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Full-Text Articles in Engineering
Embedded Ai For Wheat Yellow Rust Infection Type Classification, Uferah Shafi, Rafia Mumtaz, Muhammad Deedahwar Mazhar Qureshi, Zahid Mahmood, Sikander Khan Tanveer, Ihsan Ul Haq, Syed Mohammad Hassan Zaidi
Embedded Ai For Wheat Yellow Rust Infection Type Classification, Uferah Shafi, Rafia Mumtaz, Muhammad Deedahwar Mazhar Qureshi, Zahid Mahmood, Sikander Khan Tanveer, Ihsan Ul Haq, Syed Mohammad Hassan Zaidi
Articles
Wheat is the most important and dominating crop in Pakistan in terms of production and acreage, which is grown on 37% of the cultivated area, accounting for 70% of the total production. However, wheat yield is highly affected by stripe rust, which is considered the most devastating fungal disease, causing 5.5 million tonnes of loss per year globally. In order to minimize this loss, the accurate and timely detection of rust disease is crucial instead of manual inspection. Towards this end, we propose a system to detect wheat rust disease and classify its infection types into four classes, including healthy, …
Interpreting Energy Utilisation With Shapley Additive Explanations By Defining A Synthetic Data Generator For Plausible Charging Sessions Of Electric Vehicles, Prasant Kumar Mohanty, Gayadhar Panda, Malabika Basu, Diptendu Sinha Roy
Interpreting Energy Utilisation With Shapley Additive Explanations By Defining A Synthetic Data Generator For Plausible Charging Sessions Of Electric Vehicles, Prasant Kumar Mohanty, Gayadhar Panda, Malabika Basu, Diptendu Sinha Roy
Articles
Electric vehicles (EVs) are an effective solution for reducing reliance on non-renewable energy sources. However, the lack of charging infrastructure and concerns over their range are some of the biggest hurdles to adopting EVs. Charging infrastructure for EVs is, however, on the rise. Proper planning of charging stations vis-`a-vis road networks and related points of interest such as transportation hubs, schools, shopping centres, etc., alongside such roads become vital to laying out a plan for such infrastructure, particularly for developing countries like India where EV adoption is relatively in a nascent stage. Synthetic datasets can help overcome these hurdles and …
How Visual Stimuli Evoked P300 Is Transforming The Brain–Computer Interface Landscape: A Prisma Compliant Systematic Review, Jai Kalra, Prashasti Mittal, Nirmiti Mittal, Abhishek Arora, Utkarsh Tewari, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Luca Longo
How Visual Stimuli Evoked P300 Is Transforming The Brain–Computer Interface Landscape: A Prisma Compliant Systematic Review, Jai Kalra, Prashasti Mittal, Nirmiti Mittal, Abhishek Arora, Utkarsh Tewari, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Luca Longo
Articles
Non-invasive Visual Stimuli evoked-EEGbased P300 BCIs have gained immense attention in recent years due to their ability to help patients with disability using BCI-controlled assistive devices and applications. In addition to the medical field, P300 BCI has applications in entertainment, robotics, and education. The current article systematically reviews 147 articles that were published between 2006-2021*. Articles that pass the pre-defined criteria are included in the study. Further, classification based on their primary focus, including article orientation, participants’ age groups, tasks given, databases, the EEG devices used in the studies, classification models, and application domain, is performed. The application-based classification considers …
Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo
Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo
Articles
Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions, and disordered thinking. Traditionally, SCZ diagnosis involves the subject’s interview by a skilled psychiatrist. The process needs time and is bound to human errors and bias. Recently, brain connectivity indices have been used in a few pattern recognition methods to discriminate neuro-psychiatric patients from healthy subjects. The study presents Schizo-Net , a novel, highly accurate, and reliable SCZ diagnosis model based on a late multimodal fusion of estimated brain connectivity indices from EEG activity. First, the raw EEG activity is pre-processed exhaustively to remove unwanted artifacts. Next, six brain …
Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed
Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed
Articles
The brain is one of the most important and complex organs in the body, consisting of billions of individual cells. Uncontrolled growth and expansion of aberrant cell populations within or around the brain are the main causes of brain tumors. These cells have the potential to harm healthy cells and impair brain function [1]. Tumors can be detected using medical imaging techniques, which are considered the most popular and accurate way to classify different types of cancer, and this procedure is even more crucial as it is noninvasive [2]. Magnetic resonance imaging (MRI) is one such medical imaging technique that …