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About Us

About Us

About Us

We are a small research team working together on academic and research-based projects. Our work focuses on learning, collaboration, and applying knowledge to real-world problems.

Akrash Noor

I am a student and researcher with an interest in artificial intelligence, machine learning, and software development. I work on project development, research implementation, and documentation.

Hifzun Nisa

Hifzun Nisa is my research partner. She supports the research process by helping with data analysis, documentation, experimentation, and result evaluation.

Saba Latif

Saba Latif is our teacher and research supervisor. She guides us throughout the research process, provides valuable feedback, and ensures academic quality and correctness.

Together, we aim to learn, explore, and contribute to meaningful research work.

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A Comparative Study of Deep Learning Architectures for Chest X-Ray Image Classification

Comparative Analysis of Deep Learning Models for Chest X-Ray Image Classification Author: Akrash Noor, Saba Latif & Hifzun Nisa | Published: December 21, 2025 | Category: AI · Medical Imaging · Deep Learning Introduction Medical imaging has become an important aspect in the contemporary healthcare and especially the diagnosis of thoracic diseases utilizing the images of chest X-ray. In recent years, artificial intelligence has advanced significantly, and convolutional neural networks that are based on deep learning have demonstrated impressive results in the domain of automated disease detection and classification. This paper compares and contrasts several deep learning models that are trained on chest X-ray data with PyTorch and TensorFlow in their accuracy, generalization, and computational efficiency. Deep Learning Models Used Custom Convolutional Neural Networks (CNN) ResNet (Residual Networks) DenseNet VGG-styl...

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Disk Scheduling Algorithms in Operating Systems

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