Malay Kishore Dutta's research while affiliated with Center for Advanced Legal Studies and other places
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Publications (299)
Plant diseases are a critical issue in the farming industry, and early identification is essential for plant monitoring. The leaves of plants represent the majority of disease symptoms, however, leaf analysis by specialists in laboratories is expensive and time‐consuming. Hence, there is a necessity for automated and more accurate plant disease det...
Background and objectives
Microscopic images are an important part for haematologists in diagnosing various diseases in the blood cell. Changes in blood cells are caused by malaria disease, and early diagnosis can prevent the disease from entering its severe stage.
Methods
In this paper, an automated non-invasive and efficient deep learning-based...
An electromagnetic field radiations (EMF) emanating from the cell phones affect the brain and other organs in living organisms. Therefore, the objective of the present study is to examine whether the EMF radiations affect the brain cells or not, using the transfer learning-based methodology. The observations made in the present study are based on o...
Manual analysis of the indirect-immunofluorescence (IIF) human epithelial cell Type-2 (HEp-2) cell image for the diagnosis of an auto-immune disease is a subjective and time-consuming process, and it is also prone to human-errors. The present work proposes an automatic capsule neural network (CapsNet) based framework for HEp-2 cell image classifica...
Breast tumor is one of the major cause of death among women all over the world. Ultrasound imaging-based breast abnormality detection and classification play a vital role to develop an automatic computer-aided diagnostic system. In this paper, deep learning technology is integrated with ultrasound images for pre-screening of breast cancer. Two brea...
Blood cell analysis is an important part of the health and immunity assessment. There are three major components of the blood: red blood cells, white blood cells, and platelets. The count and density of these blood cells are used to find multiple disorders like blood infections (anemia, leukemia, among others). Traditional methods are time-consumin...
Background and objectives The lack of medical facilities in isolated areas makes many patients remain aloof from quick and timely diagnosis of cardiovascular diseases, leading to high mortality rates. A deep learning based method for automatic diagnosis of multiple cardiac diseases from Phonocardiogram (PCG) signals is proposed in this paper.
Metho...
Preserving the quality of fish is a challenging task. Several different cooling methods and materials are used during their storage, transportation purpose. These are responsible factors that decide the freshness of a post harvested fish. In this proposed algorithm, a computer vision-based technique is developed to predict the freshness level of fi...
Artificial Intelligence in Agriculture: Efficient and Automated Plant Disease Detection and Classification
In telemedicine, images may possibly be tailored deliberately or unintentionally as this transmission may occur all the way through vulnerable networks. Prior to making any investigative judgment, the integrity of watermarked medical image has to be validated by the medical practitioner so as to avoid erroneous verdict. An approach that can be used...
Acrylamide is a carcinogenic chemical compound found in carbohydrate rich foods when fried and baked at high temperatures, like potato chips. Identification of such toxic substances in food items is of tremendous significance. Conventional identification approaches like liquid chromatography-mass spectrometry (LC–MS) are time-consuming, destructive...
Chronic respiratory diseases (CRDs) are common across the world. In many countries, there is a shortage of medical professionals and hence there is a need to develop artificial intelligence-based automatic diagnostic tools that can help to diagnose pulmonary diseases by computing the lung sounds. This paper presents an automatic classification meth...
The world is substantially reliant on fossil fuels and the rapid depletion of these fuels raise the concern to find out alternative efficient energy resources. Microalgae biofuels emerged as one of the promising alternate renewable sources of energy that have the capability to substitute fossil fuels. This paper presents a new approach to explore t...
Background and objectives
: Advancement of the ultra-fast microscopic images acquisition and generation techniques give rise to the automated artificial intelligence (AI)-based microscopic images classification systems. The earlier cell classification systems classify the cell images of a specific type captured using a specific microscopy technique...
Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is a pathogen responsible for one of the most massive pandemics in modern history. In certain patients with prolonged resorption of pulmonary involvement, organizing pneumonia develops which may lead to irreversible fibrotic damage of the lungs. According to some studies, corticosteroid tr...
Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is a pathogen responsible for one of the most massive pandemics in modern history. In certain patients with prolonged resorption of pulmonary involvement, organizing pneumonia develops which may lead to irreversible fibrotic damage of the lungs. According to some studies, corticosteroid tr...
The classification of bioimages plays an important role in several biological studies, such as subcellular localisation, phenotype identification and other types of histopathological examinations. The objective of the present study was to develop a computer-aided bioimage classification method for the classification of bioimages across nine diverse...
Glioma is the most pernicious cancer of the nervous system, with histological grade influencing the survival of patients. Despite many studies on the multimodal treatment approach, survival time remains brief. In this study, a novel two-stage ensemble of an ensemble-type machine learning-based predictive framework for glioma detection and its histo...
Fish is one of the most nutritive food products whose quality gets affected along the food supply chain from harvesting to consumption. Freshness of fish, during that time, gets affected owing to the chemical decomposition of focal tissues like gills, eyes and skin. A novel mathematical model, is being proposed in this article, for the computation...
Deep-fried carbohydrate-rich foods items such as potato chips and French fries are one of the most popular snack foods consumed across the globe. In the production of these carbohydrate-rich foods items, a compound known as acrylamide is formed which is carcinogen and mutagen as well. The conventional chemical-based methods for detection of the pre...
A child has specific language impairment (SLI) or developmental dysphasia (DD) when the speech is delayed or has disordered language development for no apparent reason. As it may be related to loss of hearing, speech abnormality should be diagnosed at an early stage. The existing methods are mainly based on the utterance of vowels and have a high m...
Cervical cancer is still one of the most prevalent cancers in women and a significant cause of mortality. Cytokine gene variants and socio-demographic characteristics have been reported as biomarkers for determining the cervical cancer risk in the Indian population. This study was designed to apply a machine learning-based model using these risk fa...
Fetal heart rate (FHR) is used to monitor the fetal state by obstetricians as a screening tool. Common guidelines for visual interpretation of FHR signals results in significant subjective variability due to the fetal physiological dynamics complexity. Automated diagnostic technology can assist obstetricians in medical decisions based on artificial...
Heavy metal pollution in water negatively affects the health status of fishes and makes it toxic to human health. Conventional chemical‐based methods for fish quality assessment are destructive, highly time‐consuming, and require expensive machines and expert manpower. In this novel pilot study, the image of the gill tissue of fish is considered as...
Viral infection in crops is something that may lead to a huge loss in crop yield as there are no known recovery procedures. Also, at the onset of yellowing in a leaf, no observable changes occur in leaf structure and geometry. Therefore, the manual inspection and diagnosis of such diseases by the framers in agricultural fields are difficult on a la...
Plant diseases are one of the major concern in the agricultural domain and their automatic identification is very crucial in monitoring the plants. Most of the disease symptoms are reflected in the leaves of plants but the leaf diagnosis by experts in laboratories are costly and time-consuming. In this paper, a deep-learning-based approach is prese...
Bacteriosis is one of the most common and devastating diseases for peach crops all over the world. Timely identification of bacteriosis disease is necessary for reducing the usage of pesticides and minimize loss of crops. In this proposed work, convolutional neural network (CNN) models using deep learning and an imaging method is developed for bact...
The lethal novel coronavirus disease 2019 (COVID-19) pandemic is affecting the health of the global population severely, and a huge number of people may have to be screened in the future. There is a need for effective and reliable systems that perform automatic detection and mass screening of COVID-19 as a quick alternative diagnostic option to con...
Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine le...
Cardiovascular diseases are one of the most fatal diseases across the globe. Clinically, conventional stethoscope is used to check the medical condition of a human heart. Only a trained medical professional can understand and interpret the heart auscultations clinically. This paper presents a machine learning-based automatic classification system b...
Various viral diseases affect the growth of the plants that causes a huge loss to farmers. If the viral infection could be noticed at earlier stages, then recovery procedures and respective action can be taken on time. Thus, there is a need for developing automatic viral infection detection methods for monitoring crops and analyzing symptoms at dif...
Diabetic retinopathy (DR) is one of the complications of diabetes affecting the eyes. If not treated at an early stage, then it can cause permanent blindness. The present work proposes a method for automatic detection of pathologies that are indicative parameters for DR and use them strategically in a framework to grade the severity of the disease....
The biometric identification is an important topic with applications in different fields. Among the different modalities, based-handwriting biometric is a very useful and extended modality, and the most known one is the signature. The use of handwritten texts is researched presenting a biometric system for identifying writers from their handwritten...
Background and objectives:
Cardiovascular diseases are critical diseases and need to be diagnosed as early as possible. There is a lack of medical professionals in remote areas to diagnose these diseases. Artificial intelligence-based automatic diagnostic tools can help to diagnose cardiac diseases. This work presents an automatic classification m...
Visually impaired people face numerous difficulties in their daily life, and technological interventions may assist them to meet these challenges. This paper proposes an artificial intelligence-based fully automatic assistive technology to recognize different objects, and auditory inputs are provided to the user in real time, which gives better und...
Identification of statement is truth or lie is a major problem. It has various applications for safety and clime control. Traditionally physiological activities are monitored during the question-answer round and compare to a normal level. However, because the subject can control his/her physiological reactions, therefore, to overcome these brain si...
The brain of a human and other organisms is affected by the electromagnetic field (EMF) radiations, emanating from the cell phones and mobile towers. Prolonged exposure to EMF radiations may cause neurological changes in the brain, which in turn may bring chemical as well as morphological changes in the brain. Conventionally, the identification of...
Electromagnetic field (EMF) radiations from mobile phones and cell tower affect brain of humans and other organisms in many ways. Exposure to EMF could lead to neurological changes causing morphological or chemical changes in the brain and other internal organs. Cellular level analysis to measure and identify the effect of mobile radiations is an e...
Rice is among the three most consumed grains in the world, which makes its quality assessment an important task. Conventional methods based on manual inspection need specialized manpower, are time-consuming, error-prone, and at times, destructive. This paper presents an automatic, real-time and cost-effective image processing based system for class...
