Manoj Kumar Singh

• Banaras Hindu University

Due to advancement of affordable imaging devices, a huge number of images are generated for different applications. An efficient method for retrieving the appropriate images corresponding to the query image from a huge repository is still awaited. Thus, content-based image retrieval (CBIR) systems have been developed. One of the issues that directl...

The rapid expansion of medical imaging repositories in hospitals has introduced significant challenges in managing and retrieving relevant data, which may contribute to diagnostic errors. Content-based medical image retrieval (CBMIR) offers a solution to these challenges by enabling efficient querying of vast datasets. This research introduces an e...

In this paper, we present a computationally efficient hybrid thresholding method for image deconvolution in the expectation maximization (EM) framework. The proposed method alternates between two key steps: an E-step that exploits the fast Fourier transform (FFT) for inversion of the convolution operator and an M-step that uses the discrete wavelet...

Content-based medical image retrieval (CBMIR) is an approach utilized for extracting pertinent medical images from extensive databases by focusing on their visual attributes instead of relying on textual information. This method entails examining the visual qualities of medical images, including texture, shape, intensity, and spatial relationships,...

In this study, we proposed an image deconvolution method in the expectation maximization(EM) framework. This method involves two steps: (i) E-step: utilizing the fast Fourier transform(FFT) for computationally efficient inversion of the convolution operator and (ii) M-step: employing the discrete wavelet transform (DWT) for estimating the original...

Research in cognitive neuroscience has found emotion-induced distinct cognitive variances between the left and right hemispheres of the brain. In this work, we follow up on this idea by using Phase-Locking Value (PLV) to investigate the EEG based hemispherical brain connections for emotion recognition task. Here, PLV features are extracted for two...

As our knowledge, there is no dialog system for mental health-care domain in Hindi. This may be due to unavailability of user utterances corpora in Hindi for this domain. In this paper, we propose a novel algorithmic approach for user utterance generation in Hindi by considering dialects, linguistic attributes, symptoms, frequency of symptoms, and...

Content-Based Image Retrieval (CBIR) leveraging semantic segmentation integrates semantic understanding with image retrieval, enabling users to search for images based on specific objects or regions within them. This paper presents a methodology for constructing image signatures, a pivotal element in enhancing image representation within a CBIR sys...

The aim of this research is to construct a generalizable and biologically-interpretable emotion recognition model utilizing complex electroencephalogram (EEG) signals for realizing emotional state of human brain. In this paper, the spatial-temporal information of EEG signals is used to extract brain connectivity-based feature, i.e., phase-locking v...

Explosive growth of multimedia content leads to massive amount of images which are uploaded every day in the cyber world, medical imaging repository, and other areas. Retrieval of image of interest from internet or huge repository of image data set is still challenging and an open problem. Thus, content based image retrieval (CBIR) systems are deve...

The complexity of multimedia has expanded dramatically as a result of recent technology breakthroughs, and retrieval of similar multimedia material remains an ongoing research topic. Content-based image retrieval (CBIR) systems search huge databases for pictures that are related to the query image (QI). Existing CBIR algorithms extract just a subse...

we present the modeling, simulation and signal processing of Doppler radar for heart beat and reparation sensing. Distance dependency of accuracy of heart and respiration signal from radar output is investigated and verified through simulation. T

In this paper, we present the modeling, simulation and signal processing of Doppler radar for heart beat and reparation sensing. Distance dependency of accuracy of heart and respiration signal from radar output is investigated and verified through simulation. The model is experimentally validated with commercially available motion detector DNO-341....

This paper describes our experimental work on computational analysis of socio-political blog data through a novel combine of sophisticated language processing and visualization techniques. We have designed an integrated framework by utilizing Topic Modeling, Entity Extraction and Sentiment Analysis; to draw sociologically relevant inferences from u...

This paper presents our experimental work on evaluation of Machine Learning based classification approaches (Naïve Bayes and SVM) with the Unsupervised Semantic Orientation based SO-PMI-IR algorithm for sentiment analysis of movie review texts. We have used both pre-existing data sets and our own dataset collection comprising of a large number of u...

This paper concerns about the linear and nonlinear method for restoration of highly blurred passive millimeter-wave (PMMW) image. In this paper nonlinear methods: the Luccy-Richardson (LR), the maximum a posteriori method (MAP), and the linear iterative methods Adaptive Landweber, the Generalized Minimal Residual (GMRES) are discussed and their per...

Important earth surface parameters are detected and monitored by airborne and spaceborne radiometers. In the other hand, a poor inherent resolution capability of the passive millimeter-wave (PMMW) imaging becomes a problem in many applications. To obtain high- and super-resolution PMMW imaging, an efficient restoration processing is essential. We h...

A poor inherent resolution capability of the passive millimeter-wave (PMMW) imaging becomes a problem in many applications. The need for efficient post-processing to achieve resolution improvement is being increasingly recognized. To obtain high- and super-resolution PMMW imaging, many restoration methods have been developed and evaluated. In this...

A poor inherent resolution capability of the passive millimeter-wave (PMMW) imaging becomes a problem in many applications. The need for efficient post-processing to achieve resolution improvement is being increasingly recognized. To obtain high- and super-resolution PMMW imaging, many restoration methods have been developed and evaluated. In this...

In this paper we present an adaptive method for accelerating conventional Maximum Entropy Method (MEM) for restoration of Passive Millimeter-Wave (PMMW) image from its blurred and noisy version. MEM is nonlinear and its convergence is very slow. We present a new method to accelerate the MEM by using an exponent on the correction ratio. In this meth...