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Found 7 papers, 1 papers with code
A Systematic Review of Low-Rank and Local Low-Rank Matrix Approximation in Big Data Medical Imaging
We note a significant shift towards a preference for LLRMA in the medical imaging field since 2015, demonstrating its potential and effectiveness in capturing complex structures in medical data compared to LRMA.
Anomaly Detection in Power Generation Plants with Generative Adversarial Networks
A GANs model was trained and fine-tuned both with and without data augmentation, with the goal of increasing the dataset size to enhance performance.
Label Assisted Autoencoder for Anomaly Detection in Power Generation Plants
In addition, the proposed model is able to classify the anomalies according to their degree of severity.
Creating awareness about security and safety on highways to mitigate wildlife-vehicle collisions by detecting and recognizing wildlife fences using deep learning and drone technology
Additionally, we used aerial and still annotated images extracted from the drone and still cameras for the segmentation and detection tasks.
Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images
Deep learning shows promise for medical image analysis but lacks interpretability, hindering adoption in healthcare.
Predicting Fuel Consumption in Power Generation Plants using Machine Learning and Neural Networks
The instability of power generation from national grids has led industries (e. g., telecommunication) to rely on plant generators to run their businesses.
Automatic Speech Recognition And Limited Vocabulary: A Survey
This work consequently provides a way forward when designing an ASR system using limited vocabulary.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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