Soman Kp

Soman Kp
Amrita Vishwa Vidyapeetham | AMRITA · Center for Computational Engineering and Networking (CEN)

About

776
Publications
445,255
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10,744
Citations
Citations since 2017
452 Research Items
9374 Citations
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500

Publications

Publications (776)
Preprint
Full-text available
With increasing volumes of data and increased demands of computing, Distributed Optimization is more relevant than ever to solving large-scale optimization problems. This is a tutorial that introduces some of the latest and relevant techniques such as ADMM and ALADIN with the necessary historical contexts, in an intuitive and easy-to-understand way...
Chapter
Biological sequence analysis involves the study of structural characteristics and chemical composition of a sequence. From a computational perspective, the goal is to represent sequences using vectors which bring out the essential features of the virus and enable efficient classification. Methods such as one-hot encoding, Word2Vec models, etc. have...
Article
Full-text available
Pneumonia is an acute respiratory infection caused by bacteria, viruses, or fungi and has become very common in children ranging from 1 to 5 years of age. Common symptoms of pneumonia include difficulty breathing due to inflamed or pus and fluid-filled alveoli. The United Nations Children’s Fund (UNICEF) reports nearly 800,000 deaths in children...
Conference Paper
Linear algebra is the backbone of modern applied data analytics. Not only does it provide the theoretical substratum for the development of analytical algorithms, it also lends the technological support for extremely efficient implementations. The linear algebra ecosystem consists of remarkably fast hardware support with equally efficient software...
Conference Paper
Power quality monitoring and parameter estimation are essential for the proper functioning of modern power grids. Various techniques have been proposed to estimate the characteristics of power signals and to gain insight into their dynamics. Non-stationary Fourier mode decomposition (NFMD) is a new interpretable time-frequency analysis framework fo...
Article
Full-text available
Software Requirement Specification (SRS) describes a software system to be developed that captures the functional, non-functional, and technical aspects of the stakeholder’s requirements. Retrieval and extraction of software information from SRS are essential to the development of software product line (SPL). Albeit Natural Language Processing (NLP...
Article
Full-text available
Pediatric pneumonia has drawn immense awareness due to the high mortality rates over recent years. The acute respiratory infection caused by bacteria, viruses, or fungi infects the lung region and hinders oxygen transport, making breathing difficult due to inflamed or pus and fluid-filled alveoli. Being non-invasive and painless, chest X-rays are t...
Chapter
Finding similar biological sequences to categorize into respective families is an important task. The present works attempt to use machine learning-based approaches to find the family of a given sequence. The first task in this direction is to convert the sequences to vector representations and then train a model using a suitable machine learning a...
Chapter
Cryptocurrency is based on blockchain technology which is ideally decentralised, referring to no superior authority overlooking it. The community is maintained by numerous user machines forming a “peer-to-peer” network. With the recent skyrocket of crypto-assets in the financial markets, many view it as the quickest and riskiest way to earn. Such a...
Chapter
Automation of vehicle classification is essential in the establishment of effective Intelligent Transportation Systems (ITS). Based on the MIOvision Traffic Camera Dataset (MIO-TCD), this paper categorizes the types of vehicles as car, bus, van, light truck, motorcycle and multi-axle truck. The classification of surveillance images is achieved usin...
Chapter
Full-text available
Bird audio identification is one of the challenging fine-grained tasks due to various complexity in the signal. In the current work, we present a new bird audio dataset from the Indian subcontinent and propose a novel hybrid features-based ensembled residual convolutional neural network to identify bird audios from the Indian subcontinent. We utili...
Conference Paper
Full-text available
Deep learning (DL) algorithms are widely used in object detection such as roads, vehicles, buildings, etc., in aerial images. However, the object detection task is still considered challenging for detecting complex structures, oil pads are one such example: due to its shape, orientation, and background reflection. A recent study used Faster Region-...
Conference Paper
Full-text available
Dense Residual U-Net (DRU-Net) is a neural network used for image segmentation. It is based on the U-Net architecture and isa combination of modified ResNet as the encoder and modified DenseNet as the decoder blocks. DRU-Net captures both the local and contextual information. Previous studies on DRU-Net have not tested the influence of the spectral...
Article
Full-text available
Alarming decline of the Odonates (Dragonflies and Damselflies) population needs urgent conservation efforts to balance nature’s food cycle and to reduce the negative impact on humans such as increasing the mosquito borne diseases. The existing odonates identification approaches are not efficient and are mainly based on domain expertise which is hig...
Chapter
Deep neural network is widely used nowadays for the extraction of geometrical features from the 3D models. Extracting the geometrical features from the 3D bodies plays an important role in many applications like registration and tracking. This paper focuses on the registration of CAD models of machining features which are commonly used in industrie...
Chapter
Nowadays, interpreting the topic of social media text content is an important task. It will take time when tried to do manually. AI with machine learning and deep learning approaches is used immensely for detecting the topic category. In the current work, Tamil text data from social media sources like YouTube, Facebook, Twitter are collected. The t...
Chapter
Automatic speech recognition systems are of two types, such as monolingual and multilingual. Due to its ability to use transfer learning techniques and create better SR models for resource-scarce languages, multilingual speech recognition has recently become more prevalent. Generally, multilingual speech recognition models use specific parameters a...
Chapter
Emotion analysis is a widely researched topic in the domain of natural language processing (NLP) due to its numerous applications in our daily lives as well as in the industries, especially the e-commerce industry. Emotions such as happiness, sadness, rage, fear, surprise, and disgust can be extracted from a document, allowing us to determine the v...
Chapter
Madan, YaminiVeetil, Iswarya KannothV, SowmyaEA GopalakrishnanKP, SomanMachine learning models are being increasingly proposed for the automated classification of Parkinson’s disease from brain imaging data such as magnetic resonance imaging (MRI). However, the problem of class imbalance is a major setback in deriving the maximum benefit from using...
Chapter
The proposed work utilises a combined architecture of time delay neural networks (TDNN) and multi-layered bidirectional long short-term memory (Bi-LSTM) network for the ink recognition from the handwritten text. We added a Trie beam search decoder with three smoothing algorithms such as Kneser–Ney Back off, Kneser–Ney Interpolated, and Stupid Back...
Chapter
Manufacturing industries have widely adopted the reuse of machine parts as a method to reduce costs and as a sustainable manufacturing practice. Identification of reusable features from the design of the parts and finding their similar features from the database is an important part of this process. In this project, with the help of fully convoluti...
Chapter
The two key components of Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) systems are language modeling and acoustic modeling. The language model generates a lexicon, which is a pronunciation dictionary. A lexicon can be created using a variety of approaches. For low-resource languages, rule-based methods are typically employed to build...
Article
Full-text available
Intracranial Haemorrhage (ICH) occurring due to any injury to the brain is a fatal condition and its timely diagnosis is critically important. In this work, we propose a complete one-stop model for the identification of Intracranial Haemorrhage (ICH) and for the segmentation of ICH regions in Computerized Tomography (CT) images. The proposed method...
Conference Paper
Full-text available
In this paper, we propose a novel method that establishes a newborn relation between Signal Processing and Natural Language Processing (NLP) method via Variational Mode Decomposition (VMD). Unlike the modern Neural Network approaches for NLP which are complex and often masked from the end-user, our approach involving Term Frequency Inverse Document...
Preprint
In 2020, covid-19 virus had reached more than 200 countries. Till December 20th 2021, 221 nations in the world had collectively reported 275M confirmed cases of covid-19 & total death toll of 5.37M. Many countries which include United States, India, Brazil, United Kingdom, Russia etc were badly affected by covid-19 pandemic due to the large populat...
Chapter
Diagnosis is the key step forward to cure a disease. Deep learning is becoming popular as a tool for usage in medical diagnosis. The existing literature using deep learning for the diagnosis of Parkinson’s Disease (PD) by transfer learning of MRI data was limited to the AlexNet architecture. The present work aims to inculcate commonly used deep lea...
Chapter
Deep Learning plays a major role in advancements in the healthcare domain, of which early disease diagnosis is one main appli- cation. With respect to the same, deep learning based classi�cation of brain MRI at the subject level is the requirement in the medical �eld. In this work, we have implemented an algorithm to identify the most discriminativ...
Chapter
Lack of labeled data is a major issue in the case of disease diagnosis using machine learning or deep learning algorithms. In this chapter, the authors address the issue of lack of labeled training data for medical image diagnosis by providing a completely unsupervised deep learning framework, which requires no labeled data for training. The propos...
Chapter
The impact of covid-19 on the financial market is considered a ’black swan event’, i.e., the occurrence of a highly unpredictable event with far-reaching consequences. Prediction of such events in prior is essential due to the financial risk associated. In this paper, we study critical slowing down as an early warning signal to forewarn such unpred...
Chapter
Messenger Ribonucleic acid (mRNA) vaccine faces a challenge of structural instability, due to which the production of vaccine becomes a big challenge. The sequence information of the mRNA vaccine can provide possible degradation sites. Recently, Deep learning areas like Natural Language Processing have shown great promise in understanding these seq...
Chapter
Unmanned aerial vehicles (UAVs) usually capture large amounts of images. The images need not be of good quality and need not contain the data that are required. Processing and selecting valuable data from these images take time. To overcome this difficulty, deep convolutional neural network algorithms can be assigned for processing huge image data....
Chapter
Unmanned aerial vehicles (UAVs) are useful for acquiring images of epiphytes as they grow on other trees and in areas that are not easily accessible. Manually identifying epiphytes in these images is both time-consuming and prone to errors. Convolutional neural networks (CNNs) are the building blocks for almost all state-of-the-art image classifica...
Chapter
In the past years, the activity on social media platforms is rising. Social media platforms ease the communication between users; nevertheless, this has led to hate speech proliferation. Hate speech detection has become a hot research topic, this is not only reflected by the hiked media coverage, but also by the political attention, it is receiving...
Conference Paper
Parkinson’s Disease (PD) is a progressive brain disorder cased by dopmainergic neuronal loss and mainly affects the Substantia Nigra located in the mid brain region. The increasing availability of public datasets has driven the development of advanced machine learning algorithms as a tool to assist in the classification and initial risk assessment...
Article
Morphological synthesis is one of the main components of Machine Translation (MT) frameworks, especially when any one or both of the source and target languages are morphologically rich. Morphological synthesis is the process of combining two words or two morphemes according to the Sandhi rules of the morphologically rich language. Malayalam and Ta...
Conference Paper
Full-text available
Quantum Dot Cellular Automata (QCA) technology is one of the emerging next-generation nano-scale technologies, to subdue the limitations of existing CMOS technologies. As researchers continue to work hard to find an alternative to CMOS technology, QCA provides a solution for a faster computer with a smaller size and low power consumption. This pape...
Chapter
This paper is an attempt to show a dependency parser for Hindi Language using Integer Linear Programming. A new approach is described for developing the constraint parser by convexifying the integer values taken as input, depicting the source groups (nouns) and demand groups (verbs) in a sentence. The convexified input is further used to find the I...
Preprint
Full-text available
Deep Learning (DL), a novel form of machine learning (ML) is gaining much research interest due to its successful application in many classical artificial intelligence (AI) tasks as compared to classical ML algorithms (CMLAs). Recently, DL architectures are being innovatively modelled for diverse applications in the area of cyber security. The lite...
Preprint
Full-text available
Deep Learning (DL), a novel form of machine learning (ML) is gaining much research interest due to its successful application in many classical artificial intelligence (AI) tasks as compared to classical ML algorithms (CMLAs). Recently, DL architectures are being innovatively modelled for diverse applications in the area of cyber security. The lite...
Chapter
Phonocardiogram (PCG) assumes a critical part in the early determination of heart irregularities. Phono-cardiogram can be utilized as an underlying diagnostics apparatus in far-off applications because of its effortlessness and cost-adequacy. The proposed work targets utilising a CNN architecture, with multiple preprocessing strategies like convert...
Chapter
Biological sequence comparison is one of the key tasks in finding similarities between different species. The primary task involved in computing such biological sequences is to produce embeddings in vector space which can capture the most meaningful information for the original sequences. Several methods such as one-hot encoding, Word2Vec models, e...
Article
Full-text available
Recently computer-aided diagnosis methods have been widely adopted to aid doctors in disease diagnosis making their decisions more reliable and error-free. Electrocardiogram (ECG) is the most commonly used, noninvasive diagnostic tool for investigating various cardiovascular diseases. In real life, patients suffer from more than one heart disease a...
Conference Paper
Full-text available
Bilingual dictionaries are essential resources in many areas of natural language processing tasks, but resource-scarce and less popular language pairs rarely have such. Efficient automatic methods for inducting bilingual dictionaries are needed as manual resources and efforts are scarce for low-resourced languages. In this paper, we induce word tra...
Chapter
Diabetes is a chronic condition much prevalent globally. It is an incurable condition, which has to be managed well. Otherwise, it leads to serious complications like heart diseases, stroke, kidney failure, diabetic retinopathy etc. Hyperglycaemia associated with diabetes leads to cardiovascular malfunctioning after the exclusion of other causes li...
Preprint
Full-text available
Manufacturing industries have widely adopted the reuse of machine parts as a method to reduce costs and as a sustainable manufacturing practice. Identification of reusable features from the design of the parts and finding their similar features from the database is an important part of this process. In this project, with the help of fully convoluti...
Conference Paper
Full-text available
Deep learning (DL) methods are used for identifying objects in aerial and ground-based images. Detecting vehicles, roads, buildings, and crops are examples of object identification applications using DL methods. Identifying complex natural and man-made features continues to be a challenge. Oil pads are an example of complex built features due to th...
Conference Paper
Full-text available
The deep learning (DL) models require timely updates to continue their reliability and robustness in prediction, classification, and segmentation tasks. When the deep learning models are tested with a limited test set, the model will not reveal the drawbacks. Every deep learning baseline model needs timely updates by incorporating more data, change...
Chapter
Full-text available
The price of a single stock is seldom independent. It has been known to brokers and fund managers, that, they heavily influence each other. Portfolios are built, on the premise of minimizing such dependencies between stocks. There have been several efforts to quantify these dependencies, predominantly using conventional statistics and correlations....
Chapter
Vamsi Krishna, U.Priyamvada, R.Jyothish Lal, G.Sowmya, V.Soman, K. P.Wavelet decomposition, variational mode decomposition, and dynamic mode decomposition are the latest signal processing tools that are recently being utilized in the music domain. Most of the work on these algorithms in music domain shows results based on pitch contour. None of the...
Preprint
Full-text available
Human communication is inherently multimodal and asynchronous. Analyzing human emotions and sentiment is an emerging field of artificial intelligence. We are witnessing an increasing amount of multimodal content in local languages on social media about products and other topics. However, there are not many multimodal resources available for under-r...
Article
Full-text available
Linguists have been focused on a qualitative comparison of the semantics from different languages. Evaluation of the semantic interpretation among disparate language pairs like English and Tamil is an even more formidable task than for Slavic languages. The concept of word embedding in Natural Language Processing (NLP) has enabled a felicitous oppo...
Article
Full-text available
Considering the gap between low-level image features and high-level retrieval concept, this paper investigates the effect of incorporating visual saliency based features for content-based image retrieval(CBIR).Visual saliency plays an important role in human perception due to its capability to focus the attention on the point of interest, i.e. an i...
Chapter
Tulasi Sasidhar, T.Premjith, B.Sreelakshmi, K.Soman, K. P.Social media has been experiencing an enormous amount of activity from millions of people across the globe over last few years. This resulted in the accumulation of substantial amount of textual data and increased several opportunities of analysis. Sentiment analysis and classification is on...
Chapter
Full-text available
Harini, N.Ramji, B.Sowmya, V.Krishna Menon, VijayGopalakrishnan, E. A.Sajith Variyar, V. V.Soman, K. P.Accurate automatic Identification and localization of spine vertebrae points in CT scan images is crucial in medical diagnosis. This paper presents an automatic feature extraction network, based on transfer learned CNN, in order to handle the avai...
Article
Full-text available
Tree Adjoining Grammars (TAGs) are very useful psycholinguistic formalisms for syntax and dependency analysis of phrase structures. Since natural languages are finitely ambiguous, TAGs are ideal to model them being mildly context sensitive. But these grammars are very hard to parse as they have a worst case complexity of O(n6). In reality most conv...
Article
The widespread use of social media like Facebook, Twitter, Whatsapp, etc. has changed the way News is created and published; accessing news has become easy and inexpensive. However, the scale of usage and inability to moderate the content has made social media, a breeding ground for the circulation of fake news. Fake news is deliberately created ei...
Article
Full-text available
Cybercriminals use domain generation algorithms (DGAs) to prevent their servers from being potentially blacklisted or shut down. Existing reverse engineering techniques for DGA detection is labor intensive, extremely time-consuming, prone to human errors, and have significant limitations. Hence, an automated real-time technique with a high detectio...
Chapter
Deep learning models achieved state-of-the-art performance in many fields including biomedical due to the ability of convolutional network (CNN) models and knowledge of transfer learning approaches. The CNN models gave scope for tuberculosis classification by enabling transfer learning approaches. In this paper, we analyzed the effect of transfer l...
Chapter
Cancer is termed as one of the deadliest disease, and it is becoming a major health problem in the world. This deadly disease can be cured, if it is found at earlier stages. Medical imaging plays an important role in finding this type of diseases and helps in treatment planning. Automated lesion/tumor segmentation is an important and challenging cl...
Article
Full-text available
The world encountered a deadly disease by the beginning of 2020, known as the coronavirus disease (COVID-19). Among the different screening techniques available for COVID-19, chest radiography is an efficient method for disease detection. Whereas other disease detection techniques are time consuming, radiography requires less time to identify abnor...
Conference Paper
Deep Learning plays a major role in advancements in the healthcare domain, of which early disease diagnosis is one main application. With respect to the same, deep learning based classi�fication of brain MRI at the subject level is the requirement in the medical f�ield. In this work, we have implemented an algorithm to identify the most discriminat...
Chapter
Full-text available
Named Entity Recognition (NER) is the process of taking a string and identifying relevant proper nouns in it. In this paper (All codes and datasets used in this paper are available at: https://github.com/AindriyaBarua/Contextual-vs-Non-Contextual-Word-Embeddings-For-Hindi-NER-With-WebApp.) we report the development of the Hindi NER system, in Devan...