Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted
in breakthroughs in many areas. However, deploying these highly accurate models for data …

Convolutional neural networks (CNN) is a specialized case of artificial neural networks
(ANN) and finds its application in computer vision and parallel distributed computing for …

Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …

Inverted bottleneck layers, which are built upon depthwise convolutions, have been the
predominant building blocks in state-of-the-art object detection models on mobile devices. In …

Abstract Deep Neural Network (DNN) models for both resource-rich environments and
resource-constrained devices have become abundant in recent years. As of now, the …

Deep learning is now present in a wide range of services and applications, replacing and
complementing other machine learning algorithms. Performing training and inference of …

Wafer map defect recognition (WMDR) is an important part of the integrated circuit
manufacturing system. Accurate recognition of wafer map defects can help operators …

Present architecture of convolution neural network for diabetic retinopathy (DR-Net) is based
on normal convolution (NC). It incurs high computational cost as NC uses a multiplicative …

Pervasive computing applications commonly involve user's personal smartphones collecting
data to influence application behavior. Applications are often backed by models that learn …

Acoustic scene classification (ASC) categorizes an audio file based on the environment in
which it has been recorded. This has long been studied in the detection and classification of …