An algorithm was proposed, using sparse matrix as the storage structure of the data. To prevent the critical path from being lost, the queue method was adopted for the operation. Compared with the classical algorithm, this algorithm is simple, with close asymptotic time complexity (O (n e~2...
Specifically, we add the two output tensors to obtain the probability map and then apply a normal argmax operation on top of it. As for the case in which only algorithm-annotated images are available, only output #1 is used for generating results in both training and test. Experiments ...
2387.Median-of-a-Row-Wise-Sorted-Matrix (H-) 3116.Kth-Smallest-Amount-With-Single-Denomination-Combination (H) 3134.Find-the-Median-of-the-Uniqueness-Array (H-) Hash Map 049.Group-Anagrams (M+) 149.Max-Points-on-a-Line (H) 166.Fraction-to-Recurring-Decimal (M) 170.Two-Sum-III-Dat...
Simplex algorithm, like the revised simplex algorithm, involves many operations on matrices, and many authors have tried to take advantage of recent advances in LP. Indeed, some well-known tools like BLAS (Basic Linear Algebra Subprograms) or MATLAB have some of their matrix operations, such as...
GP-GPUs have been used as the platform for many applications due to their powerful computation ability and massively parallel features. In this paper, we first investigate the CSR sparse matrix format, the performance of existing optimized SpMV (Sparse matrix-vector multiplication) algorithms, and an...
Calculate the current best position t to improve “denoising”. The SORT algorithm introduces the intersection and merging ratio (IOU) between the detection box and the prediction boundary box into the loss matrix of the Hungarian algorithm. Check the test results and trajectories to determine ...
Our second contribution is a matrix-free algorithm to find a minimizer of the regularized reaper which is also suited for high-dimensional data. The algorithm couples a primal-dual minimization approach with a thick-restarted Lanczos process. This appears to be the first efficient convex variational...
We describe an efficient implementation of an algorithm for computing selected elements of a general sparse symmetric matrix A that can be decomposed as A = LDLT where L is lower triangular and D is diagonal. Our implementation, which is called SelInv, is built on top of an efficient supermo...
Analyzing multi-way data (orn-way tensors) has attracted a lot of attention due to their intrinsic complexity and richness. Hence, to deal with this complexity, in the last two decades, manyad hocmethods and extensions of 2-way matrix methods have been proposed, many of which are tensor ...
where [x, y, z] is the coordinate of original image and [X, Y, Z] is the coordinate of new image with transformation, M is the transformation matrix which helps us to obtain the perspective transformation model preparing for the following image reconstruction. ...