Ranking-Preserving Cross-Source Learning for Image Retargeting Quality Assessment
نویسندگان
چکیده
منابع مشابه
Image Retargeting Quality Assessment
Content-aware image retargeting is a technique that can flexibly display images with different aspect ratios and simultaneously preserve salient regions in images. Recently many image retargeting techniques have been proposed. To compare image quality by different retargeting methods fast and reliably, an objective metric simulating the human vision system (HVS) is presented in this paper. Diff...
متن کاملSaliency & structure preserving multi-operator image retargeting
Content-aware image retargeting has attracted substantial research interests in the related research community. However, so far there is still no method can preserve important image contents and structure well without introducing deformation. To address this problem, we propose a Saliency & Structure Preserving Multi-operator (SSPM) method. SSPM classifies images into three categories utilizing...
متن کاملImage Quality Ranking Method for Microscopy
Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for...
متن کاملErratum: Image Quality Ranking Method for Microscopy
“The PyImageQualityRanking software’s source code can be downloaded from https://bitbucket.org/sakoho81/ pyimagequalityranking/. The software is distributed as a standard Python package, which contains an automatic setup script for easy installation. A convenient command line interface is provided for controlling various measures. For further details, please refer to the software documentation ...
متن کاملDeep Semantic-Preserving and Ranking-Based Hashing for Image Retrieval
Hashing techniques have been intensively investigated for large scale vision applications. Recent research has shown that leveraging supervised information can lead to high quality hashing. However, most existing supervised hashing methods only construct similarity-preserving hash codes. Observing that semantic structures carry complementary information, we propose the idea of cotraining for ha...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2020
ISSN: 0162-8828,2160-9292,1939-3539
DOI: 10.1109/tpami.2019.2923998