Towards digital diagnosis of malaria: How far have we reached?

S Aqeel, Z Haider, W Khan - Journal of Microbiological Methods, 2023 - Elsevier
… of Morogoro and Kilimanjaro in Tanzania. A Random Forest … A comparative analysis of the
NB, SVM and ANN was carried … CNN models was replaced by classification models like SVM

Image segmentation techniques: statistical, comprehensive, semi-automated analysis and an application perspective analysis of mathematical expressions

Sakshi, V Kukreja - Archives of Computational Methods in Engineering, 2023 - Springer
… -based segmentation techniques (CNN, RNN, LSTM… comparative analysis-based survey
is still found to be on the verge of seeking more attention from the survey community of research

[HTML][HTML] Spatial and temporal deep learning methods for deriving land-use following deforestation: A pan-tropical case study using Landsat time series

RN Masolele, V De Sy, M Herold, D Marcos… - Remote Sensing of …, 2021 - Elsevier
… likelihood estimators, support vector machines, or random forests… pasture in Tanzania, Kenya,
and some parts of West Africa. … 2D-CNN achieved higher classification performance on the …

[HTML][HTML] Machine learning and soil sciences: A review aided by machine learning tools

J Padarian, B Minasny, AB McBratney - Soil, 2020 - soil.copernicus.org
… Other comparative studies also showed a consistent higher performance of ML methods (NN,
SVM, … b) show that a deep CNN trained using a large dataset (around 20 000 soil samples) …

Post-disaster recovery assessment with machine learning-derived land cover and land use information

M Sheykhmousa, N Kerle, M Kuffer, S Ghaffarian - Remote sensing, 2019 - mdpi.com
… Moreover, CNN is not easy to use and computationally is … linked through damage classes
in the event time, all translated … as a classifier compared to SVM in the current research. …

[PDF][PDF] Comparative Analysis for Predicting Cardiovascular Diseases Using Machine Learning and Deep Learning Approaches

CL Uzoegwu, F Ahmed, H Li - researchgate.net
… failure treatment, echocardiography interpretation, evaluation … SVM or MLP use class count
for classification, according to … , and MLP and CNN, two DL models, are studied. Results will …

A real-time electrical load forecasting and unsupervised anomaly detection framework

X Wang, Z Yao, M Papaefthymiou - Applied Energy, 2023 - Elsevier
… Solyali et al. have presented a comparative analysis … That study compares a support vector
machine (SVM), a … interval is both translated and resized, since mere translation will result in …

Real-time detection of electrical load anomalies through hyperdimensional computing

X Wang, R Flores, J Brouwer, M Papaefthymiou - Energy, 2022 - Elsevier
… , and a rural village in Tanzania that relies on wireless monitoring … SVM tends to provide
better performance than other ML models in … metric for a balanced interpretation of results. Other …

Detecting mammals in UAV images: Best practices to address a substantially imbalanced dataset with deep learning

B Kellenberger, D Marcos, D Tuia - Remote sensing of environment, 2018 - Elsevier
Using our recommendations, we are able to train a CNN reducing the number of false
positives by an order of magnitude compared … Although the task of manual photo-interpretation

[HTML][HTML] Animal species detection and classification framework based on modified multi-scale attention mechanism and feature pyramid network

CC Ukwuoma, Z Qin, SB Yussif, MN Happy, GU Nneji… - Scientific African, 2022 - Elsevier
… In contrast, Tanzanian and American scientists' reports show … by the outstanding performance
of recent research results. … values contributing to CNN, LASSO, and SVM applications. …