Abstract: Many unsupervised domain adaptation (UDA) methods have been proposed to bridge the domain gap by utilizing domain invariant information. Most approaches have chosen depth as such information and achieved remarkable successes. Despite their effectiveness, using depth as domain invariant information in UDA tasks may lead to multiple issues, such as excessively high extraction costs and difficulties in achieving a reliable prediction quality. As a result, we introduce Edge Learning based Domain Adaptation (ELDA), a framework which incorporates edge information into its training process to serve as a type of domain invariant information. Our experiments quantitatively and qualitatively demonstrate that the incorporation of edge information is indeed beneficial and effective, and enables ELDA to outperform the contemporary state-of-the-art methods on two commonly adopted benchmarks for semantic segmentation based UDA tasks.

Abstract: The disclosure provides a power management method. The power management method is applicable to an electronic device. The electronic device is electrically coupled to an adapter, and includes a system and a battery. The adapter has a feed power. The battery has a discharge power. The power management method of the disclosure includes: reading a power value of the battery; determining a state of the system; and discharging power to the system, when the system is in a power-on state and the power value is greater than a charging stopping value, by using the battery, and controlling, according to the discharge power and the feed power, the adapter to selectively supply power to the system. The disclosure further provides an electronic device using the power management method.

Abstract: Disclosed is a memory device and an operation method thereof. The operation method of memory device, comprising: programming a plurality of sub-matrices including at least one of non-zero element of a rearranged matrix to a plurality of operation units of the memory device; and programming a mapping table into a working memory of a memory device. The rearranged matrix is generated by rearrange a plurality of columns and a plurality of rows of an original matrix according to the positions of a plurality of non-zero elements of the original matrix. The mapping table comprises a correspondence of row indexes between the original matrix and the rearranged matrix, a correspondence of column indexes between the original matrix and the rearranged matrix and a correspondence between the sub-matrices including at least one non-zero element and the operation units storing the sub-matrices including at least one non-zero element.

Abstract: Disclosed is a memory device and an operation method thereof. The operation method of memory device, comprising: programming a plurality of sub-matrices including at least one of non-zero element of a rearranged matrix to a plurality of operation units of the memory device; and programming a mapping table into a working memory of a memory device. The rearranged matrix is generated by rearrange a plurality of columns and a plurality of rows of an original matrix according to the positions of a plurality of non-zero elements of the original matrix. The mapping table comprises a correspondence of row indexes between the original matrix and the rearranged matrix, a correspondence of column indexes between the original matrix and the rearranged matrix and a correspondence between the sub-matrices including at least one non-zero element and the operation units storing the sub-matrices including at least one non-zero element.