Results 301 to 310 of about 2,264,527 (364)
MULTITASK FEATURE SELECTION WITH TASK DESCRIPTORS [PDF]
Biocomputing 2016, 2015 Machine learning applications in precision medicine are severely limited by the scarcity of data to learn from. Indeed, training data often contains many more features than samples. To alleviate the resulting statistical issues, the multitask learning framework proposes to learn different but related tasks jointly, rather than independently, by sharing
Véronique Stoven +2 more
openaire +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
IEEE Geoscience and Remote Sensing Letters, 2021
Classifying tree species from point clouds acquired by light detection and ranging (LiDAR) scanning systems is important in many applications, including remote sensing, virtual reality, and forestry inventory.
Yanxing Lv +6 more
semanticscholar +1 more source
Classifying tree species from point clouds acquired by light detection and ranging (LiDAR) scanning systems is important in many applications, including remote sensing, virtual reality, and forestry inventory.
Yanxing Lv +6 more
semanticscholar +1 more source
Feature Descriptors for Face Recognition
2020 IEEE 17th India Council International Conference (INDICON), 2020Human face has lot of information about identity as well as emotional status of the individual. Face recognition for authentication purpose is a challenging as well as an interesting problem. These problems have great impacts on crucial applications in several areas like identification, banking, law enforcement, security system access, and personal ...
Puja S. Prasad, Vinit Kumar Gunjan
openaire +2 more sources
Shape of Gaussians as feature descriptors
2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009This paper introduces a feature descriptor called shape of Gaussian (SOG), which is based on a general feature descriptor design framework called shape of signal probability density function (SOSPDF). SOSPDF takes the shape of a signal's probability density function (pdf) as its feature.
Tianjiang Wang, Fang Liu, Liyu Gong
openaire +2 more sources
Harris feature vector descriptor
2010 International Conference on Machine Learning and Cybernetics, 2010This paper defines a new image feature called Harris feature vector, which is able to describe the image gradient distribution in an effective way. By computing the mean and the standard deviation of the Harris feature vector in a local image region, novel descriptors are constructed for feature matching which are invariable to image rigid ...
Xu-Guang Wang, Hai-Yan Cheng, Jie Su
openaire +2 more sources
Texture descriptors for representing feature vectors
Expert Systems with Applications, 2019Abstract Pattern representation affects classification performance. Although discovering “universal” features that work for many classification problems is ideal, most representations are problem specific. In this paper, we improve the classification performance of a classifier system by transforming a one-dimensional input descriptor into a two ...
Loris Nanni +2 more
openaire +2 more sources
Features Descriptors for Demographic Estimation: A Comparative Study [PDF]
, 2014 Estimation of demographic information from video sequence with people is a topic of growing interest in the last years. Indeed automatic estimation of audience statistics in digital signage as well as the human interaction in social robotic environment needs of increasingly robust algorithm for gender, race and age classification.
Carcagnì Pierluigi +4 more
openaire +3 more sources
TLD and Struck: A Feature Descriptors Comparative Study [PDF]
, 2014 Object tracking across multiple cameras is a very challenge issue in vision based monitoring applications. The selection of features is the first step to realize a reliable tracking algorithm.,In this work we analyse TLD and Struck, which are two of the most cited real-time visual trackers proposed in the literature in last years.
Adamo F +4 more
openaire +3 more sources
Evaluation of feature descriptors for texture classification
Journal of Electronic Imaging, 2012Successful execution of tasks such as image classification, object detection and recognition, and scene classification depends on the definition of a set of features able to describe images effectively. Texture is among the features used by the human visual system.
William Robson Schwartz +3 more
openaire +1 more source
A comparison of feature descriptors for visual SLAM
2013 European Conference on Mobile Robots, 2013Feature detection and feature description plays an important part in Visual Simultaneous Localization and Mapping (VSLAM). Visual features are commonly used to efficiently estimate the motion of the camera (visual odometry) and link the current image to previously visited parts of the environment (place recognition, loop closure).
Jan Helge Klussendorff +2 more
openaire +2 more sources