In this paper, we present a multiscale “squiral" (square spiral) image processing (SIP) framework. An efficient spiral addressing scheme is deployed for standard pixel based square images to facilitate fast image processing. A SIP-based convolution technique is developed by simulating the “eye tremor" phenomenon of the human visual system. The multiscale SIP operators are constructed by convert...

Abnormal traffic detection is critical to network security and quality of service. However, the similarity features single dimension model cause great difficulties for abnormal detection, thus a big-step convolutional neural based on attention mechanism proposed. Firstly, characteristics are analyzed raw preprocessed mapped into two-dimensional grayscale image. Then, multi-channel images genera...

The continuing Covid-19 pandemic, caused by the SARS-CoV2 virus, has attracted eye of researchers and many studies have focussed on controlling it. affected daily life, employment, health human beings along with socio-economic disruption. Deep Learning (DL) shown great potential in various medical applications past decade continues to assist effective image analysis. Therefore, it is effectivel...

Multiuser communication systems or multiple access scheme favor sequences possessing the ideal periodic cross-correlation function (PCCF) property. In comparison, channel estimation, equalization, and synchronization applications auto-correlation (PACF) However, there is no set of both PCCF PACF properties simultaneously, where balance each other. this work, property are used as base sequences....

A well developed and maintained highway infrastructure is essential for the economic social prosperity of modern societies. Highway maintenance poses significant challenges pertaining to ever-increasing ongoing traffic, insufficient budget allocations lack resources. Road potholes detection timely repair a major contributing factor sustaining safe resilient critical road infrastructure. Current...

For the contour detection task, we use EfficientNet model as backbone network and propose a that uses dilated convolution for multi-scale optimization. The is accumulated top-down layer by layer, combining multiple optimization modules concat together to achieve richer feature representation. To fuse information at different scales, introduce new Multi-scale module replace of deeper structures ...

This study sought to address the problem of insufficient extraction shallow object information and boundary when using traditional FPN structures in current detection algorithms, which degrades accuracy. In this paper, a new structure model, DA-FPN, is proposed. DA-FPN replaces 1 × convolution used conventional for lateral connection with 3 deformable adds feature alignment module after 2x down...