G-Tech evolution project

[Audio] Hello My Name is Kavya Dwivedi. I will be presenting the presentation on Computer Vision..

[Audio] What is Computer Vision? Computer Vision derives from a field of Artificial Intellligence which helps in analyzing images and videos from which important necessary information can be extracted. From that we can understand the information to predict results on events and trends..

[Audio] Who is developing the Technology? Scientists and engineers have created technology that can see and understand robots. Around the same time, the first technology for computer image scanning was developed, which enabled computers to digitize and acquire images. Researchers have utilized technology to investigate the issue of human vision ever since the acceptance of artificial intelligence (AI) in academia began in 1960. In 1974, the first optical character recognition system was introduced that could read text printed in any typeface or typespace. David Marr developed a network of pattern-recognition cells and a hierarchical vision mechanism in 1982. The first real-time facial recognition applications launched the era of computer vision in 2001. By 2000, object acknowledgment had become the dominant focal point in the examination. In these days, numerous research foundations and organizations are conducting research on PC vision, including large companies like Google, Microsoft, and IBM that are conducting research on their own initiative..

[Audio] Where is it being Developed? Due to its numerous applications in industries like health and medicine, sports and entertainment, and mechanical innovation, computer vision has gained some momentum and recognition. plan, free vehicles, and a variety of applications Visual affirmation tasks such as solicitation, limit, and identification are significant for the vast majority of these applications. Convolutional Cerebrum Associations (CNNs) as of late exhibited their power by performing uncommonly well in these top-level visual acknowledgment undertakings and designs. In PC vision, the fundamental building blocks of deep learning calculations are currently convolutional brain organizations (CNNs)..

[Audio] State Of Computer Vision Computer vision is utilized in industrial inspections, autonomous navigation, robotic assembly, and the past and present. The outcomes have been difficult to anticipate at best. I can't change modern review programs that only do 2D picture handling and example recognition. The fragility of nearly all computer vision algorithms is the main obstacle; In some situations, a strategy may work, but not in others. The future applications that it will get dealt with is The Metaverse, Edge Registering. , AI that shifts from being based on models to being based on data, generative AI, and augmented reality that makes merged reality better In a flash, these technologies will dominate the future. The computer vision would leave traces in the virtual reality environment..

[Audio] Type of Technology Google, Microsoft, and Amazon are just a few of the major tech companies that are contributing significantly to the development of computer vision technology. Autonomous driving, augmented reality, and image and video identification are among these applications. Public research institutions, such as universities and government-funded labs, are also actively involved in computer vision research and development with a focus on advancing the state of the art and developing new applications. TensorFlow and OpenCV, two open-source projects that provide programmers with robust frameworks and tools for creating computer vision applications, are just two of the many that contribute to the advancement of computer vision technology..

[Audio] Applications Of Computer Vision One of the most interesting purposes of PC vision is text extraction. PC vision is able to examine a photograph and transform it into electronic text that a machine can examine through the use of optical individual affirmation (OCR). After that, you can use this material for translation and search, among other things. The most significant strategy for removing crucial data from mechanized pictures in PC vision is picture understanding. This is risky because pictures can be especially improbable and ambiguous. Nonetheless, late improvements in information made by people have made it feasible for computers to in this manner sort out a cunning way for eliminating importance from photos. Picture search, scene understanding, and thing affirmation are two or three cases of usages where picture understanding is a vital part. The purpose of these projects is to locate a photograph that can serve as information and provide extremely in-depth details about it or something comparable. PC vision is using workstations to decipher and figure out electronic pictures. Security and reconnaissance, auto flourishing, clinical picture evaluation, and mechanical course all make use of this advancement. Spatial evaluation is an essential part of PC vision. The image's numerical connections were sorted out during this cycle. Plans, objects, and their development can all be seen and tracked with this data..

[Audio] Positive Implications of Computer Vision Computer vision is currently assisting in the detection and removal of poisonous or hazardous substances through virtual entertainment venues. In 2022, it is anticipated that 3.96 billion individuals will make use of person-to-person communication services. This number is expected to rise as informal mobile organizations and cell phone use continue to rise in previously underserved markets. With PC vision, you can control video, pictures, and text. This makes it easier for people to move around and faster to tell the most ridiculously awful things apart. Computer vision can help ensure accuracy without causing eye fatigue or any other kind of fatigue. As a result, it is less likely to make mistakes and more likely to quickly and accurately identify crucial image elements, such as a manufacturing defect. Machines are programmed to work indefinitely and never get bored..

[Audio] Negative Implications of Computer Vision It is extremely challenging to make a machine that can see like a human, and this difficulty is not just related to the challenges of using computers to accomplish this. There is a lot we need to learn about how human vision works. In order to fully comprehend natural vision, one needs to understand not only how various receptors, like those in the eye, function, but also how the brain processes what it finds. Although the framework has been spread out, its tips and backup strategies have been seen, and the frontal cortex needs to be examined in greater detail..

REFERENCES. https://www.weforum.org/agenda/2022/03/how-computer-vision-change-healthcare/#:~:text=Computer%20vision%20can%20help%20ensure,line%20%E2%80%94%20with%20precision%20and%20speed . https://www.ibm.com/topics/computer-vision#:~:text=In%201982%2C%20neuroscientist%20David%20Marr,cells%20that%20could%20recognize%20patterns . https://www.researchgate.net/publication/353326963_ARTIFICIAL_INTELLIGENCE_IN_COMPUTER_VISION/link/60f48d99fb568a7098bd155a/download file:///C:/Users/Ninad/Downloads/249-254Tesma601IJEAST.pdf https://research.ibm.com/topics/computer-vision https://www.blicker.ai/news/the-future-of-computer-vision-9-trends-and-applications-2023 https://blog.miraclesoft.com/features-and-applications-of-computer-vision/#:~:text=Computer%20vision%20is%20using%20computers,key%20component%20of%20computer%20vision . https://www.clockworks.co/news/the-future-of-computer-vision-9-applications-and-trends-in-2023#:~:text=The%20computer%20vision%20market%20has,according%20to%20Allied%20Market%20Research ). https://www.researchgate.net/publication/323106814_Computer_Vision_and_Image_Processing_A_Paper_Review#:~:text=Computer%20vision%20helps%20scholars%20to,domain%20with%20massive%20data%20analysis ..

THANK YOU.