Prabin Kumar Bora's research while affiliated with Indian Institute of Technology Guwahati and other places

Publications (34)

Article
Full-text available
Charts are powerful tools for visualizing and comparing data. With the increase in the presence of various chart types in scientific documents in electronic media, the development of an automatic chart classification system is becoming an important task. Existing studies on chart classification fail to address the presence of noise in charts and co...
Chapter
In clinical practice, continuous recording and monitoring of the standard 12-lead electrocardiogram (ECG) is often not feasible. The emerging technology and advancement to record the ECG signal without the help of the medical expert’s in-home care or ambulatory conditions with minimal complexity have become more common in recent times. We aim to de...
Article
Full-text available
Automatic modulation classification (AMC) is a significant part of cognitive communication systems. In early researches, likelihood-based (LB) and feature-based (FB) solutions were proposed for the AMC problem. With the developments in the data-driven approaches, a third method based on deep learning (DL) has recently gained prominence among AMC re...
Article
This paper proposes a novel two-stream encoder–decoder network that utilizes both the high-level and the low-level image features for precisely localizing forged regions in a manipulated image. This is motivated by the fact that the forgery creation process generally introduces both the high-level artefacts (e.g., unnatural contrast) and the low-le...
Article
High-resolution (HR) retinal optical coherence tomography (OCT) images are preferred by the ophthalmologists to diagnose retinal diseases. These images can be obtained by dense scanning of the target retinal region during acquisition. However, a dense scanning increases the image acquisition time and introduces motion artefacts, which corrupt diagn...
Article
The automated analysis of optical coherence tomography (OCT) images can play a crucial role in the diagnosis and management of retinal diseases. The wide variations of the retinal disease manifestations in terms of shape, size, texture and spatial location pose a huge challenge in designing reliable and efficient automated methods. Existing methods...
Article
Automatic Modulation Classification (AMC) plays an important role in many civilian applications such as spectrum monitoring (SM) and cognitive radio (CR). The majority of the AMC algorithms for MIMO systems are developed for rich scattering environments, which offer a full rank channel matrix. A rank deficient channel such as a keyhole channel seve...
Book
This book comprises the select proceedings of the International Conference on Emerging Global Trends in Engineering and Technology (EGTET 2020), held in Guwahati, India. The chapters in this book focus on the latest cleaner, greener, and efficient technologies being developed for the implementation of smart cities across the world. The broader topi...
Article
In this Letter, the authors propose a variational mode decomposition method for quantifying diagnostic information of myocardial infarction (MI) from the electrocardiogram (ECG) signal. The multiscale mode energy and principal component (PC) of multiscale covariance matrices are used as features. The mode energies determine the strength of the mode...
Preprint
Full-text available
This paper proposes a novel two-stream encoder-decoder network, which utilizes both the high-level and the low-level image features for precisely localizing forged regions in a manipulated image. This is motivated from the fact that the forgery creation process generally introduces both the high-level artefacts (e.g. unnatural contrast) and the low...
Article
Full-text available
This paper proposes a novel compressed domain robust watermarking scheme which embeds watermark by altering the intra prediction modes of 4 × 4 intra prediction blocks of the most recent high-definition video standards H.265/HEVC. Due to different compression architecture and higher number of intra prediction mode, the existing intra prediction mod...
Article
Optical coherence tomography (OCT) enables 3D cross-sectional imaging of the retinal tissues and has become an essential tool for the diagnosis of eye diseases. Clinically, the ophthalmologists examine each cross-sectional image (B- scan) of the 3D OCT volume to diagnose the retinal pathologies. However, this process is time-consuming and tedious....
Article
Age-related macular degeneration (AMD) is the leading cause of progressive vision loss in the elderly. Optical coherence tomography (OCT) is a promising diagnostic tool for early detection and management of AMD. However, the speckle noise and low resolution (LR) of the OCT images affect its diagnostic viabilities. Therefore, denoising and super-res...
Article
Deep learning algorithms can offer a reliable automated interpretation of retinal optical coherence tomography (OCT) images to assist clinicians in disease diagnosis and management. However, retinal image processing presents pertinent obstacles such as the struggle of large-scale data acquisition and high cost of annotation. To address this, we hav...
Article
Full-text available
Underwater images suffer from haze, blue/green tint, and color distortion, caused by attenuation and scattering of light. Existing methods for restoration depend on transmission maps to inverse the effects based on the underwater image formation model, and enhancement methods often result in unnatural colors. In this paper, we propose a method to a...
Chapter
Intraocular anti-vascular endothelial growth factor (VEGF) therapy is the most significant treatment for vascular and exudative diseases of the retina. The highly detailed views of the retina provided by optical coherence tomography (OCT) scans play a significant role in the proper administration of anti-VEGF therapy and treatment monitoring. With...
Article
Identification of the macular pathologies at an early stage can prevent vision loss. Similarity in the pathological manifestations of common macular disorders like age related macular degeneration (AMD) and diabetic macular edema (DME) can make manual screening fallible. There is a growing interest among researchers for reliable automated detection...
Article
Advancements in tele-medicine have led to the development of portable and cheap hand-held retinal imaging devices. However, the images obtained from these devices have low resolution (LR) and poor quality that may not be suitable for retinal disease diagnosis. Therefore, this paper proposes a novel framework for the super-resolution (SR) of the LR...
Book
The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical secti...
Book
The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical secti...
Article
The presence of a keyhole can severely degrade the signal identification performance of the multiple input multiple output (MIMO) system. In this work, a novel algorithm, namely the direct modulation recognition (DMR) algorithm is presented to classify the lower order PSK constellations under the spatially correlated MIMO keyhole and Rayleigh chann...

Citations

... A separate detection model is used to obtain more accurate detection results to enhance the detection effect of the copy-move manipulation image. Mazumdar et al. [13] present a two-stream encoderdecoder network. e first stream extracts the noise residuals to learn the low-level features through the encoder of the high-pass filter. ...
... However, the majority of the recent studies focus on using state-of-the-art deep learning models such as VGGs, ResNets, etc. As reported in Thiyam et al. (2021aThiyam et al. ( , 2021b, majority of the existing chart classification models face problems while handling (i)Chart noise: most of the publicly available datasets for chart classification contain samples with various types of noise such as background noise, pattern noise, composite noise, etc., and (ii) Confusing chart class pairs: charts of similar characteristics is also one of the major reason for chart misclassification. ...
... Common to both architectures is the average classification accuracy, in the range from 90% to 100%. The comparison of different CNN architectures is available in Chart decoder [37], in a publication written by Thiyam et al. [38], and in the results of a competition in chart-type classification [39]. The publications show that all architectures perform similarly, with up to 5% divergence. ...
... The perceptual hashing approach generates a fixed-length fingerprint, i.e., a hash code based on the perceptual content of the image/video/audio. In the last few years, perceptual hashing has been used in different applications such as tampering detection [15], person re-identification [7], victim identification [4], or illegal Tor domain classification [5]. ...
... Then, using the lesion attention map, the classification network improves the OCT classification performance and accelerates the network training process by utilizing the information from local lesion-related regions. Das et al. [18] introduced a self-attention module based on traditional neural networks. It combines spatial features from the cross-sectional image based on their clinical relevance to obtain a discriminative high-level feature vector for a reliable diagnosis, which improves the classification performance. ...
... e information transmission model of the distributed 3D interior design system is constructed by using PCI bus technology, the basic entity object of the distributed 3D interior design system is constructed, the local information processing of the distributed 3D interior design system is carried out by using a multi-threaded scheduling method, the virtual reality visual application support layer is constructed by using client/server model, and the research and development of the distributed 3D interior design system is carried out under CCS 2.20 development platform [18]. e overall design structure of the system is shown in Figure 1. ...
... AMC plays a crucial role where enemy signal identification is essential. There is a strong demand for detection and identification of signals in the frequency spectrum during combat circumstances to differentiate between friendly and foe signals [5]. It also helps the communication system to dodge pre-defined receivers due to the change of modulation scheme in real-time. ...
... The results indicated that the SRCNN method is superior to traditional super-resolution image reconstruction methods in improving the resolution of underwater images. Das, V [17] conducted unsupervised super-resolution of OCT images based on generative adversarial networks to improve the diagnosis of age-related macular degeneration. Experimental results on clinical OCT images demonstrated that this method is superior to existing methods in terms of SR performance and calculation time. ...
... At present, the research of digital watermarking technology for video is mainly based on spatial domain [4][5][6], compression domain [7][8][9][10][11][12] and transform domain [13][14][15][16][17][18][19][20][21]. The principle of the video watermarking algorithm in the spatial domain is to embed watermark data on the basis of a processing pixel value of a video frame image. ...
... When a limited labeled dataset is available, semi-supervised GAN is appropriate to classify the OCT images. This was implemented by Das et al. [9]. The GAN architecture consists of a generator and a discriminator with less than 6 layers of depth. ...