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| 1 | Rice husk ash as an effective adsorbent: Evaluation of adsorptive characteristics for Indigo Carmine dye显示文摘 | Uma R. Lakshmi Vimal Chandra Srivastava Indra Deo Mall Dilip H. Lataye | 2008 | Journal of Environmental Management2008，，2： | 1 |
| 2 | Adsorptive desulfurization by activated alumina显示文摘 | Ankur Srivastav Vimal Chandra Srivastava | 2009 | Journal of Hazardous Materials2009，，2： | 1 |
| 3 | Oxida- tive desulfurization by chromium promoted sulfated zirconia 显示文摘 | Sachin Kumar Vimal Chandra Srivastava Badoni R P | 2012 | Fuel Processing Technology2012，93，1： | 1 |
| 4 | Adsorption thermodynamics and isosteric heat of adsorption of toxic metal ions onto bagasse fly ash (BFA) and rice husk ash (RHA)显示文摘 | Vimal Chandra Srivastava Indra Deo Mall Indra Mani Mishra | 2007 | Chemical Engineering Journal2007，，1： | 1 |
| 5 | Rice husk ash as an effective adsorbent: Evaluation of adsorptive characteristics for Indigo Carmine dye显示文摘 | Uma R Lakshmi Vimal Chandra lndra Deo Mall | 2009 | Joumal of Environmental Management2009，90，2： | 1 |
| 6 | Characterization of mesoporous rice husk ash (RHA) and adsorption kinetics of metal ions from aqueous solution onto RHA显示文摘 | Vimal Chandra Srivastava Indra Deo Mall Indra Mani Mishra | 2006 | Journal of Hazardous Materials2006，，134： | 1 |
| 7 | Competitive adsorption of cadmium ( II ) and nickel ( 1I ) metal ions from aqueous solution onto rice husk ash 显示文摘 | Vimal Chandra Srivastava Indra DeoMall Indra Mani Mishra | 2009 | Chemical Engineering and Processing: Process Intensification2009，48，1： | 1 |
| 8 | multi-response optimization of parameters for the electrocoagulation treatment of electroplating wash-water using aluminum electrodes 显示文摘 | Vidya Sagar Jagati Vimal Chandra Srivastava Basheshwar prasad | 2015 | Separation Scieiace and Technology2015，50，： | 1 |
| 9 | Comparative studies on adsorptive removal of indole by granular activated carbon and bagasse fly ash显示文摘 | Ajay Devidas Hiwarkar Vimal Chandra Srivastava Indra Deo mall | 2015 | Environ. Prog. Sustainable Energy2015，，2： | 1 |
| 10 | Use of bagasse fly ash as an adsorbent for the removal of brilliant green dye from aqueous solution显示文摘 | Venkat S Mane Indra Deo Mall Vimal Chandra Srivastava | 2007 | Dyes and Pigments2007，73，： | 1 |
| 11 | Adsorptive removal of malachite green dye from aqueous solution by bagasse fly ash and activated carbon-kinetic study and equilibrium isotherm analyses显示文摘 | Indra Deo Mall Vimal Chandra Srivastava Nitin Kumar Agarwal Indra Mani Mishra | 2005 | Colloids and Surfaces A: Physicochemical and Engineering Aspects2005，，1： | 1 |
| 12 | Treat- ment of pulp an d paper mill wasterwaters With poly aluminium chloride and hagasses fly ash显示文摘 | Vimal Chandra Srivastava Indra Mall Indra Mani Mishra | 2005 | Colloids and Surfaces2005，，260： | 1 |
| 13 | Jatropha curcas : A potential biofuel plant for sustainable environmental development显示文摘 | Vimal Chandra Pandey Kripal Singh Jay Shankar Singh Akhilesh Kumar Bajrang Singh Rana P. Singh | 2012 | Renewable and Sustainable Energy Reviews2012，，5： | 1 |
| 14 | Rice husk ash as an effective adsorbent: Evaluation of adsorptive characteristics for Indigo Carmine dye 显示文摘 | Uma R Lakshmi Vimal Chandra Sfivastava Indra Deo Mall | 2009 | Journal of Environmental Management2009，90，： | 1 |
| 15 | Competitive adsorption of cadmium( Ⅱ ) and nickel ( Ⅱ ) metal ions from aqueous solution onto rice husk ash 显示文摘 | Vimal Chandra Srivastava Indra Deo Mall Indra Mani Mishra | 2009 | Chemical Engineering and Processing: Process Intensification2009，48，： | 1 |
| 16 | Advances in Hyperspectral Image Classification Based on Convolutional Neural Networks: A Review显示文摘Hyperspectral image(HSI)classification has been one of themost important tasks in the remote sensing community over the last few decades.Due to the presence of highly correlated bands and limited training samples in HSI,discriminative feature extraction was challenging for traditional machine learning methods.Recently,deep learning based methods have been recognized as powerful feature extraction tool and have drawn a significant amount of attention in HSI classification.Among various deep learning models,convolutional neural networks(CNNs)have shown huge success and offered great potential to yield high performance in HSI classification.Motivated by this successful performance,this paper presents a systematic review of different CNN architectures for HSI classification and provides some future guidelines.To accomplish this,our study has taken a few important steps.First,we have focused on different CNN architectures,which are able to extract spectral,spatial,and joint spectral-spatial features.Then,many publications related to CNN based HSI classifications have been reviewed systematically.Further,a detailed comparative performance analysis has been presented between four CNN models namely 1D CNN,2D CNN,3D CNN,and feature fusion based CNN(FFCNN).Four benchmark HSI datasets have been used in our experiment for evaluating the performance.Finally,we concluded the paper with challenges on CNN based HSI classification and future guidelines that may help the researchers to work on HSI classification using CNN. | Somenath Bera Vimal K.Shrivastava Suresh Chandra Satapathy | 2022 | Computer Modeling in Engineering & Sciences2022，，11： | 0 |
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