Naver Corporation

About: Naver Corporation is a company organization based out in Seongnam-si, South Korea. It is known for research contribution in the topics: Terminal (electronics) & Computer science. The organization has 4038 authors who have published 4294 publications receiving 35045 citations. The organization is also known as: NAVER Corporation & NAVER.

Automated Information Retrieval for Hazard Identification in Construction Sites

Abstract: The repetitive occurrence of similar accident in construction disasters is one of the prevalent features. Similar accident cases provide direct information for determining the risk of scheduled activities and planning safety countermeasure. Researchers have developed many systems in order to retrieve and use past accident cases. Although the developed systems have a clear and limited target, most of them were developed under a retrieval methods based on ad-hoc systems which can cause inconvenience for users in using the retrieval system. To overcome these limitations, this study proposes an automated information retrieval system that can search for and provide similar accident cases. The retrieval system extracts building information modeling objects and composes a query set by combining BIM objects with a project management information system. Based on the results of this study, the users can excessively reduce query generation. Furthermore, they can easily avoid risks by receiving similar past accident cases that can happen while they work.

End-to-End Differentiable Learning to HDR Image Synthesis for Multi-exposure Images

Abstract: Recent deep learning-based methods have reconstructed a high dynamic range (HDR) image from a single low dynamic range (LDR) image by focusing on the exposure transfer task to reconstruct the multi-exposure stack However, these methods often fail to fuse the multi-exposure stack into a perceptually pleasant HDR image as the local inversion artifacts are formed in the HDR imaging (HDRI) process The artifacts arise from the impossibility of learning the whole HDRI process due to its non-differentiable structure of the camera response recovery Therefore, we tackle the major challenge in stack reconstruction-based methods by proposing a novel framework with the fully differentiable HDRI process Our framework enables a neural network to train the HDR image generation based on the end-to-end structure Hence, a deep neural network can train the precise correlations between multi-exposure images in the HDRI process using our differentiable HDR synthesis layer In addition, our network uses the image decomposition and the recursive process to facilitate the exposure transfer task and to adaptively respond to recursion frequency The experimental results show that the proposed network outperforms the state-of-the-art quatitative and qualitative results in terms of both the exposure transfer tasks and the whole HDRI process

Slope Stability Characteristic of Unsaturated Weathered Granite Soil in Inje considering Antecedent Rainfall

Abstract: In this paper, effects of antecedent rainfall on stability of the unsaturated weathered granite slope at Inje, Korea were investigated. Effect of antecedent rainfall was considered in the numerical analysis using initial condition of matric suction, which was induced from field measurement. We also investigated case histories of slope failure, rainfall data, geotechnical properties, soil-water characteristic curve (SWCC) and hydraulic conductivity in those areas. Several sets of numerical stability analysis were performed on unsaturated slope with different initial matric suction. Result of the analyses indicated that the higher initial matric suction (less antecedent rainfall) of the unsaturated weathered granite slope delayed the slope failure. Also, unsaturated slope with higher saturated permeability is more vulnerable to rainfallinduced landslide than that with lower saturated permeability due to rainfall infiltration. Numerical analysis also indicated that a slope with wetting SWCC reached the failure condition earlier than a slope with drying SWCC.

Method and apparatus for monitoring invalid clicks

Abstract: A charging method of an Internet advertisement is provided. A method of monitoring an invalid click on a search advertisement, the method including: tracking user's activities after clicking a web site which is displayed as online advertisement, based, at least in part, upon predetermined rules; collecting the tracking information of the user's activities; analyzing at least one activity pattern of the user's activities based, at least in part, upon the collected tracking information; and determining if the user's click is an invalid click based, at least in part, upon the analyzed activity pattern and a predetermined reference value.

Automatic pronunciation assessment of Korean spoken by L2 learners using best feature set selection

Abstract: This paper proposes a method for automatic pronunciation assessment of Korean spoken by L2 learners by selecting the best feature set from a collection of the most well-known features in the literature. The L2 Korean Speech Corpus is used for assessment modeling, where the native languages of the L2 learners are English, Chinese, Japanese, Russian, and Mongolian. In our system, learners' speech is forced-aligned and recognized using a native Korean acoustic model. Based on these results, various features for pronunciation assessment are computed, and divided into four categories such as RATE, SEGMENT, SILENCE, and GOP. Pronunciation scores produced by combining categories of features by multiple linear regression are used as a baseline. In order to enhance the baseline performance, relevant features are selected by using Principal Component Regression (PCR) and Best Subset Selection (BSS), respectively. The results show that the BSS model outperforms the baseline and the PCR model, and that features corresponding to speech segment and rate are selected as the relevant ones for automatic pronunciation assessment. The observed tendency of salient features will be useful for further improvement of automatic pronunciation assessment model for Korean language learners.