Search
Search Results
-
GFSCompNet: remote sensing image compression network based on global feature-assisted segmentation
The proliferation of remote sensing image data in recent years has posed a pressing need for efficient compression techniques due to constrained...
-
Attention-based variable-size feature compression module for edge inference
Artificial intelligence has made significant breakthroughs in many fields, especially with the broad deployment of edge devices, which provides...
-
Dual-branch spectral–spatial feature extraction network for multispectral image compression
The advent of the information age and the continuous development of spectrum imaging technologies have both triggered an explosion of multispectral...
-
A Hybrid Model for Video Compression Based on the Fusion of Feature Compression Framework and Multi-object Tracking Network
This paper proposes a video compression algorithm which bases on the combination of feature compression framework and multi-object tracking network....
-
A Single Image High-Perception Super-Resolution Reconstruction Method Based on Multi-layer Feature Fusion Model with Adaptive Compression and Parameter Tuning
We propose a simple image high-perception super-resolution reconstruction method based on multi-layer feature fusion model with adaptive compression...
-
A differential privacy-preserving federated learning scheme with predictive maintenance of wind turbines based on deep learning for feature compression and anomaly detection with state assessment
The transport and supply of traditional energy have been greatly affected, which has attracted the attention of countries worldwide and has become an...
-
Compression-resistant backdoor attack against deep neural networks
In recent years, a number of backdoor attacks against deep neural networks (DNN) have been proposed. In this paper, we reveal that backdoor attacks...
-
Structured pruning via feature channels similarity and mutual learning for convolutional neural network compression
The development of convolutional neural network (CNN) have been hindered in resource-constrained devices due to its large memory and calculation. To...
-
Compression through extraction of learned parameters from images in de-correlated image space
Image compression is a class of algorithms that reduces the storage space requirement for a digital image. Lossy image compression techniques achieve...
-
Mixture autoregressive and spectral attention network for multispectral image compression based on variational autoencoder
Multispectral images, with their unique three-dimensional characteristics, require specialized spatial-spectral feature extraction modules to achieve...
-
FANs: fully attentional networks for image compression
We propose a fully attentional networks model and achieve excellent results on top of both large-scale datasets and small-scale datasets to use as a...
-
Multispectral Image Compression Based on Prediction Network
Multispectral images have rich spatial and spectral information which contain great application superiority. Therefore, effective compression of...
-
Robust median filtering forensics using texture feature and deep fully connected network
Image forensics researchers have recently focused a lot of attention on detection of median filtering that is used to hide evidence of image forgery...
-
Sentence Compression as a Supervised Learning with a Rich Feature Space
We present a novel supervised approach to sentence compression, based on classification and removal of word sequences generated from subtrees of the...
-
AFMPM: adaptive feature map pruning method based on feature distillation
Feature distillation is a technology that uses the middle layer feature map of the teacher network as knowledge to transfer to the students. The...
-
Membership inference attacks against compression models
With the rapid development of artificial intelligence, privacy threats are already getting the spotlight. One of the most common privacy threats is...
-
Deep learning-assisted medical image compression challenges and opportunities: systematic review
Over the preceding decade, there has been a discernible surge in the prominence of artificial intelligence, marked by the development of various...
-
Prediction on compression indicators of clay soils using XGBoost with Bayesian optimization
The determination of the compressibility of clay soils is a major concern during the design and construction of geotechnical engineering projects....
-
Deep Video Compression Based on 3D Convolution Artifacts Removal and Attention Compression Module
Most research of video compression focuses on how to effectively extract the information between frames and use this information for the subsequent...
-
EARN: toward efficient and robust JPEG compression artifact reduction
JPEG is one of the most widely used lossy image compression algorithms, but artifacts are generated during compression. Various artifact reduction...
