Abstract: A method for detecting objects and labeling the objects with distances in an image includes steps of: obtaining a thermal image from a thermal camera, an RGB image from an RGB camera, and radar information from an mmWave radar; adjusting the thermal image based on the RGB image to generate an adjusted thermal image, and generating a fused image based on the RGB image and the adjusted thermal image; generating a second fused image based on the fused image and the radar information; detecting objects in the images, and generating, based on the fused image, another fused image including bounding boxes marking the objects; and determining motion parameters of the objects.

Abstract: A smart dandruff analysis system and method are provided for analyzing a severity of a subject's dandruff, and the smart dandruff analysis system has operation module, first neural network module, second neural network module, and classification module. The operation module receives a scalp area image of the subject and transforms the scalp area image into a first feature map. The first neural network module, a Convolutional Neural Network model, electrically connects with the operation module for receiving and transforming the scalp area image into a second feature map. The second neural network module, a Transformer model, electrically connecting with the first neural network module for receiving and transforming the second feature map into a third feature map. The classification module electrically connects with the second neural network module for receiving the third feature map and outputting a rating, wherein the rating is to determine the severity of the subject's dandruff.

Abstract: A method for detecting objects and labeling the objects with distances in an image includes steps of: obtaining a thermal image from a thermal camera, an RGB image from an RGB camera, and radar information from an mmWave radar; adjusting the thermal image based on the RGB image to generate an adjusted thermal image, and generating a fused image based on the RGB image and the adjusted thermal image; generating a second fused image based on the fused image and the radar information; detecting objects in the images, and generating, based on the fused image, another fused image including bounding boxes marking the objects; and determining motion parameters of the objects.