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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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portfolio
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publications
Face Detection in Camera Captured Images of Identity Documents Under Challenging Conditions
Published in International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019
Face detection for identity documents under challenging capture conditions.
Recommended citation: S. Bakkali, Z. Ming, M. M. Luqman, J-C. Burie. "Face Detection in Camera Captured Images of Identity Documents Under Challenging Conditions." ICDARW 2019, Vol. 4, pp. 55-60. https://arxiv.org/pdf/1911.03567
Visual and Textual Deep Feature Fusion for Document Image Classification
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020
Fusion of visual and textual deep features for document image classification.
Recommended citation: M. Farhan, N. I. Kajla, M. D. A. Awan, M. M. Luqman, M. Coustaty, S. Bakkali. "Visual and Textual Deep Feature Fusion for Document Image Classification." CVPRW 2020, pp. 562-563. https://openaccess.thecvf.com/content_CVPRW_2020/papers/w34/Bakkali_Visual_and_Textual_Deep_Feature_Fusion_for_Document_Image_Classification_CVPRW_2020_paper.pdf
Cross-modal Deep Networks for Document Image Classification
Published in IEEE International Conference on Image Processing (ICIP), 2020
Cross-modal deep networks for document image classification.
Recommended citation: S. Bakkali, Z. Ming, M. Coustaty, M. Rusinol. "Cross-modal Deep Networks for Document Image Classification." ICIP 2020, pp. 2556-2560. https://marcalr.github.io/pdfs/ICIP20.pdf
EAML: Ensemble Self-Attention-Based Mutual Learning Network for Document Image Classification
Published in International Journal on Document Analysis and Recognition (IJDAR), 2021
A mutual learning framework with ensemble self-attention for document image classification.
Recommended citation: S. Bakkali, Z. Ming, M. Coustaty, M. Rusinol. "EAML: Ensemble Self-Attention-Based Mutual Learning Network for Document Image Classification." IJDAR 24(3):251-268, 2021. https://arxiv.org/pdf/2305.06923
Multimodal Document Understanding with Unified Vision and Language Cross-Modal Learning
Published in PhD Thesis, Universite de La Rochelle, 2022
PhD thesis on unified vision-language learning for multimodal document understanding.
Recommended citation: S. Bakkali. "Multimodal Document Understanding with Unified Vision and Language Cross-Modal Learning." PhD Thesis, Universite de La Rochelle, 2022. https://theses.hal.science/tel-04197696/
VLCDoC: Vision-Language Contrastive Pre-training Model for Cross-Modal Document Classification
Published in Pattern Recognition, 2023
Vision-language contrastive pre-training for robust cross-modal document classification.
Recommended citation: S. Bakkali, Z. Ming, M. Coustaty, M. Rusinol, O. Ramos Terrades. "VLCDoC: Vision-Language Contrastive Pre-training Model for Cross-Modal Document Classification." Pattern Recognition 139:109419, 2023. https://arxiv.org/pdf/2205.12029
State-of-the-Art Khmer Text Recognition Using Deep Learning Models
Published in ASEAN Conference on Emerging Technologies, 2024
A survey of Khmer text recognition methods using deep learning.
Recommended citation: S. Keo, M. Coustaty, S. Bakkali, et al. "State-of-the-Art Khmer Text Recognition Using Deep Learning Models." ASEAN Conference on Emerging Technologies, 2024. https://hal.science/hal-05157225v1/file/ACET2024.pdf
LLMChain: Blockchain-based Reputation System for Sharing and Evaluating Large Language Models
Published in IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC), 2024
A blockchain-based reputation mechanism for sharing and evaluating large language models.
Recommended citation: M. A. Bouchiha, Q. Telnoff, S. Bakkali, R. Champagnat, M. Rabah, M. Coustaty, Y. Ghamri-Doudane. "LLMChain: Blockchain-based Reputation System for Sharing and Evaluating Large Language Models." COMPSAC 2024, pp. 439-448. https://arxiv.org/pdf/2404.13236
Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting
Published in International Conference on Document Analysis and Recognition (ICDAR), 2024
Anytime early-exit strategies for efficient multimodal document classification.
Recommended citation: O. Hamed, S. Bakkali, M. Blaschko, S. Moens, J. Van Landeghem. "Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting." ICDAR 2024, pp. 270-286. https://arxiv.org/pdf/2405.12705
KhmerST: A Low-Resource Khmer Scene Text Detection and Recognition Benchmark
Published in Asian Conference on Computer Vision (ACCV), 2024
A benchmark for Khmer scene-text detection and recognition.
Recommended citation: V. Nom, S. Bakkali, M. M. Luqman, M. Coustaty, J-M. Ogier. "KhmerST: A Low-Resource Khmer Scene Text Detection and Recognition Benchmark." ACCV 2024, pp. 1777-1792. https://openaccess.thecvf.com/content/ACCV2024/papers/Nom_KhmerST_A_Low-Resource_Khmer_Scene_Text_Detection_and_Recognition_Benchmark_ACCV_2024_paper.pdf
GlobalDoc: A Cross-Modal Vision-Language Framework for Real-World Document Image Retrieval and Classification
Published in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025
A cross-modal framework for robust document image retrieval in real-world settings.
Recommended citation: S. Bakkali, S. Biswas, Z. Ming, M. Coustaty, M. Rusinol, O. Ramos Terrades, J. Llados. "GlobalDoc: A Cross-Modal Vision-Language Framework for Real-World Document Image Retrieval and Classification." WACV 2025, pp. 1436-1446. https://openaccess.thecvf.com/content/WACV2025/papers/Bakkali_GlobalDoc_A_Cross-Modal_Vision-Language_Framework_for_Real-World_Document_Image_Retrieval_WACV_2025_paper.pdf
DocSum: Domain-Adaptive Pre-training for Document Abstractive Summarization
Published in Winter Conference on Applications of Computer Vision (WACV), 2025
Domain-adaptive pre-training for document-level abstractive summarization.
Recommended citation: P. P. M. Chau, S. Bakkali, A. Doucet. "DocSum: Domain-Adaptive Pre-training for Document Abstractive Summarization." WACV 2025, pp. 1303-1312. https://openaccess.thecvf.com/content/WACV2025W/VISIONDOCS/papers/Chau_DocSum_Domain-Adaptive_Pre-training_for_Document_Abstractive_Summarization_WACVW_2025_paper.pdf
IDTrust: Deep Identity Document Quality Detection with Bandpass Filtering
Published in Winter Conference on Applications of Computer Vision (WACV) Workshops, 2025
Quality assessment for identity documents using bandpass filtering.
Recommended citation: M. Al-Ghadi, J. Voerman, S. Bakkali, M. Coustaty, O. Lessard, N. Sidere. "IDTrust: Deep Identity Document Quality Detection with Bandpass Filtering." WACV Workshops 2025, pp. 716-723. https://openaccess.thecvf.com/content/WACV2025W/AI4MFDD/papers/Al-Ghadi_IDTrust_Deep_Identity_Document_Quality_Detection_with_Bandpass_Filtering_WACVW_2025_paper.pdf
Fusion of GNN and GBDT Models for Graph and Node Classification
Published in International Workshop on Graph-Based Representations in Pattern Recognition (GbRPR), 2025
Hybrid graph learning by combining GNNs with gradient-boosted decision trees.
Recommended citation: M. Farhan, N. I. Kajla, M. D. A. Awan, M. M. Luqman, M. Coustaty, S. Bakkali. "Fusion of GNN and GBDT Models for Graph and Node Classification." GbRPR 2025, pp. 167-178. https://hal.science/hal-05111226v1/file/Fusion%20of%20GNN%20and%20GBDT%20Models%20%28Published%20Work%29.pdf
Evaluating the Impact of Khmer Font Types on Text Recognition
Published in arXiv preprint, 2025
An empirical analysis of Khmer font characteristics for text recognition.
Recommended citation: V. Nom, S. Bakkali, M. M. Luqman, et al. "Evaluating the Impact of Khmer Font Types on Text Recognition." arXiv:2506.23963, 2025. https://arxiv.org/pdf/2506.23963
Confidence-based Knowledge Distillation to Reduce Training Costs and Carbon Footprint for Low-Resource Neural Machine Translation
Published in Applied Sciences, 2025
This paper proposes confidence-based distillation strategies for low-resource neural machine translation.
Recommended citation: M. Zafar, P. J. Wall, S. Bakkali, et al. "Confidence-based Knowledge Distillation to Reduce Training Costs and Carbon Footprint for Low-Resource Neural Machine Translation." Applied Sciences 15(14):8091, 2025. https://www.mdpi.com/2076-3417/15/14/8091
WildKhmerST: A Comprehensive Benchmark Dataset for Khmer Scene Text Detection and Recognition
Published in International Conference on Document Analysis and Recognition (ICDAR), 2025
A large-scale benchmark for Khmer scene-text detection and recognition.
Recommended citation: S. Keo, V. Nom, S. Bakkali, M. M. Luqman, M. Rusinol, M. Coustaty, J-M. Ogier. "WildKhmerST: A Comprehensive Benchmark Dataset for Khmer Scene Text Detection and Recognition." ICDAR 2025, pp. 351-368. https://hal.science/hal-05120511/document
Visual Text Generation in Khmer Language: Challenges and Trends with Diffusion Models
Published in International Conference on Document Analysis and Recognition (ICDAR), 2025
A survey of diffusion-based approaches for Khmer text generation.
Recommended citation: S. Keo, V. Nom, S. Bakkali, M. M. Luqman, M. Coustaty, J-M. Ogier. "Visual Text Generation in Khmer Language: Challenges and Trends with Diffusion Models." ICDAR 2025, pp. 134-152. https://hal.science/hal-05178406/document
Cross-Lingual Learning for Low-Resource Khmer Scene Text Detection and Recognition
Published in International Conference on Document Analysis and Recognition (ICDAR), 2025
Cross-lingual learning strategies for Khmer scene-text recognition.
Recommended citation: V. Nom, S. Keo, S. Bakkali, et al. "Cross-Lingual Learning for Low-Resource Khmer Scene Text Detection and Recognition." ICDAR 2025, pp. 347-365. https://hal.science/hal-05191219/document
Hybrid Retrieval-Augmented Generation for Robust Multilingual Document Question Answering
Published in arXiv preprint, 2025
Hybrid RAG strategies for multilingual document question answering.
Recommended citation: A. Mudet, S. Bakkali. "Hybrid Retrieval-Augmented Generation for Robust Multilingual Document Question Answering." arXiv:2512.12694, 2025. https://arxiv.org/pdf/2512.12694
Scientific Research (Legacy)
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