While machine learning approaches to image restoration offer great promise, current methods risk training “onetrick ponies” that perform well only for image corruption of a particular level of difficulty—such as a certain level of noise or blur. First, we expose the weakness of today’s one-trick pony and demonstrate that training general models equipped to handle arbitrary levels of corruption ...

Witnessing the sheer amount of user-contributed photos and videos, we argue to leverage such freely available image collections as the training images for image classification. We propose an image expansion framework to mine more semantically related training images from the auxiliary image collection provided with very few training examples. The expansion is based on a semantic graph consideri...

We describe a similarity based adult image detection technique (SID) exploiting composed MPEG-7 visual descriptors. The technique with a large set of training adult image database and a smaller set of training non-adult image database is practically useful in detecting adult images with little false negatives. SID achieved 99% correct detections with 23% false positives when experimented with a...

In this paper, we design and evaluate a convolutional autoencoder that perturbs an input face image to impart privacy to a subject. Specifically, the proposed autoencoder transforms an input face image such that the transformed image can be successfully used for face recognition but not for gender classification. In order to train this autoencoder, we propose a novel training scheme, referred t...

Recently Learning –Based Approach for Super– resolution (SR) has been used witch generate favorable result. In this paper image super –resolution based on the multiple kernel regression is presented. This approach’s core is to learn the map between the space of high resolution image patches and the space of blurred high – resolution image patches.That are the interpolation result generated from...

The purpose of this study was to determine if a short-term exercise program (6 weeks) could improve subjective physical appearance ratings. Twenty-five previously sedentary adult men (aged 18-40 years) were randomly assigned to one of 3 training groups: cardiovascular, strength, or control. Subjects participating in an exercise group trained for an average of 34 minutes, 3 times per week. All s...

Many automatic segmentation methods are based on supervised machine learning. Such methods have proven to perform well, on the condition that they are trained on a sufficiently large manually labeled training set that is representative of the images to segment. However, due to differences between scanners, scanning parameters, and patients such a training set may be difficult to obtain. We pres...

A novel face hallucination method is proposed in this paper for the reconstruction of a high-resolution face image from a low-resolution observation based on a set of highand low-resolution training image pairs. Different from most of the established methods based on probabilistic or manifold learning models, the proposed method hallucinates the high-resolution image patch using the same positi...