Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

IEEE Transactions on Pattern Analysis and Machine Intelligence

The invention addresses the problem that traditional Total Variation only enforces the horizontal and vertical intensity continuity and thus fails to reconstruct oblique edges well. In an embodiment, Directional Total Variation is defined which supports multiple gradient directions. It first pre-processes the image and determines the direction of edges / texture; Directional TV is calculated based on the gradients along the determined direction and its orthogonal direction. By utilizing adaptive weights to different directions in the regularization, Directional TV is capable of preserving edges independent from their orientation nicely. Thus, Directional TV regularization based image denoising, compression or super resolution tend to obtain better quality.

Method and device for processing of an image

Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks

The Aspect ratio is the fractional relation of the width of a video image compared to its height. The paper is focused on solving the problem that how to play various kinds of videos on the device screen with different aspect ratio from them. It is the first time to introduce saliency model, which can take human attention into account, into the aspect ratio conversion. Based on the saliency model, we proposed a novel cropping mode and a novel un-unique expanding mode, and then combine the two modes according to some principles from media aesthetics. Experiment results show that there is no distortion in the region of interest and no loss will be noticed in the output video sequences, which demonstrates the effectiveness and efficiency of our approach.

Aspect Ratio Conversion Based on Saliency Model

The invention concerns a method for embedding video annotation data into a coded video stream. The method comprises the step of - encapsulating said video annotation data into a unit, so-called video annotation unit, of the coded video data stream which format corresponds to at least one format used for sending the associated video data, - inserting an identifiable synchronizing code enabling the identification of said video annotation unit into the video data stream.

Method for embedding video annotation data into a coded video stream and video recording device.

Global motion estimation (GME) plays an important role in a variety of video processing applications, such as content-based coding, coarse video segmentation, and mosaic In this paper a novel fast global motion estimation algorithm based on iterative least square estimation (ILSE) is proposed for a four-parameter linear global motion model The basic idea is to design rules to keep the symmetrical structure of processing units during iterative process, which can enormously reduce the computation load without impact on the estimation accuracy The performance of the proposed fast-ILSE is analyzed and compared with traditional ILSE algorithm using sum of absolute difference (SAD) as criteria Roughly about 50% addition operation is eliminated during calculation of zoom parameters, and 100% multiplying operation and 75% of adding operations are eliminated during calculation of pan parameters And the proposed algorithm shows better estimation performance than the traditional ILSE method

Zhibo Chen

Papers

Method and device for processing of an image

Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks

Aspect Ratio Conversion Based on Saliency Model

Method for embedding video annotation data into a coded video stream and video recording device.

Fast global motion estimation based on iteration least-square estimation with sustained symmetrical structure