Vision Learning

 Vision Learning


Introductions [Meeting]

Computer Vision

Machine Learning


Learning New Things


Vision [Planning]

Image Processing

Introductory Blogs

-Vision Intelligence

Sight is the most amazing and complex sense among humans, it took nearly 500 million years for human evolution to reach this stage, which helps us to see and appreciate the most beautiful things in this world. Over the years, we have made amazing technological advances to enhance the visual ability of machines or Computers to help us see and capture beautiful moments around us. But machines do not see the world the way they do. from which we see it. In Computers or any electronic devices the Image appears as an array of square blocks known as pixels that are specified with a numerical value that indicates the intensity of the pixel. Image Processing is a technique of applying relevant mathematical operations or algorithms to a digitized Image or extracting some useful features such as edge shape and color. Suppose if an Image is overexposed and needs a reduction in brightness then simply subtracting a constant number from the pixel intensity value can reduce the brightness of the Image to make it more realistic. With advances in technology, diagnostic scans such as MRI ultrasound and X-rays can be analyzed using Image Processing and machine learning techniques.

-Image Processing

It is a system that Processes Images or videos, for example to magnify an Image [to make it look better], recognize Objects in an Image [is it a dog or a cat], recognize a person [ Tag your friend in Facebook], track the lane of the road [autonomous car], and so on

Image Processing is a method for converting an Image into digital form and performing certain operations on it, obtaining an enhanced Image or extracting some useful information from it. It is a type of signal distribution in which the input is an Image, such as a video frame or photograph, and the output may be the Image or features associated with that Image. Typically, Images in Image Processing systems are treated as two-dimensional signals while already applying set signal Processing methods to them.

It is one of the fast growing technologies today with its Applications in various aspects of business. Image Processing is also a core research area within the engineering and Computer science disciplines.

Image Processing basically includes the following three steps.

Importing the Image by optical scanner or digital photography.

Analyzing and manipulating the Image including data compression and Image enhancement and spotting patterns that are not to the human eye like satellite photographs.

Output is the last step in which the result can be converted to an Image or report based on Image analysis.

Purpose of Image Processing

The purpose of Image Processing is divided into 5 groups. They:

1. Visualization - observe Objects that are not visible.

2. Image Sharpening and Restoration - To create a better Image.

3. Image Retrieval - Search for the Image of interest.

4. Measurement of Patterns - Measures different Objects in an Image.

5. Image Recognition - To distinguish Objects in an Image.

-Computer Vision

The only main Application for Computer Vision is Image comprehension. It also means video, as it is technically a collection of Images [frames]. Understanding an Image is quite a complex and lengthy problem. Rather people identify certain tasks in Image comprehension requirements, and do only that.

There are many functions in understanding the Image; Some are low level functions that are used in various other tasks, while some are high level functions. Some of the low-level functions are:

Image Cleaning

Image Segmentation

Histogram Analysis

Image Color Space Translation

Image Change

Image Edge Detection and Contrast, Lines Approximation


Some high level functions [which usually use low level ones] are:

Object Detection

Object Recognition

Object Segmentation and Localization

commodity tracking

feature extraction

feature, color correction

Feature reconstruction, approximation


The Application of CV is usually based on higher level tasks [as mentioned above]. Some Applications are:

Face recognition in cameras

Road detection in pedestrians, cars, smart [self-driving] cars

Terrain detection in drones and airplanes

Vehicle license plate scanner at security checkpoints

Object 3D scanning to digitize the physical appearance of the Object

Augmented Reality [AR], Mixed Reality [MR] or Hybrid Reality [HR]


However, due to advances in Deep Learning [Machine Learning], most CV Applications are now using Deep Learning to achieve better accuracy. Nevertheless, the low level functions of CV are being used for Image pre-Processing [Processing Images before feeding them into deep learning networks].

For more details you can also check below blog/vlog/video.

Vision Learning is an Innovative new Resource for interdisciplinary Science Education funded by the National Science Foundation of US. These modules combine lessons, interactive animations, assessment resources and other tools to provide a complete learning environment. In addition, modules integrate short text-based lessons with links to news stories, scientific biographies and research papers to provide historical and topical context in science education. These modules can be completely customized to the individual needs.

Vision Learning is a web-based EduTech resource for Students and Teachers in the following STEM disciplines. 





Designed for those Studying at the High School and Graduate levels, Vision Learning takes advantage of recent advances in new online media to provide Teaching and Learning materials to Students and Teachers. Research by project personnel has shown that this peer-reviewed and bilingual content improves Students' understanding of Science and facilitates Multidisciplinary Learning.

The project also seeks to build a community to improve STEM Education.

Supported by the National Science Foundation and the United States Department of Education, Vision Learning provides Educational material that not only explores specific STEM concepts  but examines how we know these things.

Project Leaders believe that an important aspect of being successful in these disciplines is understanding their respective histories, as well as engaging with the process of discovery.

Vision Learning at a Glance

Learn about the Process of Science.

This training module is compliant with Next Generation Science Standards [NGSS]. 

Strengthen your understanding about  Vision Learning 

All Vision Learning modules include comprehensive literacy elements, in order to provide Students with a powerful framework for understanding the STEM concepts presented. From questions to encourage prior knowledge in the pre-reader to checkpoints strategically placed to understand readings, we aim to aid the learning process.

Review your understanding.

Included with almost every Vision Learning module is a quiz that tests your knowledge of the topic. The quizzes include best practices to ensure that Students are Learning the key elements presented.

Define unfamiliar.

Terms that may be unknown are hyperlinked throughout our module and included in a glossary page.

Listen to our Blog /Vlog

Several Vision Learning modules and vocabulary words include an audio recording. These recordings can be streamed while you are on the page and are especially helpful for auditory learners, struggling readers and language learners. In addition to audio, a font specially created to help dyslexic individuals can be activated on each page.

Create customized Classes.

In our classroom, instructors can select materials from the Vision Learning Blog to integrate the Science process into their Teaching.




Vision Learning Expert 

Austin TX

From: Mariana Goodwin <>

Sent: September 18, 2021 7:22 AM

To:  A Sowmya <>

Subject: Vision Learning


See Our Resources 


Popular posts from this blog

WhatsApp Group for Aviation Latest Job Updates

Career with AirCrews Work @ Home

Alfa Soft Tech Android Apps development company