pushpasri-m / ai-ml

Training section helded by Gensis (Computer Vision). Attending the computer vision training by Genisi company was a truly enjoyable experience. During the training, I had the opportunity to delve deep into the fascinating world of computer vision, where I learned to teach machines how to interpret and understand visual information.

ai-ml

Definition

Computer vision is a subfield of artificial intelligence (AI) that involves developing algorithms and systems to help computers gain a high-level understanding of visual data from the real world. This includes images and videos.

Applications

Computer vision has a wide range of practical applications, including:

Object_recognition

Identifying and categorizing objects within images or video streams. Face recognition: Recognizing and verifying individuals based on their facial features. Autonomous vehicles: Enabling self-driving cars to perceive and navigate their surroundings. Medical imaging: Assisting in the diagnosis and analysis of medical images like X-rays and MRIs. Augmented reality: Enhancing the real world with digital information and graphics. Surveillance and security: Monitoring and analyzing video feeds for suspicious activities. Quality control: Inspecting manufactured products for defects. Techniques: Computer vision techniques can vary widely, but they often involve image processing, pattern recognition, machine learning, and deep learning. Convolutional Neural Networks (CNNs) are commonly used for tasks like image classification and object detection.

Challenges

Computer vision faces challenges such as handling variations in lighting, viewpoint, and occlusions. Creating robust algorithms that can work in real-world, dynamic environments is a constant focus of research.

Tools and Libraries

There are several popular libraries and frameworks for working with computer vision, including OpenCV, TensorFlow, PyTorch, and scikit-image. These libraries provide pre-built tools and models to facilitate computer vision tasks.

Ethical Considerations

As computer vision technology becomes more powerful and ubiquitous, there are ethical concerns related to privacy, surveillance, bias in algorithms, and potential misuse.

Computer vision is a rapidly evolving field with ongoing research and innovation. It plays a vital role in various industries and continues to impact our daily lives, from image and video search on the internet to improving medical diagnoses and enhancing autonomous vehicles' safety.

for info

ComputerVersion.pdf