normalized mutual informationsum of squared differencesnonlinear optimizationThis paper presents a novel visual tracking approach that combines the NMI metric and the traditional SSD metric within a gradient-based optimization frame, which can be used for direct visual odometry and SLAM. We firstly ...
The discovery of place cells and grid cells underscored the importance of the hippocampal formation as a key neural substrate for spatial navigation1,2, fueling an intensive investigation of this brain region. Understanding spatial coding requires a model of the information flow in the underlying cell...
One of the main limitations of metabolic readout-based viability measurement is its inability to distinguish the concurrent cell growth and cell death since the estimated cell growth with metabolic readout is the sum of growing and dead cells. As a result, metrics implemented for high-throughput ...
To this end, the superwideband is split into several subbands, and MDCT coefficients belonging to each subband are normalized by the subband gain that is obtained by squared sum of each MDCT coefficient. We then estimate normalized MDCT coefficients appropriate for the superwideband in order to ...
into an expression involving only the image sum and sum squared under the feature. The construction of the ta- bles requires approximately operations, which is 5 Normalizing less than the cost of computing the numerator by (4) and considerably less than the required to Examining again the ...
Table 1. Reference data and LiDAR derived estimations with error analysis (mean bias error, MBE; root mean squared error, RMSE; coefficient of determination, R2) considering fruit number (FruitLiDAR), fruit diameter (DLiDAR), and leaf area (LALiDAR) measured at the tree in five growth stages...
We propose a novel tracking algorithm by minimizing the sum-of-squared differences (SSD) between the normalized image gradients of the template image and the input image from the test image sequence. The proposed tracking algorithm is efficient to implement since it is based on the framework of ...
This paper analyzes the performance of sum of squared differences (SSD), sum of absolute differences (SAD), normalized cross correlation (NCC), zero mean normalized cross correlation (ZNCC) and several other proposed modified expressions of NCC. Experimental results on real images demonstrate that ...
We then consider self-normalization by a function of the sum of squared martingale differences as in de la Pe?a et al. (2004)...doi:10.1007/978-3-540-85636-8_8Victor H. de la PeaTze Leung LaiQi-Man Shao
We then consider self-normalization by a function of the sum of squared martingale differences as in de la Pea et al. (2004). This self-normalization yields a universal upper LIL that is applicable to all adapted sequences. In the case of martingales satisfying certain boundedness assumptions,...