A review of dimensionality reduction techniques for efficient computation
S Velliangiri, S Alagumuthukrishnan - Procedia Computer Science, 2019 - Elsevier
Dimensionality Reduction (DR) is the pre-processing step to remove redundant features,
noisy and irrelevant data, in order to improve learning feature accuracy and reduce the …
noisy and irrelevant data, in order to improve learning feature accuracy and reduce the …
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 …
Image edge detection: A new approach based on fuzzy entropy and fuzzy divergence
M Versaci, FC Morabito - International Journal of Fuzzy Systems, 2021 - Springer
In image pre-processing, edge detection is a non-trivial task. Sometimes, images are
affected by vagueness so that the edges of objects are difficult to distinguish. Hence, the …
affected by vagueness so that the edges of objects are difficult to distinguish. Hence, the …
Detecting pneumonia using convolutions and dynamic capsule routing for chest X-ray images
An entity's existence in an image can be depicted by the activity instantiation vector from a
group of neurons (called capsule). Recently, multi-layered capsules, called CapsNet, have …
group of neurons (called capsule). Recently, multi-layered capsules, called CapsNet, have …
Refined edge detection with cascaded and high-resolution convolutional network
Edge detection is represented as one of the most challenging tasks in computer vision, due
to the complexity of detecting the edges or boundaries in real-world images that contains …
to the complexity of detecting the edges or boundaries in real-world images that contains …
[HTML][HTML] Automated delineation of agricultural field boundaries from Sentinel-2 images using recurrent residual U-Net
Delineation of agricultural fields is desirable for operational monitoring of agricultural
production and is essential to support food security. Due to large within-class variance of …
production and is essential to support food security. Due to large within-class variance of …
Rice Disease Detection Using Artificial Intelligence and Machine Learning Techniques to Improvise Agro‐Business
Agro‐business is highly dependent on rice quality and its protection from diseases. There
are several prerequisites for the procedures and the strategies that are productive and …
are several prerequisites for the procedures and the strategies that are productive and …
Interactive blood vessel segmentation from retinal fundus image based on canny edge detector
Optometrists, ophthalmologists, orthoptists, and other trained medical professionals use
fundus photography to monitor the progression of certain eye conditions or diseases …
fundus photography to monitor the progression of certain eye conditions or diseases …
Sobel edge detection based on weighted nuclear norm minimization image denoising
R Tian, G Sun, X Liu, B Zheng - Electronics, 2021 - mdpi.com
As a classic and effective edge detection operator, the Sobel operator has been widely used
in image segmentation and other image processing technologies. This operator has obvious …
in image segmentation and other image processing technologies. This operator has obvious …
Adaptive resource optimized edge federated learning in real-time image sensing classifications
With the exponential growth of the Internet of things (IoT) in remote sensing image
applications, network resource orchestration and data privacy are significant aspects to …
applications, network resource orchestration and data privacy are significant aspects to …