Fused Text Segmentation Networks for Multi-oriented Scene Text Detection

In this paper, we introduce a novel end-end framework for multi-oriented scene text detection from an instance-aware semantic segmentation perspective. We present Fused Text Segmentation Networks, which combine multi-level features during the feature extracting as text instance may rely on finer feature expression compared to general objects. It detects and segments the text instance jointly and simultaneously, leveraging merits from both semantic segmentation task and region proposal based object detection task. Not involving any extra pipelines, our approach surpasses the current state of the art on multi-oriented scene text detection benchmarks: ICDAR2015 Incidental Scene Text and MSRA-TD500 reaching Hmean 84.1% and 82.0% respectively. Morever, we report a baseline on total-text containing curved text which suggests effectiveness of the proposed approach.Comment: Accepted by ICPR201

A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Concepts embody the knowledge of the world and facilitate the cognitive processes of human beings. Mining concepts from web documents and constructing the corresponding taxonomy are core research problems in text understanding and support many downstream tasks such as query analysis, knowledge base construction, recommendation, and search. However, we argue that most prior studies extract formal and overly general concepts from Wikipedia or static web pages, which are not representing the user perspective. In this paper, we describe our experience of implementing and deploying ConcepT in Tencent QQ Browser. It discovers user-centered concepts at the right granularity conforming to user interests, by mining a large amount of user queries and interactive search click logs. The extracted concepts have the proper granularity, are consistent with user language styles and are dynamically updated. We further present our techniques to tag documents with user-centered concepts and to construct a topic-concept-instance taxonomy, which has helped to improve search as well as news feeds recommendation in Tencent QQ Browser. We performed extensive offline evaluation to demonstrate that our approach could extract concepts of higher quality compared to several other existing methods. Our system has been deployed in Tencent QQ Browser. Results from online A/B testing involving a large number of real users suggest that the Impression Efficiency of feeds users increased by 6.01% after incorporating the user-centered concepts into the recommendation framework of Tencent QQ Browser.Comment: Accepted by KDD 201

Contrastive Learning enhanced Author-Style Headline Generation

Headline generation is a task of generating an appropriate headline for a given article, which can be further used for machine-aided writing or enhancing the click-through ratio. Current works only use the article itself in the generation, but have not taken the writing style of headlines into consideration. In this paper, we propose a novel Seq2Seq model called CLH3G (Contrastive Learning enhanced Historical Headlines based Headline Generation) which can use the historical headlines of the articles that the author wrote in the past to improve the headline generation of current articles. By taking historical headlines into account, we can integrate the stylistic features of the author into our model, and generate a headline not only appropriate for the article, but also consistent with the author's style. In order to efficiently learn the stylistic features of the author, we further introduce a contrastive learning based auxiliary task for the encoder of our model. Besides, we propose two methods to use the learned stylistic features to guide both the pointer and the decoder during the generation. Experimental results show that historical headlines of the same user can improve the headline generation significantly, and both the contrastive learning module and the two style features fusion methods can further boost the performance.Comment: Accepted at EMNLP 202

ANALYSIS OF THE GRASP PLANNING METHOD FOR MANIPULATION OF BH-4 DEXTEROUS HAND

ABSTRACT The paper presents method for planning robotic dexterous hand grasping task using example of the Beihang University's BH-4 dexterous hand. The grasping planning method is devised through modeling and simulation and experimentally verified using physical prototype. The paper presents the method for forward and inverse kinematic solutions of the BH-4 robot 4-DOF finger, including transformation matrix between the palm coordinate system and the finger base coordinate system. In addition, the method of the idiographic manipulation is presented using example of ball grasping. The simulation results and physical experiment verify that the inverse kinematic solution is correct, and kinematic grasping and operating planning is valid and feasible. Finally, the experiment with the complex system integrated robot arm with dexterous hand is carried out. Experimental result shows that the more complicated grasping task can be done by a dexterous hand integrated in the robot arm system

Protective effect of glucosamine cyclohexyl ester on osteoarthritis in rat via targeting expressions of matrix metalloproteinase and tissue inhibitor of metalloproteinases-1

Purpose: To investigate the therapeutic effect of glucosamine cyclohexyl ester on osteoarthritis (OA) in a rat model.Methods: Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blot assays were used to analyze the effect of glucosamine cyclohexyl ester on changes in mRNA and protein expressions of matrix metalloproteinase and tissue inhibitor of metalloproteinases-1 in isolated rat chondrocytes, and in a rat model of OA. The rat model of OA was prepared by injecting monoiodoacetate to Sprague-Dawley rats via intra-articular route.Results: Treatment of the chondrocytes with glucosamine cyclohexyl ester for 48 h prevented interleukin-1 β (IL-1β)-mediated increases in mRNA and protein  expressions in matrix metalloproteinases-1, -3 and -13, and also blocked IL-1β-induced decreases in mRNA and protein expressions of tissue inhibitor of metalloproteinase-1. Glucosamine cyclohexyl ester treatment also blocked the onset of morphological changes such as irregular surface, adhesion of tissues andpresence of osteophytes in the femoral condyle surface of the OA rats. Mankin score for control, OA and glucosamine cyclohexyl ester treatment groups were 0.98 ± 0.15, 8.35 ± 0.88 and 2.39 ± 0. 67 (p = 0.002), respectively. Treatment of OA rats with glucosamine cyclohexyl ester also inhibited increases in the activities of matrix metalloproteinases-1, -3 and -13, and decreases of tissue inhibitor of metalloproteinase-1 mRNA and protein expressions. Treatment of chondrocytes and OA rats with IL-1β caused no significant changes in the levels of H3K27 and H4K8.Conclusion: These results show that glucosamine cyclohexyl ester prevents OA by targeting the expressions of matrix metalloproteinases-1, -3 and -13 and tissue inhibitor of metalloproteinases-1.Keywords: Metalloproteinases, Interleukin, Mankin score, Osteoarthritis, Cartilag

Waveform-Domain Adaptive Matched Filtering: A Novel Approach to Suppressing Interrupted-Sampling Repeater Jamming

The inadequate adaptability to flexible interference scenarios remains an unresolved challenge in the majority of techniques utilized for mitigating interrupted-sampling repeater jamming (ISRJ). Matched filtering system based methods is desirable to incorporate anti-ISRJ measures based on prior ISRJ modeling, either preceding or succeeding the matched filtering. Due to the partial matching nature of ISRJ, its characteristics are revealed during the process of matched filtering. Therefore, this paper introduces an extended domain called the waveform domain within the matched filtering process. On this domain, a novel matched filtering model, known as the waveform-domain adaptive matched filtering (WD-AMF), is established to tackle the problem of ISRJ suppression without relying on a pre-existing ISRJ model. The output of the WD-AMF encompasses an adaptive filtering term and a compensation term. The adaptive filtering term encompasses the adaptive integration outcomes in the waveform domain, which are determined by an adaptive weighted function. This function, akin to a collection of bandpass filters, decomposes the integrated function into multiple components, some of which contain interference while others do not. The compensation term adheres to an integrated guideline for discerning the presence of signal components or noise within the integrated function. The integration results are then concatenated to reconstruct a compensated matched filter signal output. Simulations are conducted to showcase the exceptional capability of the proposed method in suppressing ISRJ in diverse interference scenarios, even in the absence of a pre-existing ISRJ model