Academic Editor
Author
Contributions by role
Author 2
Editor 1
Rabbia Mahum
University of Engineering and Technology, Taxila, Pakistan
Summary
Edited Journals
IECE Contributions

Open Access | Research Article | 23 May 2025
IRV2-hardswish Framework: A Deep Learning Approach for Deepfakes Detection and Classification
IECE Journal of Image Analysis and Processing | Volume 1, Issue 2: 45-56, 2025 | DOI: 10.62762/JIAP.2025.421251
Abstract
Deep learning models are pivotal in the advancements of Artificial Intelligence (AI) due to rapid learning and decision-making across various fields such as healthcare, finance, and technology. However, a harmful utilization of deep learning models poses a threat to public welfare, national security, and confidentiality. One such example is Deepfakes, which creates and modifies audiovisual data that humans cannot tell apart from the real ones. Due to the progression of deep learning models that produce manipulated data, accurately detecting and classifying deepfake data becomes a challenge. This paper presents a groundbreaking IRV2-Hardswish Framework for deepfake detection, leveraging a hyb... More >

Graphical Abstract
IRV2-hardswish Framework: A Deep Learning Approach for Deepfakes Detection and Classification

Open Access | Research Article | 20 March 2025
Plant Disease Detection Using Deep Learning Techniques
IECE Journal of Image Analysis and Processing | Volume 1, Issue 1: 36-44, 2025 | DOI: 10.62762/JIAP.2025.227089
Abstract
Plant diseases create one of the most serious risks to the world's food supply, reducing agricultural production and endangering millions of people's lives. These illnesses can destroy crops, disrupt food supply networks, and increase the danger of food deficiency, emphasizing the importance of establishing strong methods to protect the world's food sources. The approaches of deep learning have transformed the field of plant disease diagnosis, providing sophisticated and perfect solutions for early detection and management. However, a prevalent concern with deep learning models is their susceptibility to a lack of generalization and robustness when faced with novel crop and disease categorie... More >

Graphical Abstract
Plant Disease Detection Using Deep Learning Techniques

Open Access | Research Article | 14 March 2025
High-Quality Multi-Focus Image Fusion: A Comparative Analysis of DCT-Based Approaches with Their Variants
IECE Journal of Image Analysis and Processing | Volume 1, Issue 1: 27-35, 2025 | DOI: 10.62762/JIAP.2024.764051
Abstract
Image fusion, especially in the context of multi-focus image fusion, plays a crucial role in digital image processing by enhancing the clarity and detail of visual content through the combination of multiple source images. Traditional spatial domain methods often suffer from issues like spectral distortion and low contrast, which has led researchers to explore techniques in the frequency domain, such as the Discrete Cosine Transform (DCT). DCT-based methods are particularly valued for their computational efficiency, making them a strong alternative, especially in applications like image compression and fusion. This study focuses on DCT-based approaches, including variants that incorporate Si... More >

Graphical Abstract
High-Quality Multi-Focus Image Fusion: A Comparative Analysis of DCT-Based Approaches with Their Variants