Review of multi-view 3D object recognition methods based on deep learning
Abstract Three-dimensional (3D) object recognition is widely used in automated driving,
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …
Image inpainting based on deep learning: A review
Z Qin, Q Zeng, Y Zong, F Xu - Displays, 2021 - Elsevier
Image inpainting aims to restore the pixel features of damaged parts in incomplete image
and plays a key role in many computer vision tasks. Image inpainting technology based on …
and plays a key role in many computer vision tasks. Image inpainting technology based on …
Understanding adversarial attacks on deep learning based medical image analysis systems
Deep neural networks (DNNs) have become popular for medical image analysis tasks like
cancer diagnosis and lesion detection. However, a recent study demonstrates that medical …
cancer diagnosis and lesion detection. However, a recent study demonstrates that medical …
Voxel-based three-view hybrid parallel network for 3D object classification
Three-dimensional models are widely used in the fields of multimedia, computer graphics,
virtual reality, entertainment, design, and manufacturing because of the rich information that …
virtual reality, entertainment, design, and manufacturing because of the rich information that …
Enhanced generative adversarial network for extremely imbalanced fault diagnosis of rotating machine
Fault diagnosis is the key procedure to ensure the stability and reliability of mechanical
equipment operation. Recent works show that deep learning-based methods outperform …
equipment operation. Recent works show that deep learning-based methods outperform …
Hashing nets for hashing: A quantized deep learning to hash framework for remote sensing image retrieval
Fast and accurate remote sensing image retrieval from large data archives has been an
important research topic in the remote sensing research literature. Recently, hashing-based …
important research topic in the remote sensing research literature. Recently, hashing-based …
Learning EEG topographical representation for classification via convolutional neural network
Electroencephalography (EEG) topographical representation (ETR) can monitor regional
brain activities and is emerging as a successful technique for causally exploring cortical …
brain activities and is emerging as a successful technique for causally exploring cortical …
Deep hashing learning for visual and semantic retrieval of remote sensing images
Driven by the urgent demand for managing remote sensing big data, large-scale remote
sensing image retrieval (RSIR) attracts increasing attention in the remote sensing field. In …
sensing image retrieval (RSIR) attracts increasing attention in the remote sensing field. In …
Learning binary code for fast nearest subspace search
Subspace is widely used to represent objects under different viewpoints, illuminations,
identities, and more. Due to the growing amount and dimensionality of visual contents, fast …
identities, and more. Due to the growing amount and dimensionality of visual contents, fast …
Online latent semantic hashing for cross-media retrieval
Hashing based cross-media method has been become an increasingly popular technique in
facilitating large-scale multimedia retrieval task, owing to its effectiveness and efficiency …
facilitating large-scale multimedia retrieval task, owing to its effectiveness and efficiency …