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Direct inference on compressive measurements using convolutional neural networks

https://doi.org/10.1109/icip.2016.7532691

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cpa.20124openalex-snapshot

Stable signal recovery from incomplete and inaccurate measurements

inferredcites →https://doi.org/10.1007/978-3-642-15549-9_10openalex-snapshot

Compressive Acquisition of Dynamic Scenes

inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot

ImageNet Large Scale Visual Recognition Challenge

inferredcites →https://doi.org/10.1088/2040-8978/17/6/065701openalex-snapshot

Compressive image acquisition and classification via secant projections

inferredcites →https://doi.org/10.1090/conm/026/737400openalex-snapshot

Extensions of Lipschitz mappings into a Hilbert space

inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot

Gradient-based learning applied to document recognition

inferredcites →https://doi.org/10.1109/cvpr.2014.220openalex-snapshot

DeepFace: Closing the Gap to Human-Level Performance in Face Verification

inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot

Going deeper with convolutions

inferredcites →https://doi.org/10.1109/cvprw.2015.7301371openalex-snapshot

Reconstruction-free inference on compressive measurements

inferredcites →https://doi.org/10.1109/icassp.2006.1660651openalex-snapshot

Sparse Signal Detection from Incoherent Projections

inferredcites →https://doi.org/10.1109/icip.2006.312577openalex-snapshot

An Architecture for Compressive Imaging

inferredcites →https://doi.org/10.1109/msp.2007.914731openalex-snapshot

An Introduction To Compressive Sampling [A sensing/sampling paradigm that goes against the common knowledge in data acquisition]

inferredcites →https://doi.org/10.1109/taes.2009.5259191openalex-snapshot

Object Specific Image Reconstruction using a Compressive Sensing Architecture for Application in Surveillance Systems

inferredcites →https://doi.org/10.1109/tit.2006.871582openalex-snapshot

Compressed sensing

inferredcites →https://doi.org/10.1109/tit.2007.909108openalex-snapshot

Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit

inferredcites →https://doi.org/10.1109/tpami.2014.2375215openalex-snapshot

Zero-Aliasing Correlation Filters for Object Recognition

inferredcites →https://doi.org/10.1109/tpami.2015.2469288openalex-snapshot

Reconstruction-Free Action Inference from Compressive Imagers

inferredcites →https://doi.org/10.1117/12.714460openalex-snapshot

The smashed filter for compressive classification and target recognition

inferredcites →https://doi.org/10.1137/s1064827596304010openalex-snapshot

Atomic Decomposition by Basis Pursuit

inferredcites →https://doi.org/10.1145/2647868.2654889openalex-snapshot

Caffe

inferredcites →https://doi.org/10.1145/3065386openalex-snapshot

ImageNet classification with deep convolutional neural networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Literature Review

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Online reconstruction-free single-pixel image classification

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Enabling on-device classification of ECG with compressed learning for health IoT

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Deep Compressive Sensing for Visual Privacy Protection in FlatCam Imaging

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Compressed Classification from Learned Measurements

inferred← citeshttps://doi.org/10.1109/icip.2018.8451445openalex-snapshot

CS-VQA: Visual Question Answering with Compressively Sensed Images

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Classification Guided Deep Convolutional Network for Compressed Sensing

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Rank-Regularized Measurement Operators for Compressive Imaging

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Compressed Learning in MCA Architectures to Tolerate Malicious Noise

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Algorithmic Enablers for Compact Neural Network Topology Hardware Design: Review and Trends

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Adversarial Defense using Memristors and Input Preprocessing *

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Remote Multilinear Compressive Learning With Adaptive Compression

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Image Recognition Based on Compressive Imaging and Optimal Feature Selection

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Compressed Sensing Approach for Physiological Signals: A Review

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A Tri-Mode Compressed Analytics Engine for Low-Power AF Detection With On-Demand EKG Reconstruction

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Ship Detection Based on Compressive Sensing Measurements of Optical Remote Sensing Scenes

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Design of compressive imaging masks for human activity perception based on binary convolutional neural network

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CS-Fnet: A Compressive Sampling Frequency Neural Network for Simultaneous Image Compression and Recognition

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Compressive Classification from Single Pixel Measurements Via Deep Learning

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Data Adaptive Compressed Sensing using deep neural network for Image recognition

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CLRGAN: Compressed Learning and Reconstruction Using GAN for Alzheimer’s Disease

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Accurate Face Recognition on Highly Compressed Samples

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Privacy-Preserving Face Recognition and Verification With Lensless Camera

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CTIS-Net: A Neural Network Architecture for Compressed Learning Based on Computed Tomography Imaging Spectrometers

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Secure Sampling and Low-Overhead Compressive Analysis by Linear Transformation

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单像素高效感知方法概述

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Multilinear Compressive Learning with Prior Knowledge

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Deep Learning Techniques for Compressive Sensing-Based Reconstruction and Inference -- A Ubiquitous Systems Perspective

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Deep Learning Based Target Tracking and Classification Directly in Compressive Measurement for Low Quality Videos

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Target Detection and Classification Improvements using Contrast Enhanced 16-bit Infrared Videos

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Target Detection and Classification Performance Enhancement using Super-Resolution Infrared Videos

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Practical Approaches to Target Detection in Long Range and Low Quality Infrared Videos

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