Browsing by Subject "deep learning"
Now showing items 1-9 of 9
-
Automated Labour Detection Framework to Monitor Pregnant Women with a High Risk of Premature Labour
(2022-02-22)It is estimated that more than 1 in 10 babies are born prematurely worldwide. Babies that survive premature birth are more likely to face lifelong health-related disabilities. By monitoring uterine contractions, labour can ... -
Comprehending Software Bugs Leveraging Code Structures with Neural Language Models
(2023-08-28)Software bugs claim ~50% of development time and cost the global economy billions of dollars every year. Unfortunately, despite the use of many software quality assurance (SQA) practices in software development (e.g., ... -
A deep learning computer vision system for image based cytometry
(2017-02-02)A Complete Blood Count (CBC) is one of the most commonly deployed tests for checking the overall medical condition of a human body. It results in a summary of blood cell related measures allowing for a quick preliminary ... -
Deep Learning-Based Stacking Neural Network and Generative Adversarial Networks for Human Activity Recognition Based on Ambient Sensors
(2021-01-28)Smart home for healthcare services has acquired more attention since the increasing development of the Internet of Things and the population ageing over the world. Human activity recognition (HAR) is one of the concerns ... -
Evolving Hierarchical Structures for Convolutional Neural Networks using Jagged Arrays
(2018-04-04)Traditionally, deep learning practitioners have relied on heuristics and past high-performing networks to hand-craft their neural network architectures because architecture search algorithms were too computationally ... -
Interpreting Deep Learning Models
(2020-06-24)Model interpretability is a requirement in many applications in which crucial decisions are made by users relying on a model's outputs. The recent movement for “algorithmic fairness” also stipulates explainability, and ... -
Learning Adaptive Deep Representations for Few-to-Medium Shot Image Classification
(2021-02-22)In real-world applications, the environment in which a machine learning system is deployed tends to change due to many factors, such as sample selection bias, prior probability mismatch, and domain shift. This makes it ... -
MARINE SEARCH AND RESCUE USING LIGHT WEIGHT NEURAL NETWORKS
(2019-08-22)The research proposes an autonomous solution using deep learning techniques inte- grated on unmanned aerial vehicles (UAV) to effect a rapid and timely search in case of a man overboard (MOB) where a person has accidentally ... -
SUPERVISED MACHINE/DEEP LEARNING TECHNIQUES – A CASE STUDY OF POWDERY MILDEW DETECTION ON THE STRAWBERRY LEAF
(2020-04-16)This research proposed the algorithm, that can detect powdery mildew and give the highest classification accuracy (CA). Three image processing and two machine learning algorithms (artificial neural network; ANN and support ...