Advances in Deep Learning for Pattern Recognition
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".
Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 398
Special Issue Editors
Interests: machine learning; deep learning; models interpretability; computer vision; pattern recognition; text mining; neural networks; handwriting recognition; image processing
Interests: image processing; neural networks; pattern recognition; machine learning; computational intelligence; classification pattern
Interests: artificial intelligence; pattern recognition; signal processing; biometrics; automatic signature verification
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Special Issue Information
Dear Colleagues,
The last decade has witnessed an unparalleled transformation in pattern recognition, primarily driven by the emergence of Convolutional Neural Networks (CNNs). These neural structures have redefined benchmarks, rendering many traditional techniques obsolete and paving the way for remarkable applications previously unattainable in the pre-deep learning era.
With the ongoing evolution of deep learning methodologies, the introduction of transformer architectures has signaled a significant shift. Initially making waves in natural language processing tasks, they quickly demonstrated their prowess in visual domains, often matching or even surpassing the achievements of their CNN counterparts.
Subsequently, Large Language Models (LLMs), a subset of transformers, have further pushed the boundaries. Their unparalleled ability to understand, generate, and interact with text heralds a promising future for pattern recognition, seamlessly blending textual and visual cues like never before.
This Special Edition aims to delve into the evolving narrative of deep learning architectures and their profound influence on pattern recognition. We welcome contributions that address this journey from theory to practice, with high-quality, original research papers that highlight the transformative impact of deep learning on pattern recognition.
Dr. Cleber Zanchettin
Dr. Byron Leite Dantas Bezerra
Dr. Donato Impedovo
Dr. Vincenzo Dentamaro
Guest Editors
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Keywords
- pattern recognition
- convolutional neural network
- deep learning
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