Systematic Literature Review of Machine Learning Models and Applications for Text Recognition

arXiv:2608.26500 · cs.CV, cs.LG · Submitted 2026-08-27 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-08-27

Updated: 2026-08-27

Terminology

• Accuracy — 60× in this paper · explained in 1 episode
• Transformer — 52× in this paper · explained in 2 episodes
• Generalization — 15× in this paper · explained in 13 episodes
• Data Augmentation — 10× in this paper · explained in 7 episodes
• Feature Extraction — 10× in this paper · explained in 2 episodes
• Hybrid Models — 10× in this paper · explained in 2 episodes
• Electrical Engineering — 9× in this paper
• Universiti Teknologi Malaysia — 9× in this paper
• Attention Mechanism — 7× in this paper · explained in 3 episodes
• Adaptability — 6× in this paper · explained in 1 episode
• Resource Constraints — 5× in this paper · explained in 3 episodes
• Contextual Understanding — 4× in this paper · explained in 2 episodes
• Core — 4× in this paper · explained in 2 episodes
• Self-Supervised Learning — 4× in this paper · explained in 8 episodes
• Verification — 4× in this paper · explained in 2 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Feature Engineering — 3× in this paper · explained in 3 episodes
• Adversarial Training — 2× in this paper · explained in 1 episode
• American International University-Bangladesh — 2× in this paper
• Artificial Intelligence (AI) — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Few-Shot Learning — 2× in this paper · explained in 4 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• International Journal on Document Analysis and Recognition — 2× in this paper
• Knowledge Distillation — 2× in this paper · explained in 11 episodes
• Low-Resource Languages — 2× in this paper · explained in 4 episodes
• Pruning — 2× in this paper · explained in 4 episodes
• Quantization — 2× in this paper · explained in 12 episodes
• Selection Bias — 2× in this paper · explained in 4 episodes
• Semantic Understanding — 2× in this paper · explained in 2 episodes
• Transferability — 2× in this paper · explained in 4 episodes
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• Transformer Models — 2× in this paper · explained in 2 episodes
• VLSI and Embedded Computing Architecture Design — 2× in this paper
• Vision Transformer (ViT) — 2× in this paper · explained in 2 episodes
• ABSTRACT Optical Character Recognition — 1× in this paper
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptive Layout — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Continual Learning — 1× in this paper · explained in 2 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Cross-lingual Transfer — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Federated Learning — 1× in this paper · explained in 14 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hybrid System — 1× in this paper · explained in 2 episodes
• International Conference on Computer and Knowledge Engineering — 1× in this paper
• International Conference on Information and Communication Technology — 1× in this paper
• International Conference on Intelligent Systems — 1× in this paper
• Meta-learning — 1× in this paper · explained in 2 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Multimodal Learning — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Wavelet Transform — 1× in this paper · explained in 2 episodes

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