We extend the iterated transformation theory (ITT ) fractal image coding algorithm proposed by A. Jacquin [1] to generate a pyramid image representation. An ITT coded image is modeled as the solution of a second kind functional equation. This representation is iterated to form an ITT chain of functional equations which can serve as the framework for a multiscale signal decomposition. This forma...

time lower than other similar performing objective measures.

In this paper we propose a new face recognition system based on a biologically-inspired filtering method. Our work differs from previous proposals in (1) the multi-stage filtering method employed, in (2) the pyramid structure used, and most importantly, in (3) the prototype construction scheme to determine the models stored in memory. The method is much simpler than previous proposals and relat...

Spatial pyramid pooling module or encode-decoder structure are used in deep neural networks for semantic segmentation task. The former networks are able to encode multi-scale contextual information by probing the incoming features with filters or pooling operations at multiple rates and multiple effective fields-of-view, while the latter networks can capture sharper object boundaries by gradual...

We propose a very simple, efficient yet surprisingly effective feature extraction method for face recognition (about 20 lines of Matlab code), which is mainly inspired by spatial pyramid pooling in generic image classification. We show that features formed by simply pooling local patches over a multi-level pyramid, coupled with a linear classifier, can significantly outperform most recent face ...

Recent work has shown that depth estimation from a stereo pair of images can be formulated as a supervised learning task to be resolved with convolutional neural networks (CNNs). However, current architectures rely on patch-based Siamese networks, lacking the means to exploit context information for finding correspondence in illposed regions. To tackle this problem, we propose PSMNet, a pyramid...

The construction of multi-scale image pyramids is used in state-of-the-art methods that perform robust object recognition, such as SIFT and SURF. However, building such image pyramids is computationally expensive, especially when implementations in embedded systems with limited computing resources are considered. Therefore, the use of alternative less expensive approaches are necessary if near ...

In this paper we describe a method we developed for selective detection and enhancement of image feature patterns. A set of directional basis filters were designed to detect the image features of interest, and a steerable pyramid transform [1,2] is used to generate a multiscale representation of the image features that has desirable shift and rotation invariance. By analyzing and selectively pr...

Abstract YOLO V5 algorithm is the current target detection algorithm, but accuracy of boundary regression relatively low, and it cannot be used in scenarios with high requirement prediction frame intersection ratio. Therefore, this paper proposes an improved fast convergence model. The can avoid loss shallow semantic information, deepen pyramid depth increase layer by using cross-hierarchy meth...