[HTML][HTML] Object detection using YOLO: Challenges, architectural successors, datasets and applications
T Diwan, G Anirudh, JV Tembhurne - multimedia Tools and Applications, 2023 - Springer
Object detection is one of the predominant and challenging problems in computer vision.
Over the decade, with the expeditious evolution of deep learning, researchers have …
Over the decade, with the expeditious evolution of deep learning, researchers have …
[Retracted] Deep Neural Networks for Medical Image Segmentation
P Malhotra, S Gupta, D Koundal… - Journal of …, 2022 - Wiley Online Library
Image segmentation is a branch of digital image processing which has numerous
applications in the field of analysis of images, augmented reality, machine vision, and many …
applications in the field of analysis of images, augmented reality, machine vision, and many …
[HTML][HTML] Contributions of smart city solutions and technologies to resilience against the COVID-19 pandemic: A literature review
Since its emergence in late 2019, the COVID-19 pandemic has swept through many cities
around the world, claiming millions of lives and causing major socio-economic impacts. The …
around the world, claiming millions of lives and causing major socio-economic impacts. The …
COVID-19 image classification using deep learning: Advances, challenges and opportunities
Abstract Corona Virus Disease-2019 (COVID-19), caused by Severe Acute Respiratory
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
[HTML][HTML] Recognition of leaf disease using hybrid convolutional neural network by applying feature reduction
Agriculture is crucial to the economic prosperity and development of India. Plant diseases
can have a devastating influence towards food safety and a considerable loss in the …
can have a devastating influence towards food safety and a considerable loss in the …
[HTML][HTML] Neural decoding of EEG signals with machine learning: A systematic review
Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …
Semantic segmentation for multiscale target based on object recognition using the improved Faster-RCNN model
D Jiang, G Li, C Tan, L Huang, Y Sun, J Kong - Future Generation …, 2021 - Elsevier
Image semantic segmentation has received great attention in computer vision, whose aim is
to segment different objects and provide them different semantic category labels so that the …
to segment different objects and provide them different semantic category labels so that the …
[HTML][HTML] Application of deep learning techniques in diagnosis of covid-19 (coronavirus): a systematic review
YH Bhosale, KS Patnaik - Neural processing letters, 2023 - Springer
Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth
century. Covid-19 has already endangered the lives of millions of people worldwide due to …
century. Covid-19 has already endangered the lives of millions of people worldwide due to …
Blockchain and AI-based solutions to combat coronavirus (COVID-19)-like epidemics: A survey
The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel
virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of …
virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of …
[HTML][HTML] Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives
Artificial intelligence (AI) is being used to aid in various aspects of the COVID-19 crisis,
including epidemiology, molecular research and drug development, medical diagnosis and …
including epidemiology, molecular research and drug development, medical diagnosis and …