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Artificial intelligence and machine learning tools for high-performance microalgal wastewater treatment and algal biorefinery: A critical review
The increased water scarcity, depletion of freshwater resources, and rising environmental
awareness are stressing for the development of sustainable wastewater treatment …
awareness are stressing for the development of sustainable wastewater treatment …
Microalgae conversion to alternative energy, operating environment and economic footprint: an influential approach towards energy conversion, and management
Microalgae (MA) biorefinery is a vital platform for the conversion of biomass into biofuels,
biomaterials, and bioactive substances and it can remediate the pollutant from the …
biomaterials, and bioactive substances and it can remediate the pollutant from the …
[HTML][HTML] Sensors, features, and machine learning for oil spill detection and monitoring: A review
Remote sensing technologies and machine learning (ML) algorithms play an increasingly
important role in accurate detection and monitoring of oil spill slicks, assisting scientists in …
important role in accurate detection and monitoring of oil spill slicks, assisting scientists in …
Machine learning and deep learning based computational approaches in automatic microorganisms image recognition: methodologies, challenges, and …
Microorganisms or microbes comprise majority of the diversity on earth and are extremely
important to human life. They are also integral to processes in the ecosystem. The process of …
important to human life. They are also integral to processes in the ecosystem. The process of …
A novel deep learning instance segmentation model for automated marine oil spill detection
The visual similarity of oil slick and other elements, known as look-alike, affects the reliability
of synthetic aperture radar (SAR) images for marine oil spill detection. So far, detection and …
of synthetic aperture radar (SAR) images for marine oil spill detection. So far, detection and …
Image analysis for individual identification and feeding behaviour monitoring of dairy cows based on Convolutional Neural Networks (CNN)
Highlights•Top head image is used as Region of Interest for dairy cow individual
identification.•Dairy cows are classified in the feeder zone as standing or feeding.•Cow is …
identification.•Dairy cows are classified in the feeder zone as standing or feeding.•Cow is …
DRNet: Dual-stage refinement network with boundary inference for RGB-D semantic segmentation of indoor scenes
Semantic segmentation is a dense pixel prediction task, and its accuracy depends on the
extraction of long-range contextual knowledge and refinement of segmentation boundaries …
extraction of long-range contextual knowledge and refinement of segmentation boundaries …
A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches
Microorganisms play a vital role in human life. Therefore, microorganism detection is of great
significance to human beings. However, the traditional manual microscopic detection …
significance to human beings. However, the traditional manual microscopic detection …
[HTML][HTML] Delineation of agricultural fields using multi-task BsiNet from high-resolution satellite images
This paper presents a new multi-task neural network, called BsiNet, to delineate agricultural
fields from high-resolution satellite images. BsiNet is modified from a Psi-Net by structuring …
fields from high-resolution satellite images. BsiNet is modified from a Psi-Net by structuring …
Survey of supervised learning for medical image processing
A Aljuaid, M Anwar - SN Computer Science, 2022 - Springer
Medical image interpretation is an essential task for the correct diagnosis of many diseases.
Pathologists, radiologists, physicians, and researchers rely heavily on medical images to …
Pathologists, radiologists, physicians, and researchers rely heavily on medical images to …