Abstract: Methods and systems for detecting objects from aerial imagery are disclosed. The method includes obtaining an image of an area, obtaining a plurality of regional aerial images from the image of the area, classifying the plurality of regional aerial images as a first class or a second class by a classifier, wherein: the first class indicates a regional aerial image contains a target object, the second class indicates a regional aerial image does not contain a target object, and the classifier is trained by first and second training data, wherein the first training data include first training images containing target objects, and the second training data include second training images containing target objects obtained by adjusting at least one of brightness, contrast, color saturation, resolution, or a rotation angle of the first training images; and recognizing a target object in a regional aerial image in the first class.

Abstract: Methods and systems for detecting objects from aerial imagery are disclosed. The method includes obtaining an image of an area, obtaining a plurality of regional aerial images from the image of the area, classifying the plurality of regional aerial images as a first class or a second class by a classifier, wherein: the first class indicates a regional aerial image contains a target object, the second class indicates a regional aerial image does not contain a target object, and the classifier is trained by first and second training data, wherein the first training data include first training images containing target objects, and the second training data include second training images containing target objects obtained by adjusting at least one of brightness, contrast, color saturation, resolution, or a rotation angle of the first training images; and recognizing a target object in a regional aerial image in the first class.

Abstract: Methods and systems for detecting objects from aerial imagery are disclosed. According to certain embodiments, the method may include obtaining a Digital Surface Model (DSM) image of an area. The method may also include obtaining a DSM image of one or more target objects. The method may further include detecting the target object in the area based on the DSM images of the area and the one or more target objects. The method may further include recognizing the detected target objects by artificial intelligence. The method may further include acquiring the positions of the recognized target objects. The method may further include calculating the number of the recognized target objects.

Abstract: Methods and systems for detecting objects from aerial imagery are disclosed. According to certain embodiments, the method may include obtaining a Digital Surface Model (DSM) image of an area. The method may also include obtaining a DSM image of one or more target objects. The method may further include detecting the target object in the area based on the DSM images of the area and the one or more target objects. The method may further include recognizing the detected target objects by artificial intelligence. The method may further include acquiring the positions of the recognized target objects. The method may further include calculating the number of the recognized target objects.

Abstract: A method for processing a target pattern comprises the following steps: providing a to-be-processed image; matching the to-be-processed image is with a reference template to select at least one region of suspicion from the to-be-processed image, wherein the region suspicion comprises a target pattern and a background pattern; transforming the region of suspicion to a grayscale image; and transforming the grayscale image to an optical density image to enhance the target pattern with respect to the background pattern. A method for generating a classification system of target patterns and a method for classifying detected target patterns are also disclosed.