Some videos may have low resolution, high noise, or blurry images due to technical limitations or poor equipment conditions at the time of initial recording, resulting in poor quality after integrating micro video English teaching resources. However, improving deep learning can improve the quality of videos by training neural networks, converting low resolution videos into high-resolution videos, thereby improving image clarity and details. Therefore, a method for integrating micro video English teaching resources based on improved deep learning is proposed. Extract keyframe images of micro video English teaching resources using the K-means algorithm, enhance the original extracted images, introduce generative adversarial networks in deep learning technology, use dense convolutional neural networks and mixed attention mechanisms to improve the generator in the original generative adversarial network, construct a micro video English teaching resource integration model, input the enhanced keyframe images for classification fusion, obtain the micro video integration result and output, and achieve the integration of micro video English teaching resources. The experimental results show that compared to existing resource integration methods, our method can enhance the quality of English teaching resource images and has significant advantages in objective indicators.