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| 1 | 2,4,6-Triamino-1 ,3, 5-trinitrobenzene (TATB) and TATB-based formulations-A re- view显示文摘 | Veera M B Dabir S V Tushar K G | 2010 | Journal of Hazardous Materials2010，181，： | 1 |
| 2 | Creation of concept shap designs via a virtual reality interface显示文摘 | Tushar H Rajit G | 1997 | Computer-Aided Design1997，29，8： | 1 |
| 3 | Improving the hydrodynamic performance of diffuser vanes via shape optimization显示文摘 | Tushar G Daniel JD Raphael TH | | Computers and Fluids0，37，6： | 1 |
| 4 | Clinical significance of sperm protein 17 expression and immunogenicity in esophageal cancer显示文摘 | Garima G Rinu S Tushar K | 2007 | Int J Cancer2007，120，8： | 1 |
| 5 | Crop disease detection using image segmentation显示文摘 | Tushar H J Ravindra D B Prashant G P | 2012 | World Journal of Science and Technology2012，2，4： | 1 |
| 6 | Clinical significance of sperm protein 17 expression and immunogenicity in esophageal cancer显示文摘 | Garima G Rinu S Tushar K | 2007 | Int J Cancer2007，120，8： | 1 |
| 7 | Improvin the hydrodynamic performance of diffuser vanes vi shape optiraization 显示文摘 | Tushar G Daniel J D Raphael T H | 2008 | Computers and Fluids2008，37，6： | 1 |
| 8 | Bioconversion of soystero|s to an- drostenedione by Mycobacterium fortuitum subsp, fortuitum NCIM 5239, a mutant derived from total sterol degrader strain 显示文摘 | Vrushali G Tushar B Shridhar P | 2010 | J Chem Technol Biotechnol2010，85，： | 1 |
| 9 | Improving the Hydrodynamic Performance of Diffuser Vanes Via Shape Optimization显示文摘 | Tushar G Daniel J D Raphael T H | | Computers and Fluids0，37，6： | 1 |
| 10 | Optimization of Mult-istage Depressed Collectors显示文摘 | Tushar K Ghosh Richard G Carter | 2007 | IEEE Transactions on Elec-tron Devices2007，54，8： | 1 |
| 11 | Multiple surrogate modeling for axial compressor blade shape optimization 显示文摘 | Abdus S Kim K Y Tushar G | 2008 | Journal of Propulsion and Power2008，24，2： | 1 |
| 12 | Comparative Study of Response Surface Methodology,Artificial Neural Network and Genetic Algorithms for Optimization of Soybean Hydration显示文摘 | Tushar G Mainak C Anshu S | | 0，，01： | 1 |
| 13 | Apoptosis and hepatobiliary disease显示文摘 | TUSHAR P GREGORY J G | 1995 | Hepatology1995，21，6： | 1 |
| 14 | Apoptosis and hepatobiliary disease显示文摘 | Tushar P Gregory J G | 1995 | Hepatology1995，21，6： | 1 |
| 15 | Deep learning based detection of monkeypox virus using skin lesion images显示文摘As we set into the second half of 2022,the world is still recovering from the two-year COVID-19 pandemic.However,over the past three months,the outbreak of the Monkeypox Virus(MPV)has led to fifty-two thousand confirmed cases and over one hundred deaths.This caused the World Health Organisation to declare the outbreak a Public Health Emergency of International Concern(PHEIC).If this outbreak worsens,we could be looking at the Monkeypox virus causing the next global pandemic.As Monkeypox affects the human skin,the symptoms can be captured with regular imaging.Large samples of these images can be used as a training dataset for machine learning-based detection tools.Using a regular camera to capture the skin image of the infected person and running it against computer vision models is beneficial.In this research,we use deep learning to diagnose monkeypox from skin lesion images.Using a publicly available dataset,we tested the dataset on five pre-trained deep neural networks:GoogLeNet,Places365-GoogLeNet,SqueezeNet,AlexNet and ResNet-18.Hyperparameter was done to choose the best parameters.Performance metrics such as accuracy,precision,recall,f1-score and AUC were considered.Among the above models,ResNet18 was able to obtain the highest accuracy of 99.49%.The modified models obtained validation accuracies above 95%.The results prove that deep learning models such as the proposed model based on ResNet-18 can be deployed and can be crucial in battling the monkeypox virus.Since the used networks are optimized for efficiency,they can be used on performance limited devices such as smartphones with cameras.The addition of explainable artificial intelligence techniques LIME and GradCAM enables visual interpretation of the prediction made,helping health professionals using the model. | Tushar Nayak Krishnaraj Chadaga Niranjana Sampathila Hilda Mayrose Nitila Gokulkrishnan Muralidhar Bairy G Srikanth Prabhu Swathi K.S Shashikiran Umakanth | 2023 | Medicine in Novel Technology and Devices2023，，2： | 0 |
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