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- research-articleMarch 2024
Classification of COVID-19 on Chest X-Ray Images Using Deep Learning Model with Histogram Equalization and Lung Segmentation
AbstractArtificial intelligence techniques coupled with biomedical analysis have been play a critical role during COVID-19 pandemics as it helps to release the overwhelming pressure from healthcare systems and physicians. As the ongoing COVID-19 crisis ...
- research-articleFebruary 2024
Deep-GAN: an improved model for thyroid nodule identification and classification
Neural Computing and Applications (NCAA), Volume 36, Issue 14Pages 7685–7704https://doi.org/10.1007/s00521-024-09492-6AbstractTailoring a deep convolutional neural network (DCNN) is a tedious and time-consuming task in the field of medical image analysis. In this research paper, Deep-generative adversial neural network (Deep-GAN) based model is proposed using grid search ...
- research-articleApril 2024
A Novel Approach Using Transfer Learning Architectural Models Based Deep Learning Techniques for Identification and Classification of Malignant Skin Cancer
- Balambigai Subramanian,
- Suresh Muthusamy,
- Kokilavani Thangaraj,
- Hitesh Panchal,
- Elavarasi Kasirajan,
- Abarna Marimuthu,
- Abinaya Ravi
Wireless Personal Communications: An International Journal (WPCO), Volume 134, Issue 4Pages 2183–2201https://doi.org/10.1007/s11277-024-11006-5AbstractMelanoma, a form of skin cancer originating in melanocyte cells, poses a significant health risk, although it is less prevalent than other types of skin cancer. Its detection presents challenges, even under expert observation. To enhance the ...
- research-articleFebruary 2024
Adaptive multi-scale attention convolution neural network for cross-domain fault diagnosis
Expert Systems with Applications: An International Journal (EXWA), Volume 236, Issue Chttps://doi.org/10.1016/j.eswa.2023.121216AbstractThis paper proposes a novel approach named adaptive multi-scale attention convolution neural network (AmaCNN) to accurately detect cross-domain faults with very few labelled data. In AmaCNN, multi-scale feature fusion CNN (MSFFCNN) with a multi-...
- research-articleJuly 2024
Segmentation and Classification of Lung Cancer using Deep Learning Techniques
Procedia Computer Science (PROCS), Volume 235, Issue CPages 3226–3235https://doi.org/10.1016/j.procs.2024.04.305AbstractTo increase the survival rates for lung cancer, early identification and diagnosis are essential. The detection becomes crucial for a number of reasons, including visual similarity, heterogeneity, and low contrast variation. The several varieties ...
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- research-articleDecember 2023
SMDF: Spatial Mass Distribution Features and Deep Learning-Based Technique for Human Activity Recognition
AbstractAutomatic detection of human activity is one of the growing research areas due to the wide range of applications like elderly and patient monitoring for ambient assistive living, visual surveillance, etc. This paper presents a novel bi-channel ...
- ArticleApril 2024
Boosting Diagnostic Accuracy of Osteoporosis in Knee Radiograph Through Fine-Tuning CNN
Big Data Analytics in Astronomy, Science, and EngineeringPages 97–109https://doi.org/10.1007/978-3-031-58502-9_6AbstractOsteoporosis is a serious worldwide medical problem that might be challenging to identify promptly owing to the absence of indicators. At the moment, DEXA scans, CT scans, and other techniques with expensive devices and payroll expenses are the ...
- ArticleSeptember 2023
Robustness of Biologically-Inspired Filter-Based ConvNet to Signal Perturbation
Artificial Neural Networks and Machine Learning – ICANN 2023Pages 394–406https://doi.org/10.1007/978-3-031-44204-9_33AbstractWe have studied the effectiveness of a biologically-inspired filter in improving the performance of the VGG-16 ConvNet when presented with images perturbed by noise and distortion. Our work builds on the findings of Evans et al. (2021), who ...
- ArticleJanuary 2024
Convolutional Neural Networks and Vision Transformers in Product GS1 GPC Brick Code Recognition
AbstractOnline stores and auctions are commonly used nowadays. It means that we buy much more on the Internet than in traditional stores. It leads to the case that during looking for the products we need to have precise categories assigned to each of them ...
- ArticleAugust 2023
Traffic Sign Recognition Based on Improved VGG-16 Model
Advanced Intelligent Computing Technology and ApplicationsPages 676–687https://doi.org/10.1007/978-981-99-4742-3_56AbstractTraffic sign recognition technology is very important in intelligent transportation systems. Aiming at the problem that the imbalance of existing traffic sign data sets affects the recognition accuracy. Firstly, this paper introduces the Weighted-...
- ArticleSeptember 2023
Improving Sustainability with Deep Learning Models for Inland Water Quality Monitoring Using Satellite Imagery
Mining Intelligence and Knowledge ExplorationPages 387–395https://doi.org/10.1007/978-3-031-44084-7_36AbstractInland water sources like lakes, rivers, and streams are important for the environment and human well-being. Monitoring these water sources is essential to ensure that they remain healthy and productive. This paper presents a study of deep ...
- research-articleJune 2023
Multiple forgery detection in digital video with VGG-16-based deep neural network and KPCA
Multimedia Tools and Applications (MTAA), Volume 83, Issue 2Pages 5415–5435https://doi.org/10.1007/s11042-023-15561-0AbstractThe amount of video data is growing exponentially on a daily basis. Easily available software or mobile applications offer simple tools to perform the forgery in the video. So, before sending these videos from one place to another, it is important ...
- research-articleMay 2023
Performance Evaluation of Learning Models for the Prognosis of COVID-19
New Generation Computing (NEWG), Volume 41, Issue 3Pages 533–551https://doi.org/10.1007/s00354-023-00220-7AbstractCOVID-19 has developed as a worldwide pandemic that needs ways to be detected. It is a communicable disease and is spreading widely. Deep learning and transfer learning methods have achieved promising results and performance for the detection of ...
- research-articleMay 2023
RETRACTED ARTICLE: Securing health care data through blockchain enabled collaborative machine learning
Soft Computing - A Fusion of Foundations, Methodologies and Applications (SOFC), Volume 27, Issue 14Pages 9941–9954https://doi.org/10.1007/s00500-023-08330-6AbstractTransferring of data in machine learning from one party to another party is one of the issues that has been in existence since the development of technology. Health care data collection using machine learning techniques can lead to privacy issues ...
- research-articleApril 2023
Deep Attention Network for Enhanced Hand Gesture Recognition System
AbstractSince technology is growing in all fields, researchers are developing more advanced technologies in human–computer communication and security systems. The flexible wrist hinge and crowded background make it difficult to distinguish hands in ...
- research-articleMarch 2023
Feasibility analysis of convolution neural network models for classification of concrete cracks in Smart City structures
Multimedia Tools and Applications (MTAA), Volume 82, Issue 25Pages 38249–38274https://doi.org/10.1007/s11042-023-15136-zAbstractCracks are one of the forms of damage to concrete structures that debase the strength and durability of the building material and may pose a danger to the living being associated with it. Proper and regular diagnosis of concrete cracks is ...
- research-articleMarch 2023
Automatic early detection of rice leaf diseases using hybrid deep learning and machine learning methods
Multimedia Tools and Applications (MTAA), Volume 82, Issue 23Pages 36091–36117https://doi.org/10.1007/s11042-023-14969-yAbstractPlant leaf disease detection is critical for long-term agricultural viability. Numerous Artificial Intelligence (AI) and Machine Learning (ML) technologies have been implemented for detecting rice diseases. However, such methods failed to identify ...
- research-articleMarch 2023
A constructive deep convolutional network model for analyzing video-to-image sequences
AbstractThis paper proposes a new technique to add sign language as a special and real-time feature. In addition to gestures, sign language also uses grammatical rules, linguistic frameworks, etc. We require a method that can extract ...
- research-articleMarch 2023
ResNext50 based convolution neural network-long short term memory model for plant disease classification
Multimedia Tools and Applications (MTAA), Volume 82, Issue 19Pages 29527–29545https://doi.org/10.1007/s11042-023-14851-xAbstractAgricultural problems need to be dealt with advanced computing methods to increase food productivity. Automatic classification of plant disease using deep learning methods helps to analyze the food quality and productivity. The existing methods ...
- research-articleFebruary 2023
A two-phase approach for expression invariant 3D face recognition using fine-tuned VGG-16 and 3D-SIFT descriptors
Multimedia Tools and Applications (MTAA), Volume 82, Issue 15Pages 23873–23890https://doi.org/10.1007/s11042-023-14407-zAbstractExpression invariant 3D face recognition systems have many computer vision applications such as human-computer interaction. Most 3D face recognition systems rely on rigid region features and a substantial amount of training data to achieve better ...