Integration and Performance Analysis of Artificial Intelligence and Computer Vision Based on Deep Learning Algorithms

TL;DR

This paper analyzes how integrating deep learning with computer vision enhances system performance, highlighting successes, limitations, and future directions for building more intelligent machine vision systems.

Contribution

It provides a comprehensive analysis of the integration of deep learning and computer vision, emphasizing performance improvements and identifying challenges like generalization and interpretability.

Findings

Deep neural networks outperform traditional methods in image classification and object detection.

Integration of deep learning and computer vision drives technological breakthroughs.

Limitations include issues with generalization and interpretability.

Abstract

This paper focuses on the analysis of the application effectiveness of the integration of deep learning and computer vision technologies. Deep learning achieves a historic breakthrough by constructing hierarchical neural networks, enabling end-to-end feature learning and semantic understanding of images. The successful experiences in the field of computer vision provide strong support for training deep learning algorithms. The tight integration of these two fields has given rise to a new generation of advanced computer vision systems, significantly surpassing traditional methods in tasks such as machine vision image classification and object detection. In this paper, typical image classification cases are combined to analyze the superior performance of deep neural network models while also pointing out their limitations in generalization and interpretability, proposing directions for future improvements. Overall, the efficient integration and development trend of deep learning with massive visual data will continue to drive technological breakthroughs and application expansion in the field of computer vision, making it possible to build truly intelligent machine vision systems. This deepening fusion paradigm will powerfully promote unprecedented tasks and functions in computer vision, providing stronger development momentum for related disciplines and industries.