Institution
Lehigh University
Education•Bethlehem, Pennsylvania, United States•
About: Lehigh University is a education organization based out in Bethlehem, Pennsylvania, United States. It is known for research contribution in the topics: Catalysis & Fracture mechanics. The organization has 12684 authors who have published 26550 publications receiving 770061 citations.
Papers published on a yearly basis
Papers
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TL;DR: The yeast Sir2 protein, required for transcriptional silencing, has an NAD+dependent histone deacetylase (HDA) activity that is eliminated in a yeast strain from which SIR2 and its four homologs have been deleted as mentioned in this paper.
Abstract: The yeast Sir2 protein, required for transcriptional silencing, has an NAD+-dependent histone deacetylase (HDA) activity. Yeast extracts contain a NAD+-dependent HDA activity that is eliminated in a yeast strain from which SIR2 and its four homologs have been deleted. This HDA activity is also displayed by purified yeast Sir2p and homologous Archaeal, eubacterial, and human proteins, and depends completely on NAD+ in all species tested. The yeast NPT1 gene, encoding an important NAD+ synthesis enzyme, is required for rDNA and telomeric silencing and contributes to silencing of the HM loci. Null mutants in this gene have significantly reduced intracellular NAD+ concentrations and have phenotypes similar to sir2 null mutants. Surprisingly, yeast from which all five SIR2 homologs have been deleted have relatively normal bulk histone acetylation levels. The evolutionary conservation of this regulated activity suggests that the Sir2 protein family represents a set of effector proteins in an evolutionarily conserved signal transduction pathway that monitors cellular energy and redox states.
761 citations
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01 Aug 1999TL;DR: A generic image fusion framework based on multiscale decomposition is studied, which includes all of the existing multiscales-decomposition-based fusion approaches the authors found in the literature which did not assume a statistical model for the source images.
Abstract: The objective of image fusion is to combine information from multiple images of the same scene. The result of image fusion is a single image which is more suitable for human and machine perception or further image-processing tasks. In this paper, a generic image fusion framework based on multiscale decomposition is studied. This framework provides freedom to choose different multiscale decomposition methods and different fusion rules. The framework includes all of the existing multiscale-decomposition-based fusion approaches we found in the literature which did not assume a statistical model for the source images. Different image fusion approaches are investigated based on this framework. Some evaluation measures are suggested and applied to compare the performance of these fusion schemes for a digital camera application. The comparisons indicate that our framework includes some new approaches which outperform the existing approaches for the cases we consider.
755 citations
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University of Ljubljana1, University of Birmingham2, Czech Technical University in Prague3, Linköping University4, Austrian Institute of Technology5, Carnegie Mellon University6, Parthenope University of Naples7, University of Isfahan8, Autonomous University of Madrid9, University of Ottawa10, University of Oxford11, Hong Kong Baptist University12, Kyiv Polytechnic Institute13, Middle East Technical University14, Hacettepe University15, King Abdullah University of Science and Technology16, Pohang University of Science and Technology17, University of Nottingham18, University at Albany, SUNY19, Chinese Academy of Sciences20, Dalian University of Technology21, Xi'an Jiaotong University22, Indian Institute of Space Science and Technology23, Hong Kong University of Science and Technology24, ASELSAN25, Commonwealth Scientific and Industrial Research Organisation26, Australian National University27, University of Missouri28, University of Verona29, Universidade Federal de Itajubá30, United States Naval Research Laboratory31, Marquette University32, Graz University of Technology33, Naver Corporation34, Imperial College London35, Electronics and Telecommunications Research Institute36, Zhejiang University37, University of Surrey38, Harbin Institute of Technology39, Lehigh University40
TL;DR: The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
Abstract: The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).
744 citations
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TL;DR: An overview of developments in robust optimization since 2007 is provided to give a representative picture of the research topics most explored in recent years, highlight common themes in the investigations of independent research teams and highlight the contributions of rising as well as established researchers both to the theory of robust optimization and its practice.
742 citations
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01 Dec 1993TL;DR: A novel approach to filter design, based on Adams' ‘log-domain’ filters, is proposed that yields a truly current-mode circuit realisation and, by introducing an exponential map on the state-space description of the desired linear system, a log-domain filter can be fully realised.
Abstract: A novel approach to filter design, based on Adams' [1] ‘log-domain’ filters, is proposed that yields a truly current-mode circuit realisation. Adams' idea, which was introduced in a limited context, is generalised to permit a complete distortionless synthesis procedure, which results in circuit implementations readily realisable using complementary bipolar processes. It is shown that, by introducing an exponential map on the state-space description of the desired linear system, a log-domain filter can be fully realised with transistors configured in current mirror-type groupings, current sources and capacitors. Owing to the mapping, the state variables are intrinsically related to current, and not voltage, in the resulting circuits, a fact that emphasises the current-mode nature of the design. A general biquadratic filter section is designed, and, following discussion of cascading sections, a seventh-order Chebychev lowpass filter is designed. All designed circuits are shown to be tunable over a two-decade range in frequency while their characteristics are accurately preserved, even for biquad sections whose f0Q product is greater than fT/10. The Chebychev filter is shown in simulation to possess nearly 60 dB dynamic range relative to 0.9% THD, with a cutoff frequency of nearly 5 MHz, using transistor models from AT&T's CBIC-R 300 MHz complementary bipolar process.
722 citations
Authors
Showing all 12785 results
Name | H-index | Papers | Citations |
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Yang Yang | 171 | 2644 | 153049 |
Gang Chen | 167 | 3372 | 149819 |
Yi Yang | 143 | 2456 | 92268 |
Mark D. Griffiths | 124 | 1238 | 61335 |
Michael Gill | 121 | 810 | 86338 |
Masaki Mori | 110 | 2200 | 66676 |
Kai Nan An | 109 | 953 | 51638 |
James R. Rice | 108 | 278 | 68943 |
Vinayak P. Dravid | 103 | 817 | 43612 |
Andrew M. Jones | 103 | 764 | 37253 |
Israel E. Wachs | 103 | 427 | 32029 |
Demetrios N. Christodoulides | 100 | 704 | 51093 |
Bert M. Weckhuysen | 100 | 767 | 40945 |
José Luis García Fierro | 100 | 1027 | 47228 |
Mordechai Segev | 99 | 729 | 40073 |