Discriminative Detection and Alignment in Volumetric Data
نویسندگان
چکیده
In this paper, we aim for detection and segmentation of Arabidopsis thaliana cells in volumetric image data. To this end, we cluster the training samples by their size and aspect ratio and learn a detector and a shape model for each cluster. While the detector yields good cell hypotheses, additionally aligning the shape model to the image allows to better localize the detections and to reconstruct the cells in case of low quality input data. We show that due to the more accurate localization, the alignment also improves the detection performance.
منابع مشابه
Accurate Detection in Volumetric Images Using Elastic Registration Based Validation
In this paper, we propose a method for accurate detection and segmentation of cells in dense plant tissue of Arabidopsis Thaliana. We build upon a system that uses a top down approach to yield the cell segmentations: A discriminative detection is followed by an elastic alignment of a cell template. While this works well for cells with a distinct appearance, it fails once the detection step cann...
متن کاملF-STONE: A Fast Real-Time DDOS Attack Detection Method Using an Improved Historical Memory Management
Distributed Denial of Service (DDoS) is a common attack in recent years that can deplete the bandwidth of victim nodes by flooding packets. Based on the type and quantity of traffic used for the attack and the exploited vulnerability of the target, DDoS attacks are grouped into three categories as Volumetric attacks, Protocol attacks and Application attacks. The volumetric attack, which the pro...
متن کاملImproved Face Detection and Alignment using Cascade Deep Convolutional Network
Real-world face detection and alignment demand an advanced discriminative model to address challenges by pose, lighting and expression. Recent studies have utilized the relation between face detection and alignment to make models computationally efficiency, but they ignore the connection between each cascade CNNs. In this paper, we combine detection, calibration and alignment in each Cascade CN...
متن کاملDiscriminative Word Alignment with Syntactic Features
This report introduces a study on syntactic features used in a discriminative word alignment model. The features are implemented on a state-of-the-art discriminative word alignment system. The syntactic features are extracted from parse trees. Three types of syntactic features are experimented in this work: one global tree path feature and two first order tree features. Experimental results sho...
متن کاملMarkovian Mixture Face Recognition with Discriminative Face Alignment
A typical automatic face recognition system is composed of three parts: face detection, face alignment and face recognition. Conventionally, these three parts are processed in a bottom-up manner: face detection is performed first, then the results are passed to face alignment, and finally to face recognition. The bottom-up approach is one extreme of vision approaches. The other extreme approach...
متن کامل