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We consider the compression artifacts reduction problem, where a compressed image is transformed into an artifact-free image. Recent approaches for this problem typically train a one-to-one mapping using a per-pixel L_2 loss between the outputs and the ground-truths. We point out that these approaches used to produce overly smooth results, and PSNR doesnt reflect their real performance. In this paper,...
Nowadays, nesting problem has been encountered in many manufacturing industry. Nesting problem is given lots of layout elements and using algorithm to looking for the most suitable positions of every layout element in template to save the resource. In this paper, the two-dimensional problem is considered. The width of template is assumed to be fixed, and the heuristic and genetic algorithm is used...
In recent years, dictionary learning (DL) has shown significant potential in various classification tasks. However, most of previous works aim to learn a synthesis dictionary. The other major category of DL-analysis dictionary learning has not been fully exploited yet. This paper proposes a novel DL method, named Topology Preserving Dictionary Learning (TPDL). First, we propose a triplet-constraint-based...
In order to distinguish cover images and stego images, JPEG steganalysis technology has growing ties with machine learning in recent years. As an important research field in machine learning, dictionary learning (DL) has been successfully applied to various tasks, but its application in steganalysis is insufficient. In this paper, we propose a hybrid dictionary learning framework for JPEG steganalysis...
On the basis of the RFID testing standards theoretical analysis, it designs a RFID system test platform based on the embeddedLinux. It carries on the design development by hardware system's design of test platform, the software development platform construction and the application software system's design. It designs the application software system of test platform by Qt, and gives the application...
Error-correcting output code (ECOC) is an effective approach to solve the problem of multiclass SVM. In this paper, a probabilistic approach that is based on ECOC is proposed. In the training stage, a coding scheme is predefined, and a special model is trained by samples. In the classification stage, besides the labels from SVM as usual, posterior probabilities of labels are also calculated. They...
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