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- research-articleJanuary 2024
Securing AI‐based healthcare systems using blockchain technology: A state‐of‐the‐art systematic literature review and future research directions
Transactions on Emerging Telecommunications Technologies (TETT), Volume 35, Issue 1https://doi.org/10.1002/ett.4884AbstractHealthcare institutions are progressively integrating artificial intelligence (AI) into their operations. The extraordinary potential of AI is restricted by insufficient medical data for AI model training and adversarial attacks wherein ...
The applicability of blockchain properties from protecting and validating datasets, protecting classifiers/algorithms protecting the post‐training environment in AI is detailed in this image. image image
- research-articleJanuary 2023
TomConv: An Improved CNN Model for Diagnosis of Diseases in Tomato Plant Leaves
Procedia Computer Science (PROCS), Volume 218, Issue CPages 1825–1833https://doi.org/10.1016/j.procs.2023.01.160AbstractCrop disease in the plant is a significant issue in the agriculture sector, and it is currently very difficult to detect these illnesses in crop leaves. The foundation of the global economy is agriculture. India ranks second in the production of ...
- research-articleNovember 2022
ICACIA: An Intelligent Context-Aware framework for COBOT in defense industry using ontological and deep learning models
- Arodh Lal Karn,
- Sudhakar Sengan,
- Ketan Kotecha,
- Irina V. Pustokhina,
- Denis A. Pustokhin,
- V. Subramaniyaswamy,
- Dharam Buddhi
Robotics and Autonomous Systems (ROAS), Volume 157, Issue Chttps://doi.org/10.1016/j.robot.2022.104234AbstractMost of the world’s most advanced defense technologies are robots, and the defence industry is slowly moving toward including AI in the military robots they build. For these smart robots to make their own decisions about where to go ...
Highlights- We propose a knowledge-based framework for humans and robots to work together to understand the context of Defense missions.
- research-articleOctober 2022
A scoping review on multi-fault diagnosis of industrial rotating machines using multi-sensor data fusion
Artificial Intelligence Review (ARTR), Volume 56, Issue 5Pages 4711–4764https://doi.org/10.1007/s10462-022-10243-zAbstractRotating machines is an essential part of any manufacturing industry. The sudden breakdown of such machines due to improper maintenance can also lead to the industries' shutdown. The era of the 4th industrial revolution is taking its major shape ...
- research-articleSeptember 2022
Reconfigurable and hardware efficient adaptive quantization model-based accelerator for binarized neural network
Computers and Electrical Engineering (CENG), Volume 102, Issue Chttps://doi.org/10.1016/j.compeleceng.2022.108302Highlights- Adaptive spatial amplitude model is propose to reduce complexity of BNN accelerator.
Binarized neural networks (BNNs) architecture play a vital role in the development of deep learning accelerator for memory-constrained IoT devices. However, the cost-efficiency of the domain-specific accelerators still requires a ...
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- research-articleJune 2022JUST ACCEPTED
TAM: A Front-End to an Auto-Parallelizing Compiler
- Ashish Sharma,
- Mayank Badjatiya,
- Aayush Sahay,
- Aryan Verma,
- Ayush Agarwal,
- Gaurav Singal,
- Deepak Garg,
- Deepak Kumar Jain,
- Ketan Kotecha
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Just Accepted https://doi.org/10.1145/3543510The multi-core architecture has revolutionized the parallel computing. Despite this, the modern age compilers have a long way to achieve auto-parallelization. Through this paper, we introduce a language that encouraging the auto-parallelization. We are ...
- research-articleJune 2022
Target-DBPPred: An intelligent model for prediction of DNA-binding proteins using discrete wavelet transform based compression and light eXtreme gradient boosting
Computers in Biology and Medicine (CBIM), Volume 145, Issue Chttps://doi.org/10.1016/j.compbiomed.2022.105533AbstractDNA-protein interaction is a critical biological process that performs influential activities, including DNA transcription and recombination. DBPs (DNA-binding proteins) are closely associated with different kinds of human diseases (...
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Highlights- Designed a novel predictor named Target-DBPPred for prediction of DNA-binding proteins.
- research-articleMay 2022
Multimodal Co-learning: Challenges, applications with datasets, recent advances and future directions
Information Fusion (INFU), Volume 81, Issue CPages 203–239https://doi.org/10.1016/j.inffus.2021.12.003AbstractMultimodal deep learning systems that employ multiple modalities like text, image, audio, video, etc., are showing better performance than individual modalities (i.e., unimodal) systems. Multimodal machine learning involves multiple ...
- research-articleApril 2022
Few-Shot learning for face recognition in the presence of image discrepancies for limited multi-class datasets
AbstractOne of the primary limitations of deep learning is data-hungry techniques. Deep learning approaches do not typically generalize well for limited datasets with fewer samples. Drawing the inspiration from the way human beings are capable ...
Highlights- Implementation of the Few-Shot Learning approach to develop face recognition system for very few images for a specific class (person).
- research-articleMarch 2022
Employing multimodal co-learning to evaluate the robustness of sensor fusion for industry 5.0 tasks
Soft Computing - A Fusion of Foundations, Methodologies and Applications (SOFC), Volume 27, Issue 7Pages 4139–4155https://doi.org/10.1007/s00500-022-06802-9AbstractIndustry 5.0 focuses on collaboration between humans and machines, demanding robustness and efficiency and the accuracy of intelligent and innovative components used. The use of sensors and the fusion of data obtained from various sensors/modes ...
- research-articleMarch 2022
Deep dive in retinal fundus image segmentation using deep learning for retinopathy of prematurity
Multimedia Tools and Applications (MTAA), Volume 81, Issue 8Pages 11441–11460https://doi.org/10.1007/s11042-022-12396-zAbstractSegmentation of retinal structures, namely optic disc, vessel, demarcation line, and ridge, is essential for describing the characteristics of Retinopathy of Prematurity (ROP). Computerized systems are being developed for automatic segmentation in ...
- research-articleJanuary 2022
Enhanced Security Against Volumetric DDoS Attacks Using Adversarial Machine Learning
With the increasing number of Internet users, cybersecurity is becoming more and more critical. Denial of service (DoS) and distributed denial of service (DDoS) attacks are two of the most common types of attacks that can severely affect a website or a ...
- research-articleJanuary 2022
An Enhanced Dynamic Nonlinear Polynomial Integrity-Based QHCP-ABE Framework for Big Data Privacy and Security
- Mukesh Soni,
- Kranthi Kumar Singamaneni,
- Abhinav Juneja,
- Mohammed Abd-Elnaby,
- Kamal Gulati,
- Ketan Kotecha,
- A. P. Senthil Kumar
Topics such as computational sources and cloud-based transmission and security of big data have turned out to be a major new domain of exploration due to the exponential evolution of cloud-based data and grid facilities. Various categories of cloud ...
- research-articleDecember 2021
Applying and Understanding an Advanced, Novel Deep Learning Approach: A Covid 19, Text Based, Emotions Analysis Study
Information Systems Frontiers (KLU-ISFI), Volume 23, Issue 6Pages 1431–1465https://doi.org/10.1007/s10796-021-10152-6AbstractThe pandemic COVID 19 has altered individuals’ daily lives across the globe. It has led to preventive measures such as physical distancing to be imposed on individuals and led to terms such as ‘lockdown,’ ‘emergency,’ or curfew’ to emerge in ...
- research-articleDecember 2021
Recop: fine-grained opinions and sentiments-based recommender system for industry 5.0
Soft Computing - A Fusion of Foundations, Methodologies and Applications (SOFC), Volume 27, Issue 7Pages 4051–4060https://doi.org/10.1007/s00500-021-06590-8AbstractIn the futuristic Industry framework, user interactions with the product are seamlessly integrated with the product life cycle which results in Information overload. The shopbots were proposed in Industry 4.0 where the more focus was on process ...
- research-articleNovember 2021
Development and deployment of a generative model-based framework for text to photorealistic image generation
AbstractThe task of generating photorealistic images from their textual descriptions is quite challenging. Most existing tasks in this domain are focused on the generation of images such as flowers or birds from their textual description, ...
- research-articleJune 2021
Machine learning techniques and older adults processing of online information and misinformation: A covid 19 study
AbstractThis study is informed by two research gaps. One, Artificial Intelligence's (AI's) Machine Learning (ML) techniques have the potential to help separate information and misinformation, but this capability has yet to be empirically ...
Highlights- Machine learning techniques classified COVID-19 information and misinformation.
- research-articleJanuary 2021
Lightweight Object Detection Ensemble Framework for Autonomous Vehicles in Challenging Weather Conditions
The computer vision systems driving autonomous vehicles are judged by their ability to detect objects and obstacles in the vicinity of the vehicle in diverse environments. Enhancing this ability of a self-driving car to distinguish between the elements of ...
- research-articleJanuary 2021
Random Forest Bagging and X-Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data
- Deepak Kumar Jain,
- Rajesh Kumar Dhanaraj,
- Vinothsaravanan Ramakrishnan,
- M. Poongodi,
- Lalitha Krishnasamy,
- Mounir Hamdi,
- Ketan Kotecha,
- V. Vijayakumar
In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the ...
- research-articleAugust 2020
Data augmentation using MG-GAN for improved cancer classification on gene expression data
Soft Computing - A Fusion of Foundations, Methodologies and Applications (SOFC), Volume 24, Issue 15Pages 11381–11391https://doi.org/10.1007/s00500-019-04602-2AbstractMolecular biology studies on cancer, using gene expression datasets, have revealed that the datasets have a very small number of samples. Obtaining medical data is difficult and expensive due to privacy constraints. Accuracy of classifiers depends ...