A survey of deep convolutional neural networks applied for prediction of plant leaf diseases
In the modern era, deep learning techniques have emerged as powerful tools in image
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …
An updated survey of efficient hardware architectures for accelerating deep convolutional neural networks
Deep Neural Networks (DNNs) are nowadays a common practice in most of the Artificial
Intelligence (AI) applications. Their ability to go beyond human precision has made these …
Intelligence (AI) applications. Their ability to go beyond human precision has made these …
Automatic bunch detection in white grape varieties using YOLOv3, YOLOv4, and YOLOv5 deep learning algorithms
Over the last few years, several Convolutional Neural Networks for object detection have
been proposed, characterised by different accuracy and speed. In viticulture, yield …
been proposed, characterised by different accuracy and speed. In viticulture, yield …
Deep 3D convolutional encoder networks with shortcuts for multiscale feature integration applied to multiple sclerosis lesion segmentation
We propose a novel segmentation approach based on deep 3D convolutional encoder
networks with shortcut connections and apply it to the segmentation of multiple sclerosis …
networks with shortcut connections and apply it to the segmentation of multiple sclerosis …
[HTML][HTML] Drone-YOLO: an efficient neural network method for target detection in drone images
Z Zhang - Drones, 2023 - mdpi.com
Object detection in unmanned aerial vehicle (UAV) imagery is a meaningful foundation in
various research domains. However, UAV imagery poses unique challenges, including …
various research domains. However, UAV imagery poses unique challenges, including …
Deep learning framework for vehicle and pedestrian detection in rural roads on an embedded GPU
Object detection, one of the most fundamental and challenging problems in computer vision.
Nowadays some dedicated embedded systems have emerged as a powerful strategy for …
Nowadays some dedicated embedded systems have emerged as a powerful strategy for …
A deep learning framework performance evaluation to use YOLO in Nvidia Jetson platform
DJ Shin, JJ Kim - Applied Sciences, 2022 - mdpi.com
Deep learning-based object detection technology can efficiently infer results by utilizing
graphics processing units (GPU). However, when using general deep learning frameworks …
graphics processing units (GPU). However, when using general deep learning frameworks …
[HTML][HTML] Sustainable machine vision for industry 4.0: a comprehensive review of convolutional neural networks and hardware accelerators in computer vision
M Hussain - AI, 2024 - mdpi.com
As manifestations of Industry 4.0. become visible across various applications, one key and
opportune area of development are quality inspection processes and defect detection. Over …
opportune area of development are quality inspection processes and defect detection. Over …
Advancements in microprocessor architecture for ubiquitous AI—An overview on history, evolution, and upcoming challenges in AI implementation
Artificial intelligence (AI) has successfully made its way into contemporary industrial sectors
such as automobiles, defense, industrial automation 4.0, healthcare technologies …
such as automobiles, defense, industrial automation 4.0, healthcare technologies …
An automatic premature ventricular contraction recognition system based on imbalanced dataset and pre-trained residual network using transfer learning on ECG …
The development of automatic monitoring and diagnosis systems for cardiac patients over
the internet has been facilitated by recent advancements in wearable sensor devices from …
the internet has been facilitated by recent advancements in wearable sensor devices from …