Results 101 to 110 of about 229,861 (318)
2017 International Conference on 3D Vision (3DV), 2017 In this paper, we consider convolutional neural networks operating on sparse inputs with an application to depth upsampling from sparse laser scan data. First, we show that traditional convolutional networks perform poorly when applied to sparse data even when the location of missing data is provided to the network. To overcome this problem, we propose
Jonas Uhrig +5 more
openaire +3 more sources
Zuckerberg exclusive broadcast interview on CNN\u27s ʺNew Dayʺ about internet.org launch
, 2013 CNN\u27s New Day interviews Mark Zuckerberg about the internet.org launch in 2013https://epublications.marquette.edu/zuckerberg_files_videos/1069/thumbnail ...
CNN
core
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
Exploration of Machine Learning Algorithms and Class Imbalance Handling on Plant Disease Detection
Journal of Applied Informatics and ComputingPlant leaf diseases pose a significant threat to agricultural productivity, necessitating accurate and efficient identification systems for timely intervention.
Ervin Aditya, Ajie Kusuma Wardhana
doaj +1 more source
Table detection ANN model based on Faster R-CNN
, 2020 Table detection ANN model based on Faster R-CNN trained on three datasets ICDAR 2017, Marmot and ...
Andrey Mikhailov (8613789)
core +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
Advanced Robotics Research, EarlyView.This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
Detection of corona faults in switchgear by ssing 1D-CNN, LSTM, and 1D-CNN-LSTM methods
, 2023 The damaging effects of corona faults have made them a major concern in metal-clad switchgear, requiring extreme caution during operation. Corona faults are also the primary cause of flashovers in medium-voltage metal-clad electrical equipment.
SK Tiong (17274427) +8 more
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Solid Harmonic Wavelet Bispectrum for Image Analysis
Advanced Science, EarlyView.The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
UAV-Based Structural Damage Mapping: A Review
ISPRS International Journal of Geo-Information, 2019 Structural disaster damage detection and characterization is one of the oldest remote sensing challenges, and the utility of virtually every type of active and passive sensor deployed on various air- and spaceborne platforms has been assessed.
Norman Kerle +4 more
doaj +1 more source
CoRR, 2018 CNNs have made a tremendous impact on the field of computer vision in the last several years. The main component of any CNN architecture is the convolution operation, which is translation invariant by design. However, location in itself can be an important cue.
Zhenyi Wang 0001, Olga Veksler
openaire +2 more sources