Convolutional neural networks for automated tooth numbering on panoramic radiographs: A
scoping review - PMC Back to Top Skip to main content NIH NLM Logo Access keys NCBI …

Object detection is a widely applied approach in addressing many real-world computer
vision challenges. Despite its importance, object detection is computationally intensive and …

Plastic greenhouses (PGs) play a vital role in modern agricultural development by providing
a controlled environment for the cultivation of food crops. Their widespread adoption has the …

In the remote sensing field, object detection holds immense value for applications such as
land use classification, disaster monitoring, and infrastructure planning, where accurate and …

Multiscale features are of great importance in modern convolutional neural networks,
showing consistent performance gains on numerous vision tasks. Therefore, many plug-and …

Addressing the COVID-19 epidemic since December 2019 has emphasized the criticality of
timely and error-free identification of infected COVID-19 individuals in medical settings. To …

Over the last 10 years, researchers and developers shows a significant evolution in the
development of intelligent transport systems (ITS) ie self-driving cars. One of the challenging …

As is well known, the classification performance of large deep neural networks is closely
related to the amount of annotated data. However, in practical applications, the quantity of …

Deep neural network (DNN) based scene text recognition (STR) methods usually require a
large amount of annotated data for training, which is time-consuming and cost-expensive in …

The binary neural network (BNN) is an attractive model for edge computing, and memristor-
based neuromorphic computing platform provides competitive end-side deployment …