3-D convolutional encoder-decoder network for low-dose CT via transfer learning from a 2-D trained network
Low-dose computed tomography (LDCT) has attracted major attention in the medical
imaging field, since CT-associated X-ray radiation carries health risks for patients. The …
imaging field, since CT-associated X-ray radiation carries health risks for patients. The …
Revisiting single image depth estimation: Toward higher resolution maps with accurate object boundaries
This paper considers the problem of single image depth estimation. The employment of
convolutional neural networks (CNNs) has recently brought about significant advancements …
convolutional neural networks (CNNs) has recently brought about significant advancements …
Maximum entropy scaled super pixels segmentation for multi-object detection and scene recognition via deep belief network
Recent advances in visionary technologies impacted multi-object recognition and scene
understanding. Such scene-understanding tasks are a demanding part of several …
understanding. Such scene-understanding tasks are a demanding part of several …
UAV environmental perception and autonomous obstacle avoidance: A deep learning and depth camera combined solution
Abstract In agriculture, Unmanned Aerial Vehicles (UAVs) have shown great potential for
plant protection. Uncertain obstacles randomly distributed in the unstructured farmland …
plant protection. Uncertain obstacles randomly distributed in the unstructured farmland …
Automated sustainable multi-object segmentation and recognition via modified sampling consensus and Kernel sliding perceptron
Object recognition in depth images is challenging and persistent task in machine vision,
robotics, and automation of sustainability. Object recognition tasks are a challenging part of …
robotics, and automation of sustainability. Object recognition tasks are a challenging part of …
Computer vision-based grasp pattern recognition with application to myoelectric control of dexterous hand prosthesis
Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To
achieve suitable grasps over various objects, a novel computer vision-based classification …
achieve suitable grasps over various objects, a novel computer vision-based classification …
GeoAI in terrain analysis: Enabling multi-source deep learning and data fusion for natural feature detection
In this paper we report on a new GeoAI research method which enables deep machine
learning from multi-source geospatial data for natural feature detection. In particular, a multi …
learning from multi-source geospatial data for natural feature detection. In particular, a multi …
Permeability prediction of low-resolution porous media images using autoencoder-based convolutional neural network
Permeability prediction of porous media from numerical approaches is an important
supplement for experimental measurements with the benefits of being more economical and …
supplement for experimental measurements with the benefits of being more economical and …
RGB-D-based object recognition using multimodal convolutional neural networks: a survey
Object recognition in real-world environments is one of the fundamental and key tasks in
computer vision and robotics communities. With the advanced sensing technologies and low …
computer vision and robotics communities. With the advanced sensing technologies and low …
[HTML][HTML] Marker-free surgical navigation of rod bending using a stereo neural network and augmented reality in spinal fusion
The instrumentation of spinal fusion surgeries includes pedicle screw placement and rod
implantation. While several surgical navigation approaches have been proposed for pedicle …
implantation. While several surgical navigation approaches have been proposed for pedicle …