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Fundamental Matrix Estimation: A Study of Error Criteria
In addition, a new error criterion, Kanatani distance, was proposed and was proved to be the most effective for use during the outlier removal phase from accuracy and efficiency perspectives.
Deep Neural Networks Based Weight Approximation and Computation Reuse for 2-D Image Classification
This leads to a repetition of the weights across the processing element (PE) array, which in turn enables the reuse of the DNN sub-computations (computational reuse) and leverage the same data (data reuse) to reduce DNNs computations, memory accesses, and improve energy efficiency albeit at the cost of increased training time.
C3PU: Cross-Coupling Capacitor Processing Unit Using Analog-Mixed Signal In-Memory Computing for AI Inference
The 5x4 C3PU consumed energy of 66. 4 fJ/MAC at 0. 3 V voltage supply with an error of 5. 7%.
