Computer vision algorithms have important applications in the fields of image recognition and object detection. With the development of deep learning technology, computer vision algorithms have made significant progress in tasks such as object detection, classification, and positioning. In this study, convolutional neural networks and large-scale data sets are used for training to explore the application of computer vision algorithms in image recognition and object detection. The performance of the algorithm in target recognition and detection tasks is evaluated through feature extraction and model training of image data. The experimental results show that the accuracy rate of this algorithm is between 89% and 97%, and the computer vision algorithm has high accuracy and robustness in image recognition tasks. Through the effective training of deep learning models, the algorithm can automatically identify and classify different objects and scenes in the image.

Herui Wang. Application of Computer Vision Algorithms in Image Recognition and Object Detection. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 1: 59-64. https://doi.org/10.25236/AJCIS.2024.070109.

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