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This paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results. A new DIVerse 2K resolution image dataset (DIV2K) was employed. The challenge had 6 competitions divided into 2 tracks with 3 magnification factors each. Track 1 employed the standard bicubic downscaling setup, while Track 2...
Recently, pathological diagnosis plays a crucial role in many areas of medicine, and some researchers have proposed many models and algorithms for improving classification accuracy by extracting excellent feature or modifying the classifier. They have also achieved excellent results on pathological diagnosis using tongue images. However, pixel values can't express intuitive features of tongue images...
Matching and aligning architectural imagery is an important step for many applications but can be a difficult task due to repetitive elements often present in buildings. Many keypoint descriptor and matching methods will fail to produce distinctive descriptors for each region of man-made structures, which causes ambiguity when attempting to match areas between images. In this paper, we outline a technique...
Airborne LIDAR data often consumes hundreds of gigabytes. Existing LIDAR data compression schemes can compress the file to 5%–23% of the original size. Even after compression, the compressed data size is still in the order of gigabyte, which makes it impractical for many applications. This paper proposes a novel geometry based compression scheme. It first introduces a LIDAR classification method that...
The conventional method is not performing well in reservoir parameters prediction because of lacking learning samples. The support vector machine method could help us in this situation. We repeat an experiment to verify the excellent generalization ability of SVM. Four applications of real data processing were done by us, and they were all working very well. The result shows that this method would...
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