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Institution

Dalian University of Technology

EducationDalian, China
About: Dalian University of Technology is a education organization based out in Dalian, China. It is known for research contribution in the topics: Catalysis & Finite element method. The organization has 60890 authors who have published 71921 publications receiving 1188356 citations. The organization is also known as: Dàlián Lǐgōng Dàxué.


Papers
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Proceedings ArticleDOI
14 Jun 2020
TL;DR: The consistency-enhanced loss is exploited to highlight the fore-/back-ground difference and preserve the intra-class consistency in the aggregate interaction modules to integrate the features from adjacent levels, in which less noise is introduced because of only using small up-/down-sampling rates.
Abstract: Deep-learning based salient object detection methods achieve great progress. However, the variable scale and unknown category of salient objects are great challenges all the time. These are closely related to the utilization of multi-level and multi-scale features. In this paper, we propose the aggregate interaction modules to integrate the features from adjacent levels, in which less noise is introduced because of only using small up-/down-sampling rates. To obtain more efficient multi-scale features from the integrated features, the self-interaction modules are embedded in each decoder unit. Besides, the class imbalance issue caused by the scale variation weakens the effect of the binary cross entropy loss and results in the spatial inconsistency of the predictions. Therefore, we exploit the consistency-enhanced loss to highlight the fore-/back-ground difference and preserve the intra-class consistency. Experimental results on five benchmark datasets demonstrate that the proposed method without any post-processing performs favorably against 23 state-of-the-art approaches. The source code will be publicly available at https://github.com/lartpang/MINet.

487 citations

Proceedings ArticleDOI
Matej Kristan1, Ales Leonardis2, Jiri Matas3, Michael Felsberg4, Roman Pflugfelder5, Luka Čehovin Zajc1, Tomas Vojir3, Gustav Häger4, Alan Lukezic1, Abdelrahman Eldesokey4, Gustavo Fernandez5, Alvaro Garcia-Martin6, Andrej Muhič1, Alfredo Petrosino7, Alireza Memarmoghadam8, Andrea Vedaldi9, Antoine Manzanera10, Antoine Tran10, A. Aydin Alatan11, Bogdan Mocanu, Boyu Chen12, Chang Huang, Changsheng Xu13, Chong Sun12, Dalong Du, David Zhang, Dawei Du13, Deepak Mishra, Erhan Gundogdu11, Erhan Gundogdu14, Erik Velasco-Salido, Fahad Shahbaz Khan4, Francesco Battistone, Gorthi R. K. Sai Subrahmanyam, Goutam Bhat4, Guan Huang, Guilherme Sousa Bastos, Guna Seetharaman15, Hongliang Zhang16, Houqiang Li17, Huchuan Lu12, Isabela Drummond, Jack Valmadre9, Jae-chan Jeong18, Jaeil Cho18, Jae-Yeong Lee18, Jana Noskova, Jianke Zhu19, Jin Gao13, Jingyu Liu13, Ji-Wan Kim18, João F. Henriques9, José M. Martínez, Junfei Zhuang20, Junliang Xing13, Junyu Gao13, Kai Chen21, Kannappan Palaniappan22, Karel Lebeda, Ke Gao22, Kris M. Kitani23, Lei Zhang, Lijun Wang12, Lingxiao Yang, Longyin Wen24, Luca Bertinetto9, Mahdieh Poostchi22, Martin Danelljan4, Matthias Mueller25, Mengdan Zhang13, Ming-Hsuan Yang26, Nianhao Xie16, Ning Wang17, Ondrej Miksik9, Payman Moallem8, Pallavi Venugopal M, Pedro Senna, Philip H. S. Torr9, Qiang Wang13, Qifeng Yu16, Qingming Huang13, Rafael Martin-Nieto, Richard Bowden27, Risheng Liu12, Ruxandra Tapu, Simon Hadfield27, Siwei Lyu28, Stuart Golodetz9, Sunglok Choi18, Tianzhu Zhang13, Titus Zaharia, Vincenzo Santopietro, Wei Zou13, Weiming Hu13, Wenbing Tao21, Wenbo Li28, Wengang Zhou17, Xianguo Yu16, Xiao Bian24, Yang Li19, Yifan Xing23, Yingruo Fan20, Zheng Zhu13, Zhipeng Zhang13, Zhiqun He20 
01 Jul 2017
TL;DR: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative; results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years.
Abstract: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new "real-time" experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.

485 citations

Journal ArticleDOI
28 Jul 2017-Science
TL;DR: A catalyst composed of layered gold clusters on molybdenum carbide (MoC) nanoparticles to convert CO through its reaction with water into H2 and CO2 at temperatures as low as 150°C is developed.
Abstract: The water-gas shift (WGS) reaction (where carbon monoxide plus water yields dihydrogen and carbon dioxide) is an essential process for hydrogen generation and carbon monoxide removal in various energy-related chemical operations. This equilibrium-limited reaction is favored at a low working temperature. Potential application in fuel cells also requires a WGS catalyst to be highly active, stable, and energy-efficient and to match the working temperature of on-site hydrogen generation and consumption units. We synthesized layered gold (Au) clusters on a molybdenum carbide (α-MoC) substrate to create an interfacial catalyst system for the ultralow-temperature WGS reaction. Water was activated over α-MoC at 303 kelvin, whereas carbon monoxide adsorbed on adjacent Au sites was apt to react with surface hydroxyl groups formed from water splitting, leading to a high WGS activity at low temperatures.

484 citations

Journal ArticleDOI
TL;DR: New heptamethine cyanine dyes with an alkylamino group at the central position were found to exhibit a large Stokes shift and strong fluorescence and were suggested to be a new paradigm for excited-state intramolecular charge transfer (ICT).
Abstract: New heptamethine cyanine dyes with an alkylamino group at the central position were found to exhibit a large Stokes shift (>140 nm) and strong fluorescence. They were suggested to be a new paradigm for excited-state intramolecular charge transfer (ICT). The configuration change of the bridgehead amine accompanying ICT was investigated in different viscosity and pH media.

482 citations

Journal ArticleDOI
TL;DR: The recent advances in MOF thin films are reviewed, including fabrication and patterning strategies and existing nanotechnology applications, and the most attractive future opportunities as well as the most urgent challenges are listed.
Abstract: Surface-supported metal–organic framework thin films are receiving increasing attention as a novel form of nanotechnology. New deposition techniques that enable the control of the film thickness, homogeneity, morphology, and dimensions with a huge number of metal–organic framework compounds offer tremendous opportunities in a number of different application fields. In response to increasing demands for environmental sustainability and cleaner energy, much effort in recent years has been devoted to the development of MOF thin films for applications in photovoltaics, CO2 reduction, energy storage, water splitting, and electronic devices, as well as for the fabrication of membranes. Although existing applications are promising and encouraging, MOF thin films still face numerous challenges, including the need for a more thorough understanding of the thin-film growth mechanism, stability of the internal and external interfaces, strategies for doping and models for charge carrier transport. In this paper, we review the recent advances in MOF thin films, including fabrication and patterning strategies and existing nanotechnology applications. We conclude by listing the most attractive future opportunities as well as the most urgent challenges.

482 citations


Authors

Showing all 61205 results

NameH-indexPapersCitations
Yang Yang1712644153049
Yury Gogotsi171956144520
Hui Li1352982105903
Michael I. Posner134414104201
Anders Hagfeldt12960079912
Jian Zhou128300791402
Chao Zhang127311984711
Bin Wang126222674364
Chi Lin1251313102710
Tao Zhang123277283866
Bo Wang119290584863
Zhenyu Zhang118116764887
Liang Cheng116177965520
Anthony G. Fane11256540904
Xuelong Li110104446648
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023167
2022836
20216,974
20206,457
20196,261
20185,375