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Showing 6 of 6 academic articles

A comprehensive analytical assessment of dino-based architectures for sustainable automated potato inspection in the Al Kharj Region

Zahraa Tarek, Esraa Hasan • Journal of the Saudi Society of Agricultural Sciences (2026)

Abstract Self-supervised learning (SSL) has emerged as a pivotal paradigm in computer vision, particularly for applications where labeled data are limited, costly, or labor-intensive to obtain. This paradigm is especially relevant to sustai...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44447-026-00151-x

Attention mechanisms in computer vision: A survey

Meng-Hao Guo, Tian-Xing Xu, Jiangjiang Liu, Zheng-Ning Liu et al. • Computational Visual Media (2022)

Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s41095-022-0271-y

Text Data Augmentation for Deep Learning

Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht • Journal Of Big Data (2021)

Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augme...

OPENALEX cc-by DOI: https://doi.org/10.1186/s40537-021-00492-0 PMC: 8287113

Raman Spectroscopy Pre-Trained Encoder: A Self-Supervised Learning Approach for Data-Efficient Domain-Independent Spectroscopy Analysis

Abhiraam Eranti, Yogesh Tewari, Rafael Palacios, Amar Gupta • IEEE Access (2026)

Deep-learning methods have boosted the analytical power of Raman spectroscopy, yet they still require large, task-specific, labeled datasets and often fail to transfer across application domains. The study explores pre-trained encoders as a...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2026.3672109