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Finding appropriate feature representations from radiological images is a vital task for prediction and diagnosis. Deep convolutional neural networks have recently achieved state-of-the-art performance in classification problems from several different domains. Research has also shown the feasibility of using a pre-trained deep neural network as a feature extractor when only a small dataset is available...
This paper studies various periodic orbits and their stability in dynamic binary neural networks. The networks are characterized by the signum activation function and binary connection parameters. The dynamics is simplified into a digital return map on a set of lattice points. In order to grasp the dynamics, we present a feature plane of two simple feature quantities. Calculating the feature quantities...
Saliency detection for images and videos becomes increasingly popular due to its wide applicability. Enormous research efforts have been focused on saliency detection, but it still has some issues in maintaining spatiotemporal consistency of videos and uniformly highlighting entire objects. To address these issues, this paper proposes a superpixel-level spatiotemporal saliency model for saliency detection...
Breeding cows are known to engage in sociality, in which they interact and form groups. This paper proposes a method of detecting the interaction between breeding cows from time-series pictures of pastures by a similar image retrieval method using a Bag of Visual Words. We divided the interaction detection into three tasks: detecting a pair of cows in an interaction, pinpointing the time and the place...
We propose a new non-parametric level set model for automatic image clustering and segmentation based on non-negative matrix factorization (NMF). We show that NMF: (i) clusters the image into distinct homogeneous regions and (ii) provides the local spatial distribution of each region within the image. Furthermore, NMF has a controllable resolution and can discover homogeneous regions as small as one...
As a graph-based clustering approach, dominant sets clustering determines the number of clusters automatically and possesses some other nice properties. By applying histogram equalization transformation to the similarity matrix before clustering, we are able to accomplish the dominant sets clustering process without any user-specified parameters. However, this transformation usually leads to over-segmented...
Vascular Similarly Measurement (VSM) is an important tool in many biomedical applications. However, designing a robust computational VSM remains a challenge. We investigate different wavelet families and their orders to find their efficacy as feature extractors for computational VSM. Using a 50-subject dataset of RGB ocular surface vasculature images, we show that a compact feature vector composed...
Human Action Recognition methods have prospered during the last decade. They seek to automatically analyze ongoing activities in different camera views by using machine-learning algorithms in video sequences. Various human action recognition methods match local features and global features using action class labels in which abundant visual spatio-temporal information can hardly be generalized. To...
This paper presents a study of line-wise text identification in comic books. Due to the unavailability of a single OCR system which can handle comic text of multiple scripts, the comic text identification based on script becomes an essential step for choosing the appropriate OCR. In this investigation, a new attempt has been made to explore a comic text identification technique of speech balloon to...
This paper proposes an efficient method to detect any fraud document. It considers texture features, such as Local binary pattern and Gabor filters and performs a histogram matching to analyze the document. Texture features and RGB color information of each word in the document are extracted. Normalized histograms of two different images of a document are compared to generate a matching score for...
Alzheimer's disease as one type of dementia can cause problems to human memory, thinking and behavior. The brain damage can be detected using brain volume and whole brain form. The correlation between brain shrinkage and reduction of brain volume can affect to deformation texture. In this research, the enhancement texture approach was proposed, called advanced local binary pattern (ALBP) method. ALBP...
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