Search alternatives:
processing algorithm » processing algorithms (Expand Search)
waste processing » image processing (Expand Search), text processing (Expand Search), melt processing (Expand Search)
making algorithm » cosine algorithm (Expand Search)
deer algorithm » search algorithm (Expand Search)
element deer » elementi per (Expand Search)
processing algorithm » processing algorithms (Expand Search)
waste processing » image processing (Expand Search), text processing (Expand Search), melt processing (Expand Search)
making algorithm » cosine algorithm (Expand Search)
deer algorithm » search algorithm (Expand Search)
element deer » elementi per (Expand Search)
-
1
Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach
Published 2025“…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
-
2
-
3
-
4
-
5
-
6
An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network
Published 2021“…In this work, an efficient medical decision system for diabetes prediction based on Deep Neural Network (DNN) is presented. Such algorithms are state‐of‐the‐art in computer vision, language processing, and image analysis, and when applied in healthcare for prediction and diagnosis purposes, these algorithms can produce highly accurate results. …”
-
7
-
8
Prediction the performance of multistage moving bed biological process using artificial neural network (ANN)
Published 2020“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”
-
9
Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network
Published 2020“…<p dir="ltr">The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs), cow manure (CM), and the application of chemical pre-treatment with NaHCO<sub>3</sub> on the performance of anaerobic digestion (AD) process. …”
-
10
-
11
A machine learning model for early detection of diabetic foot using thermogram images
Published 2021“…However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. …”
-
12
-
13
Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning
Published 2020Get full text
doctoralThesis -
14
-
15
A neuro-heuristic approach for segmenting handwritten Arabic text. (c2001)
Published 2001Get full text
Get full text
masterThesis -
16
A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”
-
17
Random vector functional link network: Recent developments, applications, and future directions
Published 2023“…RVFL model has several characteristics such as fast training speed, direct links, simple architecture, and universal approximation capability, that make it a viable randomized neural network. This article presents the first comprehensive review of the evolution of RVFL model, which can serve as the extensive summary for the beginners as well as practitioners. …”
-
18
PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits
Published 2022“…Implications are that toxicity trigger detection algorithms can leverage generic approaches but must also tailor detections to specific communities.…”
-
19
Developing a UAE-Based Disputes Prediction Model using Machine Learning
Published 2022Get full text
doctoralThesis -
20
Investigation of Forming a Framework to shortlist contractors in the tendering phase
Published 2022“…The model to shortlist contractors in the tendering phase was created using machine learning to enable more contractors to submit for a project without having to waste time and money on the tendering process; if they are compatible with the project, then they have a high chance of getting it by being short-listed for the project, which they can then submit their tender package for; this will also ensure that the best company gets the job for the client which will act as a great step towards improving the tendering in construction projects. …”
Get full text