Object detection for industrial applications refers to analyzing the captured images and
videos and finding the relationship between the detected objects for better optimization, data …

Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

Recent success of semantic segmentation approaches on demanding road driving datasets
has spurred interest in many related application fields. Many of these applications involve …

We present a class of efficient models called MobileNets for mobile and embedded vision
applications. MobileNets are based on a streamlined architecture that uses depth-wise …

We present an interpretation of Inception modules in convolutional neural networks as being
an intermediate step in-between regular convolution and the depthwise separable …

Lightweight deep convolutional neural networks (LDCNNs) are vital components of mobile
intelligence, particularly in mobile vision. Although various heavy networks with increasingly …

Rainy weather is a challenge for many vision-oriented tasks (eg, object detection and
segmentation), which causes performance degradation. Image deraining is an effective …

In recent years, there have been attempts to increase the kernel size of Convolutional
Neural Nets (CNNs) to mimic the global receptive field of Vision Transformers'(ViTs) self …

Structural re-parameterization has drawn increasing attention in various computer vision
tasks. It aims at improving the performance of deep models without introducing any …

In recent years, larger and deeper models are springing up and continuously pushing state-
of-the-art (SOTA) results across various fields like natural language processing (NLP) and …