
Demonstration: Edge Detection and Conversion6 Minuten
Demonstration: Image Thresholding - Binary Image5 Minuten
Demonstration: Different Methods of Thresholding6 Minuten
Demonstration: Practical Use Cases3 Minuten
What is Adaptive Thresholding5 Minuten
Demonstration of Global Adaptive Threshold5 Minuten
Demonstration: Implementing Adaptive Thresholding Methods7 Minuten
Morphological Operations5 Minuten
Morphological Operations in OpenCV4 Minuten
Demonstration: Opening (Dilation and Erosion)6 Minuten
Demonstration: Closing and Morphological Gradient 6 Minuten
Blackhat and Whitehat Transformations5 Minuten
Demonstration: Whitehat/Tophat4 Minuten
Demonstration: Blackhat6 Minuten
Summary of Computer Vision with OpenCV7 Minuten

5 LektürenInsgesamt 40 Minuten

Welcome to AI Applications: Computer Vision and Speech Recognition10 Minuten
Exploring Technologies for Computer Vision10 Minuten
Ethical Considerations in Computer Vision10 Minuten
LBPH Algorithm: Local Binary Patterns Histogram5 Minuten
Watershed Algorithm for Image Processing5 Minuten

5 AufgabenInsgesamt 54 Minuten

Knowledge Check : Computer Vision with OpenCV30 Minuten
Practice Quiz : Evolution of AI and Computer Vision6 Minuten
Practice Quiz : Setting Up Environment6 Minuten
Practice Quiz : Image Processing6 Minuten
Practice Quiz : Morphological Operations6 Minuten

2 DiskussionsthemenInsgesamt 20 Minuten

Introduce Yourself10 Minuten
Simplifying OpenCV Environment Setup10 Minuten

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.

Das ist alles enthalten

28 Videos2 Lektüren3 Aufgaben1 Diskussionsthema

28 VideosInsgesamt 137 Minuten

Video Processing3 Minuten
Demonstration: Implementing Frame by Frame Video Processing4 Minuten
Demonstration: Exiting the Processing Operation3 Minuten
Demonstration: Initializing the Video Frames6 Minuten
Demonstration: Saving the Frames7 Minuten
Demonstration: Loading the Data 5 Minuten
Demonstration: Reading and Writing Operations 6 Minuten
Demonstration: Histogram Matching7 Minuten
Demonstration: Matching Source and Reference Images5 Minuten
Demonstration: Cumulative Distribution Function5 Minuten
Demonstration: Differences in Images4 Minuten
Haar Cascade2 Minuten
Haar Cascade: Algorithm Overview6 Minuten
Haar Cascade Application and Limitation2 Minuten
Demonstration: Implementation of Haar Cascade Algorithm7 Minuten
Demonstration: Face Detection Code for Static Image4 Minuten
Demonstration: Implementing Boundary Box for Face Detection6 Minuten
Demonstration: Applying Face Detection on Images6 Minuten
Introduction to Face Recognition6 Minuten
Demonstration: Setting Up Pre-requisite Libraries and Loading the Image2 Minuten
Demonstration: Face Recognition and Detection5 Minuten
Demonstration: Facial Landmark Detection with File Loading and Library Setup5 Minuten
Demonstration: Adjusting Video details through OpenCV6 Minuten
Demonstration: Face Recognition7 Minuten
Demonstration: Encoding Facial Landmarks 4 Minuten
Demonstration: Implementing Facial Landmarks on Images4 Minuten
Demonstration: Implementing Facial Landmarks on Videos5 Minuten
Summary of Video Processing with OpenCV6 Minuten

2 LektürenInsgesamt 20 Minuten

Marker-Based Augmented Reality (AR)10 Minuten
Pros and Cons of OpenCV’s Haar cascade Face Detector10 Minuten

3 AufgabenInsgesamt 42 Minuten

Knowledge Check : Video Processing with OpenCV30 Minuten
Practice Quiz : Video Processing Using OpenCV6 Minuten
Practice Quiz : Exploring Various Techniques for Face Detection and Recognition6 Minuten

1 DiskussionsthemaInsgesamt 10 Minuten

The Future of Face Recognition and Security: Opportunities and Challenges10 Minuten

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.

Das ist alles enthalten

27 Videos2 Lektüren3 Aufgaben1 Diskussionsthema

27 VideosInsgesamt 137 Minuten

Introduction to Speech: Audio Data 4 Minuten
Introduction to Speech: Human Computer Interaction and Applications5 Minuten
Processing Speech 6 Minuten
Speech Production7 Minuten
Difficulties in Analyzing Speech7 Minuten
Working of Sound Waves5 Minuten
ADC and Sample Rate, Bit Rate3 Minuten
Conversion of ADC (Analog to Digital Converter) to DAC (Digital to Analog Converter)5 Minuten
Demonstration: Generating Sound7 Minuten
Demonstration: Spectrogram6 Minuten
Demonstration: Signal Frequencies Over Time4 Minuten
Summary of Audio File Analysis2 Minuten
Demonstration: Converting a Sound File into Waveform7 Minuten
Human Speech7 Minuten
Speech Waveform5 Minuten
Digital Signal Processing7 Minuten
MFCC (Mel Frequency Cepstral Coefficient)6 Minuten
Windowing Formula and Cepstrum5 Minuten
Demonstration: Computing the Spectrogram4 Minuten
Demonstration: Digitizing the Audio Data5 Minuten
Demonstration: Converting Fragmented Parts of Audio File for Speech Recognition4 Minuten
Voice Onset, Voice Offset, Tremor, and Noise Detection6 Minuten
Understanding the Concepts of Voice Onset and Offset3 Minuten
Tremor Detection2 Minuten
Demonstration: ZCR, Pitch Detection, Voice Activity Detection5 Minuten
Demonstration: Tremor Detection5 Minuten
Summary of Speech Recognition and Audio Analysis5 Minuten

2 LektürenInsgesamt 20 Minuten

Speech Analysis In Cyber Security10 Minuten
Speech Processing - Interactive Creation and Evaluation (SPICE) Toolkit10 Minuten

3 AufgabenInsgesamt 42 Minuten

Knowledge Check : Speech Recognition and Audio Analysis30 Minuten
Practice Quiz : Speech and it's Variation6 Minuten
Practice Quiz : Digitizing and Analyzing Speech6 Minuten

1 DiskussionsthemaInsgesamt 10 Minuten

The Role of Speech Analysis in Modern AI Applications10 Minuten

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.