Data Encoding Stage: The MNIST dataset contains grayscale handwritten digit images. Each image is scaled and normalized, then mapped to eight qubits through Angle Encoding or Amplitude Encding. This ...
Labeling images is a costly and slow process in many computer vision projects. It often introduces bias and reduces the ability to scale large datasets. Therefore, researchers have been looking for ...
Abstract: Road obstacles are a major contributor to traffic accidents, making their accurate detection and classification vital for road safety and infrastructure maintenance. This paper presents a ...
Abstract: Most hyperspectral image (HSI) classification methods assume that all classes in the test set are present during training. However, in real-world applications, acquiring labeled training ...
A pioneering system that combines artificial intelligence and computer vision could become a powerful tool for aquaculture hatcheries, improving the classification of fertilised eggs of Atlantic ...
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