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 …
Computer vision for microscopic skin cancer diagnosis using handcrafted and non‐handcrafted features
T Saba - Microscopy Research and Technique, 2021 - Wiley Online Library
Skin covers the entire body and is the largest organ. Skin cancer is one of the most dreadful
cancers that is primarily triggered by sensitivity to ultraviolet rays from the sun. However, the …
cancers that is primarily triggered by sensitivity to ultraviolet rays from the sun. However, the …
[HTML][HTML] A decision support system for multimodal brain tumor classification using deep learning
Multiclass classification of brain tumors is an important area of research in the field of
medical imaging. Since accuracy is crucial in the classification, a number of techniques are …
medical imaging. Since accuracy is crucial in the classification, a number of techniques are …
Brain tumor segmentation using K‐means clustering and deep learning with synthetic data augmentation for classification
Image processing plays a major role in neurologists' clinical diagnosis in the medical field.
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Brain tumor detection and multi‐classification using advanced deep learning techniques
A brain tumor is an uncontrolled development of brain cells in brain cancer if not detected at
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
[HTML][HTML] A sustainable deep learning framework for object recognition using multi-layers deep features fusion and selection
With an overwhelming increase in the demand of autonomous systems, especially in the
applications related to intelligent robotics and visual surveillance, come stringent accuracy …
applications related to intelligent robotics and visual surveillance, come stringent accuracy …
A resource conscious human action recognition framework using 26-layered deep convolutional neural network
Vision-based human action recognition (HAR) is a hot topic of research from the decade due
to a few popular applications such as visual surveillance and robotics. For correct action …
to a few popular applications such as visual surveillance and robotics. For correct action …
Maximum entropy scaled super pixels segmentation for multi-object detection and scene recognition via deep belief network
Recent advances in visionary technologies impacted multi-object recognition and scene
understanding. Such scene-understanding tasks are a demanding part of several …
understanding. Such scene-understanding tasks are a demanding part of several …
[HTML][HTML] Hybrid malware classification method using segmentation-based fractal texture analysis and deep convolution neural network features
As the number of internet users increases so does the number of malicious attacks using
malware. The detection of malicious code is becoming critical, and the existing approaches …
malware. The detection of malicious code is becoming critical, and the existing approaches …
[HTML][HTML] Human action recognition: a paradigm of best deep learning features selection and serial based extended fusion
S Khan, MA Khan, M Alhaisoni, U Tariq, HS Yong… - Sensors, 2021 - mdpi.com
Human action recognition (HAR) has gained significant attention recently as it can be
adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task …
adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task …