A holistic review of machine learning adversarial attacks in IoT networks
With the rapid advancements and notable achievements across various application
domains, Machine Learning (ML) has become a vital element within the Internet of Things …
domains, Machine Learning (ML) has become a vital element within the Internet of Things …
Machine Learning: Models, Challenges, and Research Directions
T Talaei Khoei, N Kaabouch - Future Internet, 2023 - mdpi.com
Machine learning techniques have emerged as a transformative force, revolutionizing
various application domains, particularly cybersecurity. The development of optimal …
various application domains, particularly cybersecurity. The development of optimal …
Exploring the role of Convolutional Neural Networks (CNN) in dental radiography segmentation: A comprehensive Systematic Literature Review
In dentistry, there is a growing need for accurate diagnostic tools, particularly advanced
imaging techniques such as Computed Tomography (CT), Cone Beam Computed …
imaging techniques such as Computed Tomography (CT), Cone Beam Computed …
Crop monitoring using remote sensing land use and land change data: Comparative analysis of deep learning methods using pre-trained CNN models
In the context of the rapidly evolving climate dynamics of the early twenty-first century, the
interplay between climate change and biospheric integrity is becoming increasingly critical …
interplay between climate change and biospheric integrity is becoming increasingly critical …
Deep Learning in Fringe Projection: a Review
H Liu, N Yan, B Shao, S Yuan, X Zhang - Neurocomputing, 2024 - Elsevier
Fringe projection is widely recognized as a prominent technique for 3D measurement, owing
to its non-contact nature, high precision, and exceptional spatial resolution. However, it …
to its non-contact nature, high precision, and exceptional spatial resolution. However, it …
Kidney Tumor Classification on CT images using Self-supervised Learning
E Özbay, FA Özbay, FS Gharehchopogh - Computers in Biology and …, 2024 - Elsevier
One of the most common diseases affecting society around the world is kidney tumor. The
risk of kidney disease increases due to reasons such as consumption of ready-made food …
risk of kidney disease increases due to reasons such as consumption of ready-made food …
Defense against adversarial attacks: robust and efficient compressed optimized neural networks
In the ongoing battle against adversarial attacks, adopting a suitable strategy to enhance
model efficiency, bolster resistance to adversarial threats, and ensure practical deployment …
model efficiency, bolster resistance to adversarial threats, and ensure practical deployment …
A Novel Artificial-Intelligence-Based Approach for Automatic Assessment of Retinal Disease Images using Multi-view Deep-Broad Learning Network
A Zhang, X Qian, C Xu, J Zhang - IEEE Access, 2024 - ieeexplore.ieee.org
Retinal disease detection and diagnosis relying solely on artificial retinal diseases will put
great pressure on doctors and increase the rate of misdiagnosis. Therefore, the …
great pressure on doctors and increase the rate of misdiagnosis. Therefore, the …
Ensemble Transfer Learning using MaizeSet: A Dataset for Weed and Maize Crop Recognition at Different Growth Stages
Maize holds significant importance as a staple food source globally. Increasing maize yield
requires the effective removal of weeds from maize fields, as they pose a detrimental threat …
requires the effective removal of weeds from maize fields, as they pose a detrimental threat …
[HTML][HTML] A framework for detecting zero-day exploits in network flows
Zero-day attack detection solutions aim to proactively identify unknown threats targeting
valuable assets within a given system. While many Intrusion Detection System (IDS) …
valuable assets within a given system. While many Intrusion Detection System (IDS) …