Abstract The autoencoder is an artificial neural network that performs nonlinear dimension reduction and learns hidden representations of unlabeled data. With a linear transfer function it is similar to the principal component analysis (PCA). While both methods use weight vectors for linear transformations, the autoencoder does not come with any indication similar to the eigenvalues in PCA that are paired with eigenvectors. We propose a novel autoencoder node saliency method that examines whether the features constructed by autoencoders exhibit properties related to known class labels. The supervised node saliency ranks the nodes based on their capability of performing a learning task. It is coupled with the normalized entropy difference (NED). We establish a property for NED values to verify classifying behaviors among the top ranked nodes. By applying our methods to real datasets, we demonstrate their ability to provide indications on the performing nodes and explain the learned tasks in autoencoders.
Gilles @cite_33 defined based on local signal complexity for matching two images. The method computes Shannon entropy of local attributes in a neighborhood around the current pixel. Image area with higher signal complexity has a flatter distribution of pixel intensities and thus a higher entropy; while a plain image region has one peaked distribution and a lower entropy. Scale saliency @cite_25 includes a measure of the statistical dissimilarity across scale to the saliency method, which can be applied for tracking moving objects in videos @cite_37 .
@cite_37 @cite_25 @cite_33
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Detection and tracking of moving objects is important in the analysis of video data. One approach is to maintain a background model of the scene and subtract it from each frame to detect the moving objects which can then be tracked using Kalman or particle filters. In this paper, we consider simple techniques based on salient points to identify moving objects which are tracked using motion correspondence. We focus on video with a large field of view, such as a traffic intersection with several buildings nearby. Such scenes can contain several salient points, not all of which move between frames. Using public domain video and two types of salient points, we consider how to make these techniques computationally efficient for detection and tracking. Our early results indicate that salient regions obtained using the Lowe keypoints algorithm and the Scale-Saliency algorithm can be used successfully to track vehicles in moderate resolution video. Many computer vision problems can be considered to consist of two main tasks: the extraction of image content descriptions and their subsequent matching. The appropriate choice of type and level of description is of course task dependent, yet it is generally accepted that the low-level or so called early vision layers in the Human Visual System are context independent. This paper concentrates on the use of low-level approaches for solving computer vision problems and discusses three inter-related aspects of this: saliencys scale selection and content description. In contrast to many previous approaches which separate these tasks, we argue that these three aspects are intrinsically related. Based on this observation, a multiscale algorithm for the selection of salient regions of an image is introduced and its application to matching type problems such as tracking, object recognition and image retrieval is demonstrated. A portable alarm device with a battery or low voltage operated sound signal triggered by a magnetic reed switch which is closed to complete the circuit by a magnet attached to a movably mounted arm, the poles of the magnet being positioned perpendicular to the longitudinal dimension of the contact strips of the reed switch to cause the reed switch to close when the magnet is in either of two positions relative to the switch thereby permitting the device to be used with doors which open inwardly or outwardly, with sliding doors, in drawers or with windows on two sides of a room. The device may also be constructed to activate a light signal simultaneously with the sound signal. In a modified form of the device, for use in the purse or in a pocket, the magnet is positioned with its poles parallel to the longitudinal dimension of the contact strips of the reed switch to cause the reed switch to close when the magnet is in one position over the center portion of the reed switch.