BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks

We present a simple and effective framework for simultaneous semantic segmentation and instance segmentation with Fully Convolutional Networks (FCNs). The method, called BiSeg, predicts instance segmentation as a posterior in Bayesian inference, where semantic segmentation is used as a prior. We extend the idea of position-sensitive score maps used in recent methods to a fusion of multiple score maps at different scales and partition modes, and adopt it as a robust likelihood for instance segmentation inference. As both Bayesian inference and map fusion are performed per pixel, BiSeg is a fully convolutional end-to-end solution that inherits all the advantages of FCNs. We demonstrate state-of-the-art instance segmentation accuracy on PASCAL VOC.Comment: BMVC201

The role of block shareholders in the relationship between diversification and bank performance in Vietnam

Purpose: This paper examines the impact of diversification on bank performance and the role of block shareholders in this relationship. Design/Methodology/Approach: Dynamic GMM estimation is applied to test the research hypotheses on the sample of 21 Vietnamese commercial banks during the 2009-2018 period. Bank performance is measured by profitability and risks, whereas diversification is measured by income diversification, non-interest income diversification and non-interest income share. The presence of block shareholders is measured by ownership ratio and a dummy variable with 10% ownership threshold. Findings: Income diversification enhances bank performance, whereas non-interest income share has a reverse impact. State block shareholders help amplify the positive influence of diversification on bank performance, meanwhile the roles of foreign and private block shareholders remain ambiguous. Practical implications: Increased non-interest income share may adversely impact diversification. Vietnam should loosen the private and foreign ownership for banks so as to benefit more from diversification. Originality/Value: The paper contributes to the literature in three main ways. Firstly, it adds empirical evidence to the effects of diversification on bank performance in a transitional economy. Secondly, this paper provides evidence for the impact of block shareholders on the relationship between diversification and bank performance in the context of privatization and increasing presence of foreign investors. Thirdly, the article adds empirical evidence to the impact of other factors on bank performance after the 2007-2009 global financial crisis.peer-reviewe

Does trade credit spur firm performance? A case study in Vietnam

Purpose: The paper aims to examine the impacts of trade credit on firm performance in Vietnam, representing a small transition economy with high openness environment. Design/Methodology/Aproach: Generalized least squares method of estimation was used to test the hypotheses on a sample of 279 companies listed on Ho Chi Minh City Stock Exchange (HOSE) during the 2012-2018 period, after the global financial crisis. Findings: The research findings support the positive influences of trade credit on firm performance of large businesses through both accounts receivable and trade payables and reversal effects on small business. These results show the advantages of large-scale companies own over the smaller ones in acquiring financing resources and imposing market power on their business partners, which help them optimize the benefits of trade credit. Practical implications: Research results indicate that corporates should increase their business scale to capitalize on the benefits of trade credit, and small-scale businesses should control the cost of trade credit. Originality/Value: The paper contributes to the literature in three main ways. Firstly, our exclusive offers new insights into understanding the behavior of Vietnamese firms, and this would give implications for transition economies in the world. Secondly, the study was carried out in the post-crisis period, with regulatory changes in banking management. Thirdly, this research compensates for the lack of empirical evidence in this field of research.peer-reviewe

Possible Impact from Foreign Bank Presence to the Performance of Local Commercial Banks in Vietnam

Research on the impact of the presence of foreign banks on the domestic banking industry in particular is a popular topic for policy implications. The paper examines whether the presence of foreign banks improves the performance of domestic commercial banks in Vietnam. On the sample of 26 domestic commercial banks and 9 fully foreign-owned banks in Vietnam in the period 2009-2018, the research result shows that the presence of foreign banks reduces the profitability of domestic commercial banks, whereas does not have any impact on their operating costs, showing that the combination of spillover effects and competition effects has not caused a positive impact on Vietnamese banking industry. This result leads to policy implications that competition and the introduction of substitute products should be promoted, in order to make good use of the benefits of the entry of foreign banks. Keywords: foreign bank presence, bank performance, spillover effect, competition effect. JEL Classifications: G21, G34 DOI: https://doi.org/10.32479/ijefi.929

Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

Emerging applications such as Internet of Everything, Holographic Telepresence, collaborative robots, and space and deep-sea tourism are already highlighting the limitations of existing fifth-generation (5G) mobile networks. These limitations are in terms of data-rate, latency, reliability, availability, processing, connection density and global coverage, spanning over ground, underwater and space. The sixth-generation (6G) of mobile networks are expected to burgeon in the coming decade to address these limitations. The development of 6G vision, applications, technologies and standards has already become a popular research theme in academia and the industry. In this paper, we provide a comprehensive survey of the current developments towards 6G. We highlight the societal and technological trends that initiate the drive towards 6G. Emerging applications to realize the demands raised by 6G driving trends are discussed subsequently. We also elaborate the requirements that are necessary to realize the 6G applications. Then we present the key enabling technologies in detail. We also outline current research projects and activities including standardization efforts towards the development of 6G. Finally, we summarize lessons learned from state-of-the-art research and discuss technical challenges that would shed a new light on future research directions towards 6G

Revisiting LARS for Large Batch Training Generalization of Neural Networks

LARS and LAMB have emerged as prominent techniques in Large Batch Learning (LBL), ensuring the stability of AI training. One of the primary challenges in LBL is convergence stability, where the AI agent usually gets trapped into the sharp minimizer. Addressing this challenge, a relatively recent technique, known as warm-up, has been employed. However, warm-up lacks a strong theoretical foundation, leaving the door open for further exploration of more efficacious algorithms. In light of this situation, we conduct empirical experiments to analyze the behaviors of the two most popular optimizers in the LARS family: LARS and LAMB, with and without a warm-up strategy. Our analyses give us a comprehension of the novel LARS, LAMB, and the necessity of a warm-up technique in LBL. Building upon these insights, we propose a novel algorithm called Time Varying LARS (TVLARS), which facilitates robust training in the initial phase without the need for warm-up. Experimental evaluation demonstrates that TVLARS achieves competitive results with LARS and LAMB when warm-up is utilized while surpassing their performance without the warm-up technique