Himadri Mukherjee

TL;DR: A Convolutional Neural Network -tailored Deep Neural Network (DNN) that can collectively train/test both CT scans and CXRs to detect COVID-19 positive cases is engineered.

TL;DR: A light-weight Convolutional Neural Network (CNN)-tailored shallow architecture that can automatically detect COVID-19 positive cases using chest X-rays, with no false positive, and the current results were better than other deep learning models and state-of-the-art works.

TL;DR: An exhaustive analysis of different text categorization approaches over the conventional approaches has been undertaken and provides a clear idea about the available libraries used for different algorithms, availability of datasets, categorization technologies explored in various non-Indian and Indian languages as well.

TL;DR: A VAD technique is presented that uses line spectral frequency-based statistical features namely LSF-S coupled with extreme learning-based classification that helps in reducing the computational overhead as well elevate the recognition performance of speech-based systems.

TL;DR: A new second level Mel frequency cepstral coefficient-based feature named MFCC-2 that handles the large and uneven dimensionality of MFCC has been used to characterize languages in the thick of English, Bangla and Hindi.