Techniques and challenges of image segmentation: A review
Y Yu, C Wang, Q Fu, R Kou, F Huang, B Yang, T Yang… - Electronics, 2023 - mdpi.com
Image segmentation, which has become a research hotspot in the field of image processing
and computer vision, refers to the process of dividing an image into meaningful and non …
and computer vision, refers to the process of dividing an image into meaningful and non …
Demystifying the role of natural language processing (NLP) in smart city applications: background, motivation, recent advances, and future research directions
Smart cities provide an efficient infrastructure for the enhancement of the quality of life of the
people by aiding in fast urbanization and resource management through sustainable and …
people by aiding in fast urbanization and resource management through sustainable and …
Convolutional neural networks: A survey
M Krichen - Computers, 2023 - mdpi.com
Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …
Spectrum interference-based two-level data augmentation method in deep learning for automatic modulation classification
Q Zheng, P Zhao, Y Li, H Wang, Y Yang - Neural Computing and …, 2021 - Springer
Automatic modulation classification is an essential and challenging topic in the development
of cognitive radios, and it is the cornerstone of adaptive modulation and demodulation …
of cognitive radios, and it is the cornerstone of adaptive modulation and demodulation …
Insulator-defect detection algorithm based on improved YOLOv7
J Zheng, H Wu, H Zhang, Z Wang, W Xu - Sensors, 2022 - mdpi.com
Existing detection methods face a huge challenge in identifying insulators with minor defects
when targeting transmission line images with complex backgrounds. To ensure the safe …
when targeting transmission line images with complex backgrounds. To ensure the safe …
A full stage data augmentation method in deep convolutional neural network for natural image classification
Q Zheng, M Yang, X Tian, N Jiang… - Discrete Dynamics in …, 2020 - Wiley Online Library
Nowadays, deep learning has achieved remarkable results in many computer vision related
tasks, among which the support of big data is essential. In this paper, we propose a full stage …
tasks, among which the support of big data is essential. In this paper, we propose a full stage …
[HTML][HTML] Deep learning framework for rapid and accurate respiratory COVID-19 prediction using chest X-ray images
COVID-19 is a contagious disease that affects the human respiratory system. Infected
individuals may develop serious illnesses, and complications may result in death. Using …
individuals may develop serious illnesses, and complications may result in death. Using …
Class-aware fish species recognition using deep learning for an imbalanced dataset
Fish species recognition is crucial to identifying the abundance of fish species in a specific
area, controlling production management, and monitoring the ecosystem, especially …
area, controlling production management, and monitoring the ecosystem, especially …
X-ray image based COVID-19 detection using evolutionary deep learning approach
Radiological methodologies, such as chest x-rays and CT, are widely employed to help
diagnose and monitor COVID-19 disease. COVID-19 displays certain radiological patterns …
diagnose and monitor COVID-19 disease. COVID-19 displays certain radiological patterns …
[HTML][HTML] Tomato leaf disease identification via two–stage transfer learning approach
In the last ten years, there has been an upsurge in focus on sustainable agribusiness as a
response to the bio-hazards posed by the effects of climate change, severe weather events …
response to the bio-hazards posed by the effects of climate change, severe weather events …