BEYOND IMAGE RECOGNITION: INNOVATIONS IN COMPUTER VISION

Poonam R. Bobade; Prof. Pushpa Tandekar; Prof. Ashish Deharkar

doi:10.59367/s5tbky97

Authors

Poonam R. Bobade Department of Computer Science and Engineering, Technology, Shri Sai, College Chandrapur, India
Prof. Pushpa Tandekar Department of Computer Science and Engineering, Technology, Shri Sai, College Chandrapur, India
Prof. Ashish Deharkar Department of Computer Science and Engineering, Technology, Shri Sai, College Chandrapur, India

DOI:

https://doi.org/10.59367/s5tbky97

Keywords:

Interdisciplinary field, convolutional neural networks (CNNs), revolutionized computer vision

Abstract

Computer vision, the interdisciplinary field that enables machines to interpret and understand visual information from the world, has undergone a transformative journey in recent years. While image recognition has long been a cornerstone of computer vision, this research paper delves into the remarkable innovations that extend far beyond simple image recognition. With the rapid advancements in deep learning, convolutional neural networks (CNNs), and related technologies, computer vision has reached new frontiers, enabling machines to not only identify objects but also understand context, semantics, and scenes.

This paper explores the limitations and challenges of traditional image recognition and the compelling need for innovation. It investigates the emerging techniques, algorithms, and applications that have revolutionized computer vision. From object detection and semantic segmentation to scene understanding, these advancements have paved the way for a plethora of real-world applications, ranging from medical image analysis to self-driving cars, security and surveillance, and industrial automation.

However, with great innovation comes great responsibility. This paper not only delves into the potential of advanced computer vision but also discusses the ethical and societal implications. As we embrace these innovations, we must consider the privacy, security, and broader societal consequences.

The research paper concludes by emphasizing the profound impact of these innovations on various industries and our daily lives. It predicts the future directions of computer vision, offering a glimpse into what lies ahead for this dynamic field. The abstract encapsulates the exciting journey from image recognition to the broader horizons of computer vision, where machines are not just seeing but truly understanding the visual world.

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