Data harmonization for heterogeneous datasets: a systematic literature review

G Kumar, S Basri, AA Imam, SA Khowaja, LF Capretz… - Applied Sciences, 2021 - mdpi.com
As data size increases drastically, its variety also increases. Investigating such
heterogeneous data is one of the most challenging tasks in information management and …

[HTML][HTML] Deep learning applications for oil palm tree detection and counting

K Kipli, S Osman, A Joseph, H Zen… - Smart Agricultural …, 2023 - Elsevier
Oil palms are one of the essential crops in agricultural productivity for developing countries
such as Malaysia and other tropical areas. For predicting the yield and production of palm …

Leukocyte classification based on feature selection using extra trees classifier: Atransfer learning approach

D Baby, SJ Devaraj, J Hemanth - Turkish Journal of Electrical …, 2021 - journals.tubitak.gov.tr
The criticality of investigating the white blood cell (WBC) count cannot be underestimated, as
white blood cells are an important component of the body's defence system. From helping to …

[PDF][PDF] Performance investigation of two-stage detection techniques using traffic light detection dataset

SA Ajagbe, AA Adegun, AB Olanrewaju… - … Journal of Artificial …, 2023 - researchgate.net
Using a camera to monitor an object or a group of objects over time is the process of object
detection. It can be used for a variety of things, including security and surveillance, video …

[PDF][PDF] An optimized deep learning model for flower classification using NAS-FPN and faster R-CNN

I Patel, S Patel - International Journal of Scientific & Technology …, 2020 - researchgate.net
In computer vision, object detection is widely used in many applications such as face
detection, video surveillance, vehicle detection, plant leaf detection etc. Deep neural …

[PDF][PDF] A comprehensive study of deep learning architectures, applications and tools

N Ganatra, A Patel - International Journal of Computer Sciences and …, 2018 - academia.edu
The Deep learning architectures fall into the widespread family of machine learning
algorithms that are based on the model of artificial neural network. Rapid advancements in …

Leukocyte classification based on transfer learning of VGG16 features by K-nearest neighbor classifier

D Baby, SJ Devaraj - 2021 3rd International Conference on …, 2021 - ieeexplore.ieee.org
White blood cells (WBCs) are also called as leukocyte which is a significant component of
blood that covers 1% of the total blood, protect us from numerous types of illness and other …

Deep learning models for image segmentation

S Patel - 2021 8th International conference on computing for …, 2021 - ieeexplore.ieee.org
Artificial Intelligence and deep learning models have evolved rapidly in the last decade and
successfully applied to face recognition, autonomous driving, satellite imaging, robotics, and …

A Comprehensive Study of Deep Learning and Performance Comparison of Deep Neural Network Models (YOLO, RetinaNet).

NI Nife, M Chtourou - International Journal of Online & …, 2023 - search.ebscohost.com
This paper presents the latest advances in machine learning techniques and highlights
deep learning (DL) methods in recent studies. This technology has recently received great …

Brain Tumor Classification using Deep Learning: A State-of-the-Art Review

M Rasool, A Noorwali, H Ghandorh, NA Ismail… - … , Technology & Applied …, 2024 - etasr.com
Given that the number of available brain tumor images has grown, Deep Learning (DL)
plays a critical role in brain tumor classification in terms of accurately diagnosing and …