International Journal of Image Processing and Pattern Recognition
Volume 12, Issue 1 (2026)
Table of contents
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A Study on CNN-Based Image Mosaicing
Abstract: The intricate tapestry of image mosaicing, while a cornerstone of computer vision, has long been constrained by the rigidity of classical, geometry-driven pipelines. Hand-crafted feature detectors and homography estimators, while effective in controlled environments, prove brittle when confronted with the challenges of real-world scenes: significant parallax, dynamic moving objects, repetitive textures, and illumination variance. This work introduces a fundamental paradigm shift, proposing a deep convolutional neural network (CNN) architecture designed …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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Vani-Adapt: A Zero-Shot Accent Trans-Adaptation Framework for Robust Indic Speech Recognition
Abstract: In countries like India with multilingual and accent-rich dialects, speech-based human–computer interaction is important to expand digital services for better accessibility. Even with recent advancements in Automatic Speech Recognition (ASR), existing systems are still very reactive to regional accents and non-standard speech patterns which is not suitable for seamless experience. Traditional perspectives rely on accent-specific fine-tuning, which is unrealistic for real-world deployment and requires a lot of labeled data, which …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 17–22 Read article
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Enhancing Facial Expression Analysis Using CNNs: Insights from ML and Deep Learning Comparisons
Abstract: Emotion recognition from facial manifestations increases the interaction between humans and computers by enabling the interaction between humans and computers to effectively explain human feelings. This study presents a comparative analysis of three approaches to the emotional recognition of faces: a custom Convolutional Neural Network (CNN) model, Traditional Machine Learning (ML) methods, and other deep learning architectures such as VGG, ResNet, and Hybrid CNN–RNN models. The proposed CNN-based system, developed …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 23–31 Read article
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A Comprehensive Review of Convolutional Neural Network Architectures and Evolution
Abstract: Convolutional Neural Networks (CNNs) have become a foundational deep learning framework in computer vision because they can automatically extract layered, increasingly complex features directly from raw image data. CNNs use convolutional, pooling, and activation layers to extract spatial patterns from basic edges to intricate object components, drawing inspiration from the human visual cortex. An overview of CNNs’ basic architecture is given in this study, along with an explanation of important …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 32–40 Read article
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Advanced Classification of Diabetic Retinopathy Using GAN and Deep Residual CNN Model
Abstract: Diabetic retinopathy (DR) is a leading cause of blindness worldwide, impacting the largest number of individuals who have diabetes. Early identification of diabetic retinopathy may help to prevent severe effects; however, the very limited availability of labeled datasets, and the possibility of overfitting of the model, presents obstacles to obtaining an accurate diagnosis. In this research, a hybrid deep learning strategy is introduced, where Generative Adversarial Networks (GANs) are used …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 8–16 Read article