Search alternatives:
processing algorithm » processing algorithms (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
ipca algorithm » jaya algorithm (Expand Search)
processing algorithm » processing algorithms (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
ipca algorithm » jaya algorithm (Expand Search)
-
81
Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review
Published 2024“…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. …”
-
82
Developing a framework for using face recognition in transit payment transactions
Published 2021“…The argued face recognition accuracy between 98%-99.2% and average processing time including metro gate opening time ranges between 1114-1400 milliseconds. …”
Get full text
-
83
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
Published 2023“…An integrated approach, featuring the application of advanced image processing techniques and geospatial analysis using machine learning, was adopted to characterise the site while automating the process and investigating its applicability. …”
Get full text
-
84
Optical character recognition on heterogeneous SoC for HD automatic number plate recognition system
Published 2018“…</p><h2>Other Information</h2> <p> Published in: EURASIP Journal on Image and Video Processing<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1186/s13640-018-0298-2" target="_blank">http://dx.doi.org/10.1186/s13640-018-0298-2</a></p>…”
-
85
A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…Deep learning approaches have made significant progress in digital image processing, particularly in object recognition and classification, and are among the most popular computer vision tools. …”
-
86
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
Published 2023“…An integrated approach, featuring the application of advanced image processing techniques and geospatial analysis using machine learning, was adopted to characterise the site while automating the process and investigating its applicability. …”
Get full text
article -
87
A Navigation System for Indoor/Outdoor Environments with an Unmanned Ground Vehicle (UGV)
Published 2015Get full text
doctoralThesis -
88
Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
-
89
Decision-level Gait Fusion for Human Identification at a Distance
Published 2014Get full text
doctoralThesis -
90
Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data
Published 2021Get full text
doctoralThesis -
91
DASSI: differential architecture search for splice identification from DNA sequences
Published 2022“…The demand for robust algorithms over the recent years has brought huge success in the field of Deep Learning (DL) in solving many difficult tasks in image, speech and natural language processing by automating the manual process of architecture design. …”
-
92
A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education
Published 2022“…Facial recognition algorithms extract helpful information from online platforms as image classification techniques are applied to detect the emotions of student and/or teacher faces. …”
Get full text
-
93
An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control
Published 2020“…This paper proposes a system to aid people with motor disabilities by restoring their ability to move effectively and effortlessly without having to rely on others utilizing an eye-controlled electric wheelchair. The system input is images of the user’s eye that are processed to estimate the gaze direction and the wheelchair was moved accordingly. …”
-
94
Developing an online hate classifier for multiple social media platforms
Published 2020“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”
-
95
Exploring new horizons in neuroscience disease detection through innovative visual signal analysis
Published 2024“…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …”
-
96
From Collatz Conjecture to chaos and hash function
Published 2023“…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
-
97
Single-channel speech denoising by masking the colored spectrograms
Published 2025“…<p>Speech denoising (SD) covers the algorithms that remove the background noise from the target speech and thus improve its quality and intelligibility. …”
-
98
Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
Published 2017Get full text
doctoralThesis -
99
Secure and Anonymous Communications Over Delay Tolerant Networks
Published 2020“…Instead, our work introduces a novel message forwarding algorithm that delivers messages, from source to destination, via a random walk process. …”
-
100
The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”