If you are reading this on GitHub, the demo looks like this. Please follow the link below to view the live demo on my blog. Convolutional Neural Networks (CNN), a technique within the broader Deep ...

Abstract: Wheat diseases present serious threats to global agricultural productivity resulting in yield loss and economic stagnation. For efficient management, a rapid diagnosis is crucial; however, ...

This repo contains all my Deep Learning semester work, including implementations of FNNs, CNNs, autoencoders, CBOW, and transfer learning. I explored TensorFlow, Keras, PyTorch, and Theano while ...

Abstract: This paper introduces OVANet, a new deep learning framework for the diagnosis and classification of ovarian cancer subtypes from histopathological images. OVANet has been designed by ...

Acute lymphoblastic leukemia (ALL) poses a significant health challenge, particularly in pediatric cases, requiring precise and rapid diagnostic approaches. This comprehensive review explores the ...

1 Department of Information and Communication Technology, Comilla University, Cumilla, Bangladesh. 2 Department of Computer Science and Engineering, Bangladesh Army International University of Science ...

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...

In this era of pandemic, the future of healthcare industry has never been more exciting. Artificial intelligence and machine learning (AI & ML) present opportunities to develop solutions that cater ...

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at ...

Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored ...