Results 11 to 20 of about 703,591 (347)

Which academic search systems are suitable for systematic reviews or meta‐analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources

Research Synthesis Methods, 2020
Rigorous evidence identification is essential for systematic reviews and meta‐analyses (evidence syntheses) because the sample selection of relevant studies determines a review's outcome, validity, and explanatory power.
Michael Gusenbauer, Neal R Haddaway
exaly   +2 more sources

Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations’ COCI: a multidisciplinary comparison of coverage via citations [PDF]

Scientometrics, 2020
New sources of citation data have recently become available, such as Microsoft Academic, Dimensions, and the OpenCitations Index of CrossRef open DOI-to-DOI citations (COCI).
Alberto Martín-Martín, Mike Thelwall, Enrique Orduna-Malea   +2 more
exaly   +2 more sources

More on Google Scholar

, 2004
Javier Hernandez, Google Offers Journal Searches, Harvard Crimson, November 23, 2004.
Peter Suber
  +7 more sources

Commentary: To google or not to google, that is the question [PDF]

Biochemistry and Molecular Biology Education, 2003
Graham R. Parslow
openalex   +3 more sources

Google Earth Engine: Planetary-scale geospatial analysis for everyone

Remote Sensing of Environment, 2017
Noel Gorelick, Simon Ilyushchenko, David Thau   +2 more
exaly   +2 more sources

Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories [PDF]

Journal of Informetrics, 2018
Alberto Martín-Martín, Enrique Orduna-Malea, Mike Thelwall   +2 more
exaly   +2 more sources

Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Items [PDF]

IEEE International Conference on Robotics and Automation, 2022
Interactive 3D simulations have enabled break-throughs in robotics and computer vision, but simulating the broad diversity of environments needed for deep learning requires large corpora of photo-realistic 3D object models.
Laura Downs, Anthony Francis, Nate Koenig, Brandon Kinman, R. Hickman, Krista Reymann, T. B. McHugh, Vincent Vanhoucke   +7 more
semanticscholar   +1 more source

Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages [PDF]

arXiv.org, 2023
We introduce the Universal Speech Model (USM), a single large model that performs automatic speech recognition (ASR) across 100+ languages. This is achieved by pre-training the encoder of the model on a large unlabeled multilingual dataset of 12 million (
Yu Zhang, Wei Han, James Qin, Yongqiang Wang, Ankur Bapna, Zhehuai Chen, Nanxin Chen, Bo Li, Vera Axelrod, Gary Wang, Zhong Meng, Ke Hu, A. Rosenberg, Rohit Prabhavalkar, Daniel S. Park, Parisa Haghani, Jason Riesa, Ginger Perng, H. Soltau, Trevor Strohman, B. Ramabhadran, Tara N. Sainath, P. Moreno, Chung-Cheng Chiu, J. Schalkwyk, Franccoise Beaufays, Yonghui Wu   +26 more
semanticscholar   +1 more source

How Robust is Google's Bard to Adversarial Image Attacks? [PDF]

arXiv.org, 2023
Multimodal Large Language Models (MLLMs) that integrate text and other modalities (especially vision) have achieved unprecedented performance in various multimodal tasks. However, due to the unsolved adversarial robustness problem of vision models, MLLMs
Yinpeng Dong, Huanran Chen, Jiawei Chen, Zhengwei Fang, X. Yang, Yichi Zhang, Yu Tian, Hang Su, Jun Zhu   +8 more
semanticscholar   +1 more source

Removing leakage-induced correlated errors in superconducting quantum error correction

Nature Communications, 2021
Correlated errors coming from leakage out of the computational subspace are an obstacle to fault-tolerant superconducting circuits. Here, the authors use a multi-level reset protocol to improve the performances of a bit-flip error correcting code by ...
M. McEwen, D. Kafri, Z. Chen, J. Atalaya, K. J. Satzinger, C. Quintana, P. V. Klimov, D. Sank, C. Gidney, A. G. Fowler, F. Arute, K. Arya, B. Buckley, B. Burkett, N. Bushnell, B. Chiaro, R. Collins, S. Demura, A. Dunsworth, C. Erickson, B. Foxen, M. Giustina, T. Huang, S. Hong, E. Jeffrey, S. Kim, K. Kechedzhi, F. Kostritsa, P. Laptev, A. Megrant, X. Mi, J. Mutus, O. Naaman, M. Neeley, C. Neill, M. Niu, A. Paler, N. Redd, P. Roushan, T. C. White, J. Yao, P. Yeh, A. Zalcman, Yu Chen, V. N. Smelyanskiy, John M. Martinis, H. Neven, J. Kelly, A. N. Korotkov, A. G. Petukhov, R. Barends   +50 more
doaj   +1 more source