A comprehensive review of convolutional neural networks for defect detection in industrial applications
Quality inspection and defect detection remain critical challenges across diverse industrial
applications. Driven by advancements in Deep Learning, Convolutional Neural Networks …
applications. Driven by advancements in Deep Learning, Convolutional Neural Networks …
Yolov9: Learning what you want to learn using programmable gradient information
Today's deep learning methods focus on how to design the objective functions to make the
prediction as close as possible to the target. Meanwhile, an appropriate neural network …
prediction as close as possible to the target. Meanwhile, an appropriate neural network …
Surface defect detection methods for industrial products with imbalanced samples: A review of progress in the 2020s
Industrial products typically lack defects in smart manufacturing systems, which leads to an
extremely imbalanced task of recognizing surface defects. With this imbalanced sample …
extremely imbalanced task of recognizing surface defects. With this imbalanced sample …
Large selective kernel network for remote sensing object detection
Recent research on remote sensing object detection has largely focused on improving the
representation of oriented bounding boxes but has overlooked the unique prior knowledge …
representation of oriented bounding boxes but has overlooked the unique prior knowledge …
Eva-02: A visual representation for neon genesis
We launch EVA-02, a next-generation Transformer-based visual representation pre-trained
to reconstruct strong and robust language-aligned vision features via masked image …
to reconstruct strong and robust language-aligned vision features via masked image …
Hiera: A hierarchical vision transformer without the bells-and-whistles
Modern hierarchical vision transformers have added several vision-specific components in
the pursuit of supervised classification performance. While these components lead to …
the pursuit of supervised classification performance. While these components lead to …
Enhancing crop productivity and sustainability through disease identification in maize leaves: Exploiting a large dataset with an advanced vision transformer model
I Pacal - Expert Systems with Applications, 2024 - Elsevier
The timely identification of diseases in maize leaf offers several benefits such as increased
crop productivity, reduced reliance on harmful chemicals, and improved production of …
crop productivity, reduced reliance on harmful chemicals, and improved production of …
A survey of the vision transformers and their CNN-transformer based variants
Vision transformers have become popular as a possible substitute to convolutional neural
networks (CNNs) for a variety of computer vision applications. These transformers, with their …
networks (CNNs) for a variety of computer vision applications. These transformers, with their …
NTIRE 2023 challenge on stereo image super-resolution: Methods and results
In this paper, we summarize the 2nd NTIRE challenge on stereo image super-resolution
(SR) with a focus on new solutions and results. The task of the challenge is to super-resolve …
(SR) with a focus on new solutions and results. The task of the challenge is to super-resolve …
Lsknet: A foundation lightweight backbone for remote sensing
Remote sensing images pose distinct challenges for downstream tasks due to their inherent
complexity. While a considerable amount of research has been dedicated to remote sensing …
complexity. While a considerable amount of research has been dedicated to remote sensing …