A review on automatic image annotation techniques
Nowadays, more and more images are available. However, to find a required image for an
ordinary user is a challenging task. Large amount of researches on image retrieval have …
ordinary user is a challenging task. Large amount of researches on image retrieval have …
Adversarially learned anomaly detection
Anomaly detection is a significant and hence well-studied problem. However, developing
effective anomaly detection methods for complex and high-dimensional data remains a …
effective anomaly detection methods for complex and high-dimensional data remains a …
[PDF][PDF] A brief survey of color image preprocessing and segmentation techniques
S Bhattacharyya - Journal of Pattern Recognition Research, 2011 - Citeseer
Multichannel information processing from a diverse range of channel information is highly
time-and space-complex owing to the variety and enormity of underlying data. Most of the …
time-and space-complex owing to the variety and enormity of underlying data. Most of the …
FallDeFi: Ubiquitous fall detection using commodity Wi-Fi devices
Falling or tripping among elderly people living on their own is recognized as a major public
health worry that can even lead to death. Fall detection systems that alert caregivers, family …
health worry that can even lead to death. Fall detection systems that alert caregivers, family …
Segmentation of tomato leaf images based on adaptive clustering number of K-means algorithm
In image-based intelligent identification of crop diseases, leaf image segmentation is a key
step. Although the K-means is a commonly used algorithm between a number of segmented …
step. Although the K-means is a commonly used algorithm between a number of segmented …
Low-rank sparse subspace for spectral clustering
Traditional graph clustering methods consist of two sequential steps, ie, constructing an
affinity matrix from the original data and then performing spectral clustering on the resulting …
affinity matrix from the original data and then performing spectral clustering on the resulting …
Segmentation and classification of hyperspectral images using minimum spanning forest grown from automatically selected markers
Y Tarabalka, J Chanussot… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
A new method for segmentation and classification of hyperspectral images is proposed. The
method is based on the construction of a minimum spanning forest (MSF) from region …
method is based on the construction of a minimum spanning forest (MSF) from region …
Fast image-based obstacle detection from unmanned surface vehicles
M Kristan, VS Kenk, S Kovačič… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Obstacle detection plays an important role in unmanned surface vehicles (USVs). The USVs
operate in a highly diverse environments in which an obstacle may be a floating piece of …
operate in a highly diverse environments in which an obstacle may be a floating piece of …
Radar‐based fall detection based on Doppler time–frequency signatures for assisted living
Falls are a major public health concern and main causes of accidental death in the senior
US population. Timely and accurate detection permit immediate assistance after a fall and …
US population. Timely and accurate detection permit immediate assistance after a fall and …
[PDF][PDF] An integrated interactive technique for image segmentation using stack based seeded region growing and thresholding.
Image segmentation is a challenging process in numerous applications. Region growing is
one of the segmentation techniques as a basis for the Seeded Region Growing method. A …
one of the segmentation techniques as a basis for the Seeded Region Growing method. A …