Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Trends in digital image processing of isolated microalgae by incorporating classification algorithm
Identification of microalgae species is of importance due to the uprising of harmful algae
blooms affecting both the aquatic habitat and human health. Despite this occurence …
blooms affecting both the aquatic habitat and human health. Despite this occurence …
Screening of COVID-19 suspected subjects using multi-crossover genetic algorithm based dense convolutional neural network
Fast and accurate screening of novel coronavirus (COVID-19) suspected subjects plays a
vital role in timely quarantine and medical care. Deep transfer learning-based screening …
vital role in timely quarantine and medical care. Deep transfer learning-based screening …
Microalgae identification: Future of image processing and digital algorithm
The identification of microalgae species is an important tool in scientific research and
commercial application to prevent harmful algae blooms (HABs) and recognizing potential …
commercial application to prevent harmful algae blooms (HABs) and recognizing potential …
Microalgae classification based on machine learning techniques
In this paper, two models for classification of microalgae species based on artificial neural
networks have been developed and validated. The models work in combination with …
networks have been developed and validated. The models work in combination with …
Machine learning for microalgae detection and utilization
H Ning, R Li, T Zhou - Frontiers in Marine Science, 2022 - frontiersin.org
Microalgae are essential parts of marine ecology, and they play a key role in species
balance. Microalgae also have significant economic value. However, microalgae are too …
balance. Microalgae also have significant economic value. However, microalgae are too …
Estimation of cyanobacteria pigments in the main rivers of South Korea using spatial attention convolutional neural network with hyperspectral imagery
Although remote sensing techniques have been used to monitor toxic cyanobacteria with
hyperspectral data in inland water, it is difficult to optimize conventional bio-optical …
hyperspectral data in inland water, it is difficult to optimize conventional bio-optical …
Multi-scale feature fusion-based lightweight dual stream transformer for detection of paddy leaf disease
Traditionally, rice leaf disease identification relies on a visual examination of abnormalities
or an analytical result obtained by growing bacteria in the research lab. This method of …
or an analytical result obtained by growing bacteria in the research lab. This method of …
EAOD‐Net: Effective anomaly object detection networks for X‐ray images
C Ma, L Zhuo, J Li, Y Zhang, J Zhang - IET Image Processing, 2022 - Wiley Online Library
Anomaly object detection is the core technology in the application for X‐ray images.
However, the accuracy of current X‐ray anomaly object detection method still needs to be …
However, the accuracy of current X‐ray anomaly object detection method still needs to be …
[HTML][HTML] Classification of inland lake water quality levels based on Sentinel-2 images using convolutional neural networks and spatiotemporal variation and driving …
H Meng, J Zhang, Z Zheng, Y Song, Y Lai - Ecological Informatics, 2024 - Elsevier
Water quality monitoring in inland lakes is crucial to ensuring the health and stability of
aquatic ecosystems. For regional water environment agencies and researchers, remote …
aquatic ecosystems. For regional water environment agencies and researchers, remote …