Leveraging Deep Learning for Image-Based Risk Assessment in Project Management
Keywords:
Deep Learning, Image-Based Risk AssessmentAbstract
The integration of deep learning techniques in project management presents a transformative opportunity for enhancing risk assessment processes. This paper explores the application of deep learning models for performing visual risk assessments in project environments, emphasizing the identification of potential hazards based on image analysis from work sites. The study reviews various deep learning architectures, such as convolutional neural networks (CNNs), and their efficacy in analyzing images to detect risks, ensuring proactive measures are implemented. Furthermore, the research highlights case studies demonstrating successful implementations of these technologies, illustrating their effectiveness in real-world scenarios. The paper concludes with a discussion of the challenges and limitations of applying deep learning in project risk assessment, along with future research directions aimed at improving model accuracy and reliability.
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