Results 31 to 40 of about 93,854 (214)
Livestock detection in aerial images using a fully convolutional network
Computational Visual Media, 2019 In order to accurately count the number of animals grazing on grassland, we present a livestock detection algorithm using modified versions of U-net and Google Inception-v4 net. This method works well to detect dense and touching instances.
Liang Han, Pin Tao, Ralph R. Martin
doaj +1 more source
Buildings, 2022 Deep learning technology, such as fully convolutional networks (FCNs), have shown competitive performance in the automatic extraction of buildings from high-resolution aerial images (HRAIs).
Wenzhuo Zhang +6 more
doaj +1 more source
Arthritis Care &Research, Accepted Article.Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source
Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis
Arthritis Care &Research, EarlyView.Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling +4 more
wiley +1 more source
A MANY-TO-MANY FULLY CONVOLUTIONAL RECURRENT NETWORK FOR MULTITEMPORAL CROP RECOGNITION [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Recently, recurrent neural networks have been proposed for crop mapping from multitemporal remote sensing data. Most of these proposals have been designed and tested in temperate regions, where a single harvest per season is the rule. In tropical regions,
J. A. Chamorro +4 more
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Fully Convolutional Neural Network for Vehicle Speed and Emergency-Brake Prediction
Sensors, 2023 Ego-vehicle state prediction represents a complex and challenging problem for self-driving and autonomous vehicles. Sensorial information and on-board cameras are used in perception-based solutions in order to understand the state of the vehicle and the ...
Razvan Itu, Radu Danescu
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INVESTIGATING FULLY CONVOLUTIONAL NETWORK TO SEMANTIC LABELLING OF BATHYMETRIC POINT CLOUD [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 The benefit of autonomous vehicles in hydrography is largely based on the ability of these platforms to carry out survey campaigns in a fully autonomous manner. One solution is to have real-time processing onboard the survey vessel.
S. Daniel, V. Dupont
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dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Accurate Pixel-Wise Skin Segmentation Using Shallow Fully Convolutional Neural Network
IEEE Access, 2020 Skin segmentation plays an important role in human activity recognition, video surveillance, hand gesture identification, face detection, human tracking and robotic surgery.
Komal Minhas +7 more
doaj +1 more source
Advanced Functional Materials, EarlyView.A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar +9 more
wiley +1 more source