… on coarse−to−fine search for the best kernel matching. This paper re− searches for object …
To realize efficient tracking of such an object, we present a kernel matching method from …

… However, best results with kernel descriptors are achieved using efficient match kernels in
conjunction with nonlinear SVMs, which makes it impractical for large-scale problems. In this …

… match kernels by integrating the match functions for SIFT and CNN features. Specifically, a
thresholded exponential match kernel … features into the match kernels. Extensive evaluations …

… kernel learning to learn the kernel space in which the complex structures can be well captured
by kernel weights. Meanwhile, we have developed an efficient optimization algorithm to …

… The computational efficiency of GMMN is also less desirable in … efficiency by introducing
adversarial kernel learning techniques, as the replacement of a fixed Gaussian kernel in the …

… Kernels on graphs are built from kernel on walks in the graph. This paper firstly proposes new
kernels on graphs and on walks, which are very efficient … of these kernels. Thirdly we show …

… efficient match kernels (EMK) [3] to aggregate local kernel descriptors into object-level
features. Pyramid efficient match kernel … of both bag of words and set kernels. It maps local …

… to appropriate proposed kernel which matches retinal blood vessel profile more accurately.
… we choose kernel based method. In the literature, we have designed an efficient kernel by …

… expressivity versus efficiency [1]: a kernel able to capture all the small … ie an efficient algorithm2
for computing it is not known. So, if we want to define a kernel for graphs that is efficient to …

… to 2D convolution kernels, the additional dimension forming 3D convolution kernels raises
… 3D version of resource efficient kernel-based methods which can match up with the logic of …