Abstract: An image acquisition method includes, in response to a target application being in a target operating mode, obtaining a first image by a target camera in a first operating mode and obtaining a second image by the target camera in a second operating mode. A resolution of the first image and a resolution of the second image are different.

Abstract: Described are an encoding method and system for ROAs. The encoding method includes the following steps: given a set of authorized IP prefixes an AS which are maintained with an IP address trie. By specifying a sequence of hanging levels on the IP address trie, it is divided into a set of non-overlapping sub-trees, each rooted at a hanging level. A node on a hanging level uniquely defines a sub-tree rooted at it, whose prefix can be encoded as the identifier of this sub-tree. All authorized prefixes covered by a sub-tree can be encoded into a bitmap of 2h bits, where h is the height of this sub-tree. Thus, the set of authorized IP prefixes of an AS is encoded into several tuples (identifier, bitmap).

Abstract: A method for forwarding data, a load balancing device, a computer readable storage medium, and a data transmission system. An implementation of the method includes: obtaining a data packet sent by a client, and extracting an actual session parameter from the data packet; in response to the actual session parameter being an unrecorded session parameter, reading information from a preset field address constituting a packet header of the data packet; wherein a preset field corresponding to the preset field address is configured to record information used to determine a target server parameter; in response to determining that the information read from the preset field address is not empty, determining, based on target information read from the preset field address, the target server parameter as a client communication object; and forwarding the data packet to a target server corresponding to the target server parameter.

Abstract: The present application provides methods and systems for detecting and quantifying chromosomal instability from histology images with machine learning. Also described herein are methods for selecting treatments for a medical disease, by determining a chromosomal instability pathological metric from histology images. The disclosed methods and systems may also be used to investigate disease progression and prognosis.

Abstract: A method and system for classifying input data arrived one by one in time, is provided including: a) respectively training a group of classifiers with a predetermined number with recent or previous input data whose real classes are obtained as learning samples, wherein a number of the recent input data are increased progressively in reverse chronological order; b) selecting the classifier having the highest accuracy on the recent input data from the group of classifiers based on recent classifying results of the group of classifiers; and c) classifying current input data using the selected classifier.