使用深度学习生成图像标题

Prof.S. Sankareswari, Miss.Bibi, Zainab Dongarkar, Miss.Heena Dongarkar, Miss.Simran Sarang, Miss.Madhura Valke, Student
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引用次数: 0

摘要

:为了自动为照片创建令人回味的描述,图像标题生成器项目引入了计算机视觉和自然语言处理方法的新融合。系统使用卷积神经网络(CNN)处理原始照片,同时利用最先进的深度学习模型识别复杂的模式和对象。这种视觉理解与尖端的自然语言处理(NLP)算法无缝结合,利用注意力过程和序列到序列模型生成语言和上下文一致的标题。该项目非常重视用户体验,为用户提供了一个简单的界面,用户可以通过该界面上传照片,并立即收到相关的标题。通过 BLEU 和 METEOR 等严格的评估措施来保证生成标题的可靠性和正确性。该系统必须在各种数据集上进行训练,以确保符合道德规范,最大限度地减少偏见,并促进包容性成果。该项目的潜在应用包括丰富搜索引擎内容元数据、盲人无障碍工具以及提高社交媒体平台的用户参与度。
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Image Caption Generator Using Deep Learning
: In order to automatically create evocative descriptions for photos, the Image Caption Generator Project introduces a novel blend of computer vision and natural language processing approaches. Convolutional Neural Networks (CNNs) are used by the system to process raw photos while utilizing cutting-edge deep learning models to recognize complicated patterns and objects. This visual comprehension is seamlessly combined with cutting-edge Natural Language Processing (NLP) algorithms, using attention processes and Sequence-to-Sequence models to produce captions that are both linguistically and contextually coherent. The project places a strong emphasis on the user experience by giving users a simple interface via which they can upload photographs and instantly receive pertinent captions. The reliability and correctness of generated captions are guaranteed by stringent evaluation measures like BLEU and METEOR. The system must be trained on a variety of datasets to ensure ethical considerations, minimize biases, and promote inclusive outcomes. Potential applications of the project include search engine content metadata enrichment, accessibility tools for the blind, and boosting user engagement on social media platforms.
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