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An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation
TLDR
This method uses an ensemble system of bagged and boosted decision trees and utilizes a feature vector based on the orientation analysis of gradient vector field, morphological transformation, line strength measures, and Gabor filter responses to segmentation of blood vessels in retinal photographs. Expand
Blood vessel segmentation methodologies in retinal images - A survey
TLDR
The aim of this paper is to review, analyze and categorize the retinal vessel extraction algorithms, techniques and methodologies, giving a brief description, highlighting the key points and the performance measures. Expand
Crowd analysis: a survey
TLDR
This paper presents a survey on crowd analysis methods employed in computer vision research and discusses perspectives from other research disciplines and how they can contribute to the computer vision approach. Expand
The Visual Object Tracking VOT2013 Challenge Results
TLDR
The evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset are presented, offering a more systematic comparison of the trackers. Expand
Plant species identification using digital morphometrics: A review
TLDR
The main computational, morphometric and image processing methods that have been used in recent years to analyze images of plants are reviewed, introducing readers to relevant botanical concepts along the way. Expand
Summarizing Videos with Attention
TLDR
This work proposes a simple, self-attention based network for video summarization which performs the entire sequence to sequence transformation in a single feed forward pass and single backward pass during training. Expand
Deep-plant: Plant identification with convolutional neural networks
TLDR
Experimental results using these CNN features with different classifiers show consistency and superiority compared to the state-of-the art solutions which rely on hand-crafted features. Expand
AMNet: Memorability Estimation with Attention
TLDR
The design and evaluation of an end-to-end trainable, deep neural network with a visual attention mechanism for memorability estimation in still images is presented and the network outperforms the existing state of the art models on both datasets. Expand
How deep learning extracts and learns leaf features for plant classification
TLDR
This paper learns useful leaf features directly from the raw representations of input data using Convolutional Neural Networks (CNN), and gains intuition of the chosen features based on a Deconvolutional Network (DN) approach, and gains insights into the design of new hybrid feature extraction models which are able to further improve the discriminative power of plant classification systems. Expand
An approach to localize the retinal blood vessels using bit planes and centerline detection
TLDR
An automated method for segmentation of blood vessels in retinal images is reported and the results demonstrate that the performance of the proposed algorithm is comparable with state of the art techniques in terms of accuracy, sensitivity and specificity. Expand
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