Resistive (or memristive) devices, including resistive switching memory (RRAM), phase change memory (PCM) an spin-transfer torque memory (STTRAM), are strong candidates for future high-density memory, embedded memory and storage class memory. The availability of resistive-device technology in the industry would pave the way for several other applications in advanced computing, such as neuromorphic cognitive systems and other non-von Neumann approaches to computing. However, the building-block design, functionality and power consumption need to be carefully evaluated to assess all the advantages of the resistive devices with respect to standard CMOS technology. This work will review the recent progress in developing hybrid memristive/CMOS synapses based on either RRAM or PCM, showing the circuit design, the operation concept and the demonstration of real-time spike-based learning and recognition of visual patterns. The learning accuracy and power consumption of the novel synapse blocks will be finally discussed.

Abstract This paper presents a novel video stabilization approach by leveraging the multiple planes structure of video scene to stabilize inter‐frame motion. As opposed to previous stabilization procedure operating in a single plane, our approach primarily deals with multiplane videos and builds their multiple planes structure for performing stabilization in respective planes. Hence, a robust plane detection scheme is devised to detect multiple planes by classifying feature trajectories according to reprojection errors generated by plane induced homographies. Then, an improved planar stabilization technique is applied by conforming to the compensated homography in each plane. Finally, multiple stabilized planes are coherently fused by content‐preserving image warps to obtain the output stabilized frames. Our approach does not need any stereo reconstruction, yet is able to produce commendable results due to awareness of multiple planes structure in the stabilization. Experimental results demonstrate the effectiveness and efficiency of our approach to robust stabilization on multiplane videos.