ACIC Activity detection

Activity detection is a crucial task in computer vision as it enables machines to understand human actions and behaviors. In this abstract, we focus on activity detection in ACIC (Advanced Composites Image Corporation). ACIC is a leading company in the field of advanced composites manufacturing, dealing with high-performance materials for aerospace and defense industries. Developing an accurate activity detection system in this domain can enhance safety, efficiency, and quality control. This abstract presents an approach that utilizes deep learning techniques to analyze video data captured during the manufacturing process. By training a convolutional neural network on a large dataset of annotated activities, the system can automatically detect and classify different actions, such as cutting, molding, and inspection, in real-time. The proposed system shows promising results, with high accuracy and robustness, making it a valuable tool for ACIC in monitoring and optimizing their manufacturing processes.