| Crime scene reconstruction—Sex prediction from blood stained foot sole impressions N Basu, SK Bandyopadhyay Forensic science international 278, 156-172, 2017 | 16 | 2017 |
| Forensic comparison of fired cartridge cases: Feature-extraction methods for feature-based calculation of likelihood ratios N Basu, RS Bolton-King, GS Morrison Forensic science international: Synergy 5, 100272, 2022 | 10 | 2022 |
| Quantitative analysis of Euclidean distance to complement qualitative analysis of facial expression during deception A Mondal, P Mukhopadhyay, N Basu, SK Bandyopadhyay, T Chatterjee Industrial psychiatry journal 25 (1), 78-85, 2016 | 8 | 2016 |
| Application of machine intelligence in digital pathology: Identification of falciparum malaria in thin blood smear image S Nag, N Basu, SK Bandyopadhyay Advancement of machine intelligence in interactive medical image analysis, 65-97, 2020 | 7 | 2020 |
| Blood Stain with Hammer Imprint Shown in Crime Scene SK Bandyopadhyay, N Basu Open Access Library Journal 2 (4), 1-10, 2015 | 6 | 2015 |
| Facial reconstruction-a review SK Bandyopadhyay, N Basu, S Nag International Education and Research Journal 1 (5), 34-36, 2015 | 6 | 2015 |
| Review of common bloodstain patterns documented at a crime scene in the event of blunt force hit SK Bandyopadhyay, N Basu Am J Comp Sci Inform Technol 3, 45-63, 2015 | 6 | 2015 |
| Speaker identification in courtroom contexts–Part I: Individual listeners compared to forensic voice comparison based on automatic-speaker-recognition technology N Basu, AS Bali, P Weber, C Rosas-Aguilar, G Edmond, KA Martire, ... Forensic science international 341, 111499, 2022 | 5 | 2022 |
| Identification of unique characteristics of deception from facial expression A Mondal, P Mukhopadhyay, N Basu, SK Bandyopadhyay, T Chatterjee Current Science, 901-906, 2018 | 5 | 2018 |
| A strawman with machine learning for a brain: a response to Biedermann (2022) the strange persistence of (source)“identification” claims in forensic literature GS Morrison, D Ramos, RJF Ypma, N Basu, K Bie, E Enzinger, Z Geradts, ... Forensic Science International: Synergy 4, 2022 | 3 | 2022 |
| The opacity myth: A response to Swofford & Champod (2022) GS Morrison, N Basu, E Enzinger, P Weber Forensic Science International: Synergy 5, 100275, 2022 | 3 | 2022 |
| Calculation of likelihood ratios for inference of biological sex from human skeletal remains GS Morrison, P Weber, N Basu, R Puch-Solis, PS Randolph-Quinney Forensic Science International: Synergy 3, 100202, 2021 | 3 | 2021 |
| Bloodstain pattern analysis–A less explored domain N Basu, SK Bandyopadhyay IJAR 3 (1), 200-211, 2017 | 3 | 2017 |
| Initial data release of regular blood drip stain created by varying fall height, angle of impact and source dimension N Basu, SK Bandyopadhyay Data in brief 8, 1194-1205, 2016 | 3 | 2016 |
| 2D Source area prediction based on physical characteristics of a regular, passive blood drip stain N Basu, SK Bandyopadhyay Forensic science international 266, 39-53, 2016 | 3 | 2016 |
| Artefact removal and edge detection from medical image N Basu, S Nag, IK Maitra, SK Bandyopadhyay European J Biomed 3 (4), 493-502, 2016 | 2 | 2016 |
| Bloodstains Analysis on Fabric from Contact in a Crime Scene SK Bandyopadhyay, N Base International Journal of Computer System 2 (01), 30-32, 2015 | 2 | 2015 |
| Optimization of crime scene reconstruction based on bloodstain patterns and machine learning techniques SK Bandyopadhyay, N Basu Decision Management: Concepts, Methodologies, Tools, and Applications, 1497-1523, 2017 | 1 | 2017 |
| Automatic perspective rectification of documents photographed with a camera N Basu, SK Bandyopadhyay IJAR 2 (3), 705-710, 2016 | 1 | 2016 |
| An affective and adaptive E-learning system: A machine learning based approach L Mandal, N Mukherjee, S Bhattacharya, N Basu Int. J. Sci. Eng. Res. 6, 310-317, 2015 | 1 | 2015 |
