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基于深度学习的图像识别技术研究与应用

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随着深度学习技术的快速发展,图像识别技术已经取得了显著的进步,广泛应用于多个领域.针对于此,首先介绍了深度学习的基本概念,包括其工作原理和关键技术.然后,详细阐述了卷积神经网络(CNN)、循环神经网络(RNN)和生成对抗网络(GAN)等核心算法与模型,分析了它们在图像识别中的应用和优势.最后,探讨了深度学习在医疗影像分析、自动驾驶和智能安防等领域的应用,展示了其在现代技术中的重要价值.
Research and application of image recognition technology based on deep learning
With the rapid development of deep learning technology,image recognition technology has made remarkable prog-ress and is widely used in many fields.In view of this,the basic concepts of deep learning,including its working principle and key technologies,are first introduced.Then,the core algorithms and models such as convolutional neural network(CNN),recurrent neu-ral network(RNN)and generative adversarial network(GAN)are described in detail,and their applications and advantages in im-age recognition are analyzed.Finally,the application of deep learning in the fields of medical image analysis,autonomous driving and intelligent security is discussed,and its important value in modern technology is demonstrated.

deep learningimage recognitiontechnical researchapply

王华、郭艳妮

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湖南交通工程学院电气与信息工程学院,衡阳 421009

深度学习 图像识别 技术研究 应用

2024

现代计算机
中大控股

现代计算机

影响因子:0.292
ISSN:1007-1423
年,卷(期):2024.30(24)