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Aesthetic quality estimation of an image is a challenging task. In this paper, we introduce a deep CNN approach to tackle this problem. We adopt the sate-of-the-art object-recognition CNN as our baseline model, and adapt it for handling several high-level attributes. The networks capable of dealing with these high-level concepts are then fused by a learned logical connector for predicting the aesthetic...
Lithium-ion batteries play an important role in electric vehicles. Accurate and robust estimation of their state-of-charge is crucial for the efficient and safe operation of electric vehicles. To improve the accuracy and robustness of the estimation approach, an adaptive PI observer aim for state-of-charge estimation and parameters update simultaneously is proposed. Lyapunov stability analysis is...
Context adaptive binary arithmetic coding (CABAC) is the entropy coding tool applied in the latest video coding standard, High Efficiency Video Coding (H.265/HEVC). CABAC achieves high coding efficiency but involves the bin-to-bin data dependency of Binary Arithmetic Encoder (BAE). This paper proposes a range updating structure with pre-bitwise-NOT (PBN) operation to shorten the critical paths in...
Many applications of machine-to-machine (M2M) based intelligent transportation systems highly rely on the accurate estimation of neighbor map, where neighbor map mentions the locations of all nearby vehicles and pedestrians. To build the neighbor map, it usually integrates multiple sensors, such as GPS, odometer, inertial measurement unit (IMU), laser scanners, cameras, and RGB-D cameras. In this...
We present an abandoned object detection system in this paper. A finite-state-machine model is introduced to extract stationary foregrounds in a scene for visual surveillance, where the state value of each pixel is inferred via the cooperation of short-term and long-term background models constructed in the proposed approach. To identify the left-luggage event, we then verify whether the static foregrounds...
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