Arif Ahmed Sekh

XIM University Bhubaneswar

In precision medicine, there has been a paradigm shift, from a population average based one-size-fits all, to an individualized approach. The aim is to tailor a medicine according to an individual’s genetic make-up and response to drug, diet, and environment. Machine learning algorithms are being developed to dissect inter-individual variability in...

Colorectal Cancer (CRC) is treated as one of a most frequent cancer, and it is the third leading cancer ended with death. Recent progress in deep neural network makes it possible to detect such cancer automatically and accurately from histopathological images. The main challenges of such neural network based model are that we cannot understand why...

Image caption or description generation is a fundamental task that involves computer vision (CV) and natural language processing (NLP) ideas to recognize an image-context and produces description(s) using a natural language. Bengali is one of the world’s most commonly spoken languages, ranking fifth. For this reason, large research achievements hav...

Technological progress opens new ways for us to discover new things every day. Nowadays, we are far too dependent on modern technologies such as social media and digital platforms. The scenario of our daily life has changed drastically within a couple of decades. Just a few decades ago, most people started their morning by looking at the daily news...

Grading and classification of fruits and vegetables has a major role in storage and supply chain. Manual grading is difficult and time-consuming. Therefore, this study employs computer vision (CV) and machine learning algorithms to detect the freshness quality of tomatoes during storage. The freshness quality is classified into 10 grades, where gra...

In this paper, we present a new necklace dataset related to the fashion domain, namely, NecklaceFIR. In recent years, the retrieval of clothing items has attracted a lot of attention. However, fashion products that are complex in nature, such as jewellery, have not received much attention due to the absence of a proper dataset. To address this prob...

Image retrieval is a way to search similar images from a given query image. The method successfully applied to different fashion image retrieval over different garments and footwear. However, research over complex fashion products such as ornaments have not got much momentum due to the complex nature of similarity and unavailability of suitable dat...

Mitochondria play a crucial role in cellular metabolism. This paper presents a novel method to visualize mitochondria in living cells without the use of fluorescent markers. We propose a physics-guided deep learning approach for obtaining virtually labeled micrographs of mitochondria from bright-field images. We integrate a microscope’s point sprea...

Information contained in visual appearance and gait features can play an important role in designing computer vision assisted person re-identification (ReID) systems. Fusion of appearance and gait features has not yet been tested in this domain of research despite its great potential to solve some of the intriguing challenges faced by the research...

Automatic term extraction from a biomedical text is a well-known problem in the area of natural language processing. It is carried out by employing four kinds of measures: linguistic and rule-based, dictionary-based, statistical, and machine learning. Automatic term extraction indicates whether or not two or more words come together in the text mor...

In precision medicine, there has been a paradigm shift, from a population average based one-size-fits all, to an individualized approach. The aim is to tailor a medicine according to an individual’s genetic make-up and response to drug, diet, and environment. Machine learning algorithms are being developed to dissect inter-individual variability in...

Presence of irrelevant sentences containing irrelevant quantities in Math Word Problems (MWPs) throws an immense challenge in formulating the final equation(s). Failure in identification of the relevant quantities with respect to the question asked in an MWP reduces the overall system performance. This paper demonstrates a novel deep learning-based...

Image caption or description generation is a fundamental problem of artificial intelligence. It requires both knowledge, natural language processing, and computer vision together. It automatically produces description(s) from an image. The Bengali language is the fifth language spoken widely in the world. It is considered in many areas of research...

Application of typical Mamdani fuzzy inference system (MFIS) in power system protection has become a common artifact nowadays. The proposed articles on fuzzy logic-based protection initially designed the controller using typical MFIS. The related works mostly followed centroid defuzzification method. It is observed that the defuzzification method g...

Text classification is one of the widely used phenomena in different natural language processing tasks. State-of-the-art text classifiers use the vector space model for extracting features. Recent progress in deep models, recurrent neural networks those preserve the positional relationship among words achieve a higher accuracy. To push text classif...

Nowadays, it is very often that some portion of the Indian traction system is still suffering from a single line railway transportation. This in turn creates a havoc disturbance in maintaining the proper sequence of traction control system. Also, passengers are taking risk to catch the train which is already in motion but no such action has been ta...

Learning through the internet becomes popular that facilitates learners to learn anything, anytime, anywhere from the web resources. Assessment is most important in any learning system. An assessment system can find the self-learning gaps of learners and improve the progress of learning. The manual question generation takes much time and labor. The...

Automatic generation of questions and evaluating their answers is a highly challenging task in natural language processing and educational technology. This work focuses on generating subjective questions and also an evaluation system is suggested for assessing the answers. For generating the questionnaires, key-phrases are extracted from the course...

Segmenting subcellular structures in living cells from fluorescence microscope images is a ground truth (GT)-deficient problem. The microscopes’ three-dimensional blurring function, finite optical resolution due to light diffraction, finite pixel resolution and the complex morphological manifestations of the structures all contribute to GT-hardness...

Automatic assessment of learning is a process where the computer system automatically generates test items and evaluates the responses. Image is one of the major media to assess learning capabilities. In this article, we have proposed a system with a dataset containing images used to evaluate the kid’s ability to answer pictorial questions. The sys...

Multiple-choice questions (MCQs) are used as instrumental tool for assessment, not only in various competitive examinations but also in contemporary information and communications Technology (ICT)-based education, active learning, etc. Therefore, automatic generation of multiple-choice test items from text-based learning material is a truly demandi...

Protection and reliability enactment of electrical systems are important and emerging in power system research. Nowadays, it is very evident that the implementation of an intelligent algorithm is found in the field of substation equipment protection and relaying purposes. Majority of the researches are based on single load connected to a single fee...

Search-by-example, i.e. finding images that are similar to a query image, is an indispensable function for various modern image search engines. The applications of such systems are manifold. The primary application of search-by-example is in recommending fashion materials based on user interests. There are various challenges in this area of researc...

Manual processing of a large volume of video data captured through closed-circuit television is challenging due to various reasons. First, manual analysis is highly time-consuming. Moreover, as surveillance videos are recorded in dynamic conditions such as in the presence of camera motion, varying illumination, or occlusion, conventional supervised...

Diabetes mellitus affected an estimated 463 million people in the year 2019. The number of diabetic patients is projected to increase to an alarming figure of 700 million by the year 2045, out of which 90–95% of them are expected to be type 2 diabetes mellitus (T2DM) patients. The research presented an alternative way of state-of-the-art insulin th...

There is a growing interest in automatic crafting of neural network architectures as opposed to expert tuning to find the best architecture. On the other hand, the problem of stock trading is considered one of the most dynamic systems that heavily depends on complex trends of the individual company. This paper proposes a novel self-evolving neural...

Fashion image retrieval (FIR) is a challenging task, which involves similar item searching from a massive collection of fashion products based on a query image. FIR in different garments and shoes are popular in literature. More complex fashion products such as ornaments are getting less attention. Here, we introduce a new earring dataset, namely,...

Quality-based grouping or grading of fruits and vegetables played an important role in many stages of agricultural production. The method is used for sorting items based on the size, color, presence of damage etc. Manual grading is laborious and time consuming. Hence, not suitable for processing massive amounts. Grading different fruits and vegetab...

In the present scenario, the protection system has become an important issue in the field of the power system. Intelligent protection system has been introduced in many sectors like a transmission line, distribution network, power transformer, and many more. Many researchers have published their work using low voltage DC breakers, VCB, SF6, and oth...

One of the most important domains of concern in electrical power system engineering is the protection and reliability of the system. Nowadays, it is quit evident that the implementation of an intelligent algorithm is paramount in providing protection to the equipment of a substation including auxiliary components using relays and breakers as well....

Interpretabilty is one of the desired characteristics in various classification task. Rule-based system and fuzzy logic can be used for interpretation in classification. The main drawback of rule-based system is that it may contain large complex rules for classification and sometimes it becomes very difficult in interpretation. Rule reduction is al...

Examining specific sub-cellular structures while minimizing cell perturbation is important in the life sciences. Fluorescence labeling and imaging is widely used for introducing specificity despite its perturbative and photo-toxic nature. With the advancement of deep learning, digital staining routines for label-free analysis have emerged as a repl...

In the present scenario the protection system has become an important issue in the field of the power system. An Intelligent protection system has been introduced in many sectors like low voltage DC breakers, VCB, SF6 and so on. The said protection schemes have been developed to control the moving contacts using intelligent algorithms for tripping...

Surveillance camera usage has increased significantly for visual surveillance. Manual analysis of large video data recorded by cameras may not be feasible on a larger scale. In various applications, deep learning-guided supervised systems are used to track and identify unusual patterns. However, such systems depend on learning which may not be poss...

The recent worldwide outbreak of the novel coronavirus (COVID-19) has opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges...

Protection and reliability enactment of electrical systems are important and emerging in power system research. Nowadays, it is very evident that the implementation of an intelligent algorithm is found in the field of substation equipment's protection and relaying purposes. Majority of the researches are based on single load connected to a single f...

In the present scenario the protection system has become an important issue in the field of the power system. Intelligent protection system has been introduced in many sectors like transmission line, distribution network, power transformer and many more. Many researchers have explored using low voltage DC breakers, VCB, SF6 and so on. In the previo...

Typical person re-identification frameworks search for k best matches in a gallery of images that are often collected in varying conditions. The gallery usually contains image sequences for video re-identification applications. However, such a process is time consuming as video re-identification involves carrying out the matching process multiple t...

Automatic grading of retinal blood vessels from fundus image can be a useful tool for diagnosis, planning and treatment of eye. Automatic diagnosis of retinal images for early detection of glaucoma, stroke, and blindness is emerging in intelligent health care system. The method primarily depends on various abnormal signs, such as area of hard exuda...

Streaming classification methods assume the number of input features is fixed and always received. But in many real-world scenarios demand is some input features are reliable while others are unreliable or inconsistent. In this paper, we propose a novel deep learning-based model called Auxiliary Network (Aux-Net), which is scalable and agile. It em...

In many real-world scientific problems, generating ground truth (GT) for supervised learning is almost impossible. The causes include limitations imposed by scientific instrument, physical phenomenon itself, or the complexity of modeling. Performing artificial intelligence (AI) tasks such as segmentation, tracking, and analytics of small sub-cellul...

Detecting and analyzing nanoscale motion patterns of vesicles, smaller than the microscope resolution (∼ 250 nm), inside living biological cells is a challenging problem. State-of-the-art CV approaches based on detection, tracking, optical flow or deep learning perform poorly on this problem. We propose an integrative approach built upon physics-ba...

This paper presents a novel deep learning based approach to solving arithmetic word problems. Solving different types of mathematical (math) word problems (MWP) is a very complex and challenging task as it requires Natural Language Understanding (NLU) and Commonsense knowledge. An application on this can benefit learning (education) technologies su...

The pandemic coronavirus has explored all over the world with a devastated negative impact on humanity indeed. The mortality rate of the disease is increasing rapidly as the approved drug is not available yet. Only isolation from the infected individual or community is the only choice to save our existence. As the human is the only carrier so in th...

One of the most important domain in electrical power system engineering is the protection and reliability of the system. Nowadays, it is very evident that the implementation of an intelligent algorithm is found in the field of substation equipment's protection and relaying purposes. The researches are based on single load connected to a single feed...

Abstract: Isolation of infected patient seems to be the most effective way to fight against COVID-19. Isolation chamber is a separate room used to isolate patients suffering from highly transmitting infectious diseases. Several rooms for individual patients are allotted and placed together in an isolation unit or isolation chamber. We have proposed...

Diagrammatic reasoning (DR) problems are well known. However, solving DR problems represented in 4 × 1 Raven’s Progressive Matrix (RPM) form using computer vision and pattern recognition has not yet been tried. Emergence of deep learning techniques aided by advanced computing can be exploited to solve such DR problems. In this paper, we propose a n...

Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeli...

The recent worldwide outbreak of the novel corona-virus (COVID-19) opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of...

Designing an instrument protection system has been considered as one of the most challenging domains in the power system. Intelligent tripping mechanism has been introduced in few sectors for controlling the moving contacts of a single operating relay connected to an electrical system. In this work, we have developed a cascaded relaying for a prior...

The application of artificial intelligence (AI) is relatively new in microscopy. Advances in microscopes and AI are greatly expanding the possibilities for microscopy image analysis and interpretation, which is of special importance to researchers in biology. It has been noted earlier that the state-of-the-art AI methods generally perform poorly du...

This book describes the latest advances in intelligent techniques such as fuzzy logic, neural networks, and optimization algorithms, and their relevance in building intelligent information systems in combination with applied mathematics. The authors also outline the applications of these systems in areas like intelligent control and robotics, patte...

Nowadays, it is very often that some portion of the Indian traction system is still suffering from a single line railway transportation. This in turn creates a havoc disturbance in maintaining the proper sequence of traction control system. Also, passengers are taking risk to catch the train which is already in motion but no such action has been ta...

One of the most important domains of concern in electrical power system engineering is the protection and reliability of the system. Nowadays, it is quit evident that the implementation of an intelligent algorithm is paramount in providing protection to the equipment of a substation including auxiliary components using relays and breakers as well....

Knowledge acquisition is the prime objective of a learner from an educational system and evaluating the learner's knowledge is the eventual goal of an examination process. This paper introduces a system which is able to produce fill‐in‐the‐blank questions to test the knowledge of a learner that he or she has accumulated after reading a course mater...

Synopsis of a long-duration video has many applications in intelligent transportation systems. It can help to monitor traffic with lesser manpower. However, generating meaningful synopsis of a long-duration video recording can be challenging. Often summarized outputs include redundant contents or activities that may not be helpful to the observer....

Air-writing is the process of writing characters or words in free space using finger or hand movements without the aid of any hand-held device. In this work, we address the problem of mid-air finger writing using web-cam video as input. In spite of recent advances in object detection and tracking, accurate and robust detection and tracking of the f...

This paper presents a novel method to represent hours of surveillance video in a pattern-based text log. We present a tag and template-based technique that automatically generates natural language descriptions of surveillance events. We combine the output of some of the existing object tracker, deep learning guided object and action classifiers, an...

Typical person re-identification frameworks search for k best matches in a gallery of images that are often collected in varying conditions. The gallery may contain image sequences when re-identification is done on videos. However, such a process is time consuming as re-identification has to be carried out multiple times. In this paper, we extract...