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MINSU (Mobile Inventory And Scanning Unit):Computer Vision and AI
To do so, it goes through a five-step method: object detection, foreground subtraction, K-means clustering, percentage estimation, and counting.
Residual Quantity in Percentage of Factory Machines Using Computer Vision and Mathematical Methods
Computer vision has been thriving since AI development was gaining thrust.
CNN-based Semantic Segmentation using Level Set Loss
Note that each binary image consists of background and regions belonging to a class.
Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection
Experimental results show that our approach effectively improves the performance of the one-stage object detection in unsupervised domain adaptation setting.
Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection
We construct a structured domain adaptation framework for our learning paradigm and introduce a practical way of DD for implementation.
Efficient Neural Network Compression via Transfer Learning for Industrial Optical Inspection
In this paper, we investigate learning the deep neural networks for automated optical inspection in industrial manufacturing.
Nutritionally recommended food for semi- to strict vegetarian diets based on large-scale nutrient composition data
Furthermore, we find that selenium and other essential micronutrients can be subject to deficiency in plant-based diets, and suggest nutritionally-desirable dietary patterns.
