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Showing 20 of 785 academic articles
Hang Li • National Science Review
(2017)
Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...
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DOI: https://doi.org/10.1093/nsr/nwx110
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen et al. • arXiv (Cornell University)
(2011)
We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1103.0398
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond et al. • arXiv (Cornell University)
(2019)
Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building higher-capacity models and pretraining has made it possible to ...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1910.03771
Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, Thomas Wolf (2019)
The classic supervised machine learning paradigm is based on learning in isolation, a single predictive model for a task using a single dataset. This approach requires a large number of training examples and performs best for well-defined a...
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DOI: https://doi.org/10.18653/v1/n19-5004
Milagros Miceli, Tianling Yang, Laurens Naudts, Martin Schuessler et al. • ACM Conference on Fairness, Accountability, and Transparency (FAccT)
(2021)
In industrial computer vision, discretionary decisions surrounding the production of image training data remain widely undocumented. Recent research taking issue with such opacity has proposed standardized processes for dataset documentatio...
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DOI: https://doi.org/10.1145/3442188.3445880
Grzegorz Mrugacz, Aleksandra Mospinek, Małgorzata Jagielska, Dariusz Miszczak et al. • Biology
(2025)
Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...
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Open Access (DOAJ)
DOI: 10.3390/biology15010042
Abdullah Ayub Khan, Asif Ali Laghari, Shafique Ahmad Awan • ICST Transactions on Scalable Information Systems
(2018)
INTRODUCTION: Due to the advancement in the field of Artificial Intelligence (AI), the ability to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is becoming a hot topic due to the direct training of machines...
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DOI: https://doi.org/10.4108/eai.21-4-2021.169418
Xinkai Xu, Hailan Zhang, Yan Ma, Kang Liu et al. • Remote Sensing
(2023)
Small-object detection is a challenging task in computer vision due to the limited training samples and low-quality images. Transfer learning, which transfers the knowledge learned from a large dataset to a small dataset, is a popular metho...
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Open Access (DOAJ)
DOI: 10.3390/rs15143525
Irina V. Arinicheva, Igor V. Arinichev, Galina V. Volkova, Sergey V. Polyanskikh • Siberian Journal of Life Sciences and Agriculture
(2022)
Purpose. To investigate the possibility of diagnosing yellow and brown rust (Puccinia striiformis f. sp. tritici West. Puccinia triticina f. sp. tritici Erikss), yellow spot (Pyrenophora tritici-repentis (Died.) Drechsler) on wheat leaves f...
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Open Access (DOAJ)
DOI: 10.12731/2658-6649-2022-14-1-248-261
Wei Huang, Xingyu Zheng, Xudong Ma, Haotong Qin et al. • Visual Intelligence
(2024)
Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language...
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Open Access (DOAJ)
DOI: 10.1007/s44267-024-00070-x
Muhammad Faseeh, Misbah Bibi, Murad Ali Khan, Atif Rizwan et al. • IEEE Access
(2024)
Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles. Recent advancements have significantly improved both supervised and self-supervised methods for ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3485089
Direselign Addis Tadesse, Chuan-Ming Liu, Van-Dai Ta • Applied Sciences
(2020)
Reading text and unified text detection and recognition from natural images are the most challenging applications in computer vision and document analysis. Previously proposed end-to-end scene text reading methods do not consider the freque...
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Open Access (DOAJ)
DOI: 10.3390/app10134474
Yuan Zi, Chenyu Zhou, Jiefu Chen, Zhu Han et al. • IEEE Access
(2025)
Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earthȁ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3597991
Rittik Chandra Das Turjy, Fahmid Al Farid, Fahmid Al Farid, Md. Hasan Imam Bijoy et al. • Frontiers in Artificial Intelligence
(2026)
Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...
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Open Access (DOAJ)
DOI: 10.3389/frai.2026.1884567
Wenlin Yan, Xianxin Jiang, Ping Liu • IEEE Access
(2023)
Artificial Intelligence (AI) has promising applications in basketball shooting analysis, as it can help basketball athletes improve their shooting techniques and accuracy, thereby enhancing the effectiveness of both games and training sessi...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3304631
Muhammad Salihin Saealal, Mohd Zamri Ibrahim, David. J. Mulvaney, Mohd Ibrahim Shapiai et al. • PLoS ONE
(2022)
Deep learning is notably successful in data analysis, computer vision, and human control. Nevertheless, this approach has inevitably allowed the development of DeepFake video sequences and images that could be altered so that the changes ar...
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Open Access (DOAJ)
Noor Fatima, Hasan Faraz Khan, Muzammil Behzad • IEEE Access
(2026)
The rapid proliferation of AI-generated and manipulated visual content requires forensic detectors that remain reliable after routine processing and deliberate counter-forensic modification. This paper presents an attack-aware deepfake dete...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2026.3734573
Hossein Kabir, Jordan Wu, Sunav Dahal, Tony Joo et al. • Nature Communications
(2024)
Monitoring water uptake in cementitious systems is crucial to assess their durability against corrosion, salt attack, and freeze-thaw damage. However, gauging absorption currently relies on labor-intensive and infrequent weight measurements...
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DOI: https://doi.org/10.1038/s41467-024-53993-w
PMC: 11568162
Sheemona Joseph C., S. Ganesh, S. Kannadhasan, K. Selvipriya • Journal of Informatics and Web Engineering
(2025)
Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial ta...
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Open Access (DOAJ)
DOI: 10.33093/jiwe.2025.4.2.14
Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access
(2019)
Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2932037