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Global Instance Relation Distillation for convolutional neural network compression
Previous instance-relation knowledge distillation methods transfer structural relations between instances from the heavy teacher network to the...
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Spectral–Spatial Feature Completely Separated Extraction with Tensor CNN for Multispectral Image Compression
Considering the rich spectral and spatial information of multispectral image, a learned multispectral image compression method named spectral-spatial...
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Iterative shrinkage thresholding-based anti-multi-noise compression perceptual image reconstruction network
Telemedicine imaging services usually require wireless transmission of a large number of medical images MRI/CT, etc., in the network, which are...
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An efficient Moving object, Encryption, Compression and Interpolation technique for video steganography
Video steganography approach has been widely used to preserve the secret information while transmitting through the internet. This approach has...
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Feature Reduction
Image information has already been reduced when constructing the feature vector from primary image features. The reduction is based on heuristic...
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Audio Compression Using Quantum Neural Network
Data compression is a common feature of current information processing and has a broad range of uses. Audio compression is critical in database...
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Multi-file dynamic compression method based on classification algorithm in DNA storage
AbstractThe exponential growth in data volume has necessitated the adoption of alternative storage solutions, and DNA storage stands out as the most...
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End-to-End Image Compression Through Machine Semantics
With the increasing demand for AI automated analysis, machine semantics have replaced signals as a new focus in visual information compression. In...
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Efficient feature transform module
Deep neural networks have achieved impressive success in various applications, but they face challenges when deployed on mobile devices due to...
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Channel-Stationary Entropy Model for Multispectral Image Compression
Multispectral image have a large number of complex features. The existing network models have good compression performance for multispectral image,...
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End-to-end optimized image compression with the frequency-oriented transform
Image compression constitutes a significant challenge amid the era of information explosion. Recent studies employing deep learning methods have...
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A survey of model compression strategies for object detection
Deep neural networks (DNNs) have achieved great success in many object detection tasks. However, such DNNS-based large object detection models are...
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Strengthening attention: knowledge distillation via cross-layer feature fusion for image classification
Deep learning has achieved great success in computer vision, especially in image classification tasks. How to improve the generalization ability and...
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A new hybrid feature reduction method by using MCMSTClustering algorithm with various feature projection methods: a case study on sleep disorder diagnosis
In the machine learning area, having a large number of irrelevant or less relevant features to the result of the dataset can reduce classification...
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FCNet: a deep neural network based on multi-channel feature cascading for image denoising
A lot of current work based on convolutional neural networks (CNNs) has fetched good visual results on AWGN (additive white Gaussian noise) removal....
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Memristor-based storage system with convolutional autoencoder-based image compression network
The exponential growth of various complex images is putting tremendous pressure on storage systems. Here, we propose a memristor-based storage system...
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A Brief Analysis on Video Compression and Deduplication Models Using Video Steganography with Optimised Feature Extraction Techniques for Integrity Preservation
Increased Internet use has brought about a greater focus on security in recent years. The daily rate of data exchange is increasing as Internet usage...
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Network Pruning via Feature Shift Minimization
Channel pruning is widely used to reduce the complexity of deep network models. Recent pruning methods usually identify which parts of the network to...
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Multistage feature fusion knowledge distillation
Generally, the recognition performance of lightweight models is often lower than that of large models. Knowledge distillation, by teaching a student...
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Fatigue life prediction of concrete under cyclic compression based on gradient boosting regression tree
With the development of reinforced concrete bridges, the fatigue problem of concrete has attracted extensive attention. Failure occurs when concrete...
