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IE-Net: Information-Enhanced Binary Neural Networks for Accurate Classification

https://doi.org/10.3390/electronics11060937

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-01216-8_20openalex-snapshot

TBN: Convolutional Neural Network with Ternary Inputs and Binary Weights

inferredcites →https://doi.org/10.1007/978-3-030-01237-3_23openalex-snapshot

LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks

inferredcites →https://doi.org/10.1007/978-3-030-01267-0_44openalex-snapshot

Bi-Real Net: Enhancing the Performance of 1-Bit CNNs with Improved Representational Capability and Advanced Training Algorithm

inferredcites →https://doi.org/10.1007/978-3-030-58568-6_9openalex-snapshot

ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_32openalex-snapshot

XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot

ImageNet: A large-scale hierarchical image database

inferredcites →https://doi.org/10.1109/cvpr.2015.7298965openalex-snapshot

Fully convolutional networks for semantic segmentation

inferredcites →https://doi.org/10.1109/cvpr.2018.00716openalex-snapshot

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

inferredcites →https://doi.org/10.1109/cvpr.2019.00050openalex-snapshot

Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation

inferredcites →https://doi.org/10.1109/cvpr.2019.00280openalex-snapshot

Circulant Binary Convolutional Networks: Enhancing the Performance of 1-Bit DCNNs With Circulant Back Propagation

inferredcites →https://doi.org/10.1109/cvpr.2019.00506openalex-snapshot

Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit?

inferredcites →https://doi.org/10.1109/cvpr.2019.01167openalex-snapshot

Regularizing Activation Distribution for Training Binarized Deep Networks

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00232openalex-snapshot

Forward and Backward Information Retention for Accurate Binary Neural Networks

inferredcites →https://doi.org/10.1109/cvpr46437.2021.00563openalex-snapshot

Layer-wise Searching for 1-bit Detectors

inferredcites →https://doi.org/10.1109/iccv.2017.282openalex-snapshot

Performance Guaranteed Network Acceleration via High-Order Residual Quantization

inferredcites →https://doi.org/10.1109/iccv.2019.00495openalex-snapshot

Differentiable Soft Quantization: Bridging Full-Precision and Low-Bit Neural Networks

inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

inferredcites →https://doi.org/10.1609/aaai.v33i01.33018344openalex-snapshot

Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation

inferredcites →https://doi.org/10.3390/electronics10040396openalex-snapshot

Optimising Hardware Accelerated Neural Networks with Quantisation and a Knowledge Distillation Evolutionary Algorithm

inferredcites →https://doi.org/10.3390/electronics10161943openalex-snapshot

Increasing Information Entropy of Both Weights and Activations for the Binary Neural Networks

inferredcites →https://doi.org/10.3390/electronics10222823openalex-snapshot

Integer-Only CNNs with 4 Bit Weights and Bit-Shift Quantization Scales at Full-Precision Accuracy

inferredcites →https://doi.org/10.3390/electronics11010011openalex-snapshot

Real-Time LiDAR Point Cloud Semantic Segmentation for Autonomous Driving

inferredcites →https://doi.org/10.3390/electronics11040540openalex-snapshot

Smish: A Novel Activation Function for Deep Learning Methods

inferredcites →https://doi.org/10.3390/electronics11040575openalex-snapshot

A Light-Weight CNN for Object Detection with Sparse Model and Knowledge Distillation

inferredcites →https://doi.org/10.48550/arxiv.1510.00149openalex-snapshot

Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

inferredcites →https://doi.org/10.48550/arxiv.1511.00363openalex-snapshot

BinaryConnect: Training Deep Neural Networks with binary weights during propagations

inferredcites →https://doi.org/10.48550/arxiv.1711.11294openalex-snapshot

Towards Accurate Binary Convolutional Neural Network

inferredcites →https://doi.org/10.48550/arxiv.2009.08695openalex-snapshot

Searching for Low-Bit Weights in Quantized Neural Networks

What points at this work

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

inferred← citeshttps://doi.org/10.1016/j.imavis.2025.105646openalex-snapshot

Distribution-modulated binary neural network for image classification

inferred← citeshttps://doi.org/10.1038/s41598-023-46785-7openalex-snapshot

Features extraction from multi-spectral remote sensing images based on multi-threshold binarization

inferred← citeshttps://doi.org/10.1049/ell2.70496openalex-snapshot

Binary Pyramid Self‐Supervised Reconstruction Network: Lightweight Recognition of Active Jamming for PD Radar

inferred← citeshttps://doi.org/10.1109/access.2023.3258360openalex-snapshot

A Systematic Literature Review on Binary Neural Networks

inferred← citeshttps://doi.org/10.1109/access.2023.3296429openalex-snapshot

Integrated Imager and 3.22 μs/Kernel-Latency All-Digital In-Imager Global-Parallel Binary Convolutional Neural Network Accelerator for Image Processing

inferred← citeshttps://doi.org/10.1109/ecai58194.2023.10193930openalex-snapshot

Arrhythmia Classifier Based on Ultra-Lightweight Binary Neural Network

inferred← citeshttps://doi.org/10.1109/iccv51070.2023.00520openalex-snapshot

BiViT: Extremely Compressed Binary Vision Transformers

inferred← citeshttps://doi.org/10.1109/iceca55336.2022.10009197openalex-snapshot

A TinyML based Residual Binarized Neural Network for real-time Image Classification

inferred← citeshttps://doi.org/10.1109/taes.2026.3660940openalex-snapshot

LCO-BNN: A Lightweight Collaborative Optimization Binary Neural Network for Radar Jamming Recognition

inferred← citeshttps://doi.org/10.1109/tcsi.2025.3611134openalex-snapshot

A High-Energy-Efficiency Lightweight BNN Accelerator for Arrhythmia Detection

inferred← citeshttps://doi.org/10.1109/tcsvt.2023.3288572openalex-snapshot

Binarizing by Classification: Is Soft Function Really Necessary?

inferred← citeshttps://doi.org/10.1142/s0218348x25400262openalex-snapshot

HYBRID DEEP LEARNING ALGORITHM FOR FRACTAL HUMAN ACTIVITY RECOGNITION USING SMART IOT-EDGE-CLOUD CONTINUUM

inferred← citeshttps://doi.org/10.1145/3745034.3745062openalex-snapshot

Ultra-Lightweight BNN for Real-Time EEG Emotion Recognition on Wearable Devices

inferred← citeshttps://doi.org/10.15407/vidbir2023.51.062openalex-snapshot

Classification of remote sensing images based on multi-threshold binarization

inferred← citeshttps://doi.org/10.1609/aaai.v38i14.29505openalex-snapshot

BVT-IMA: Binary Vision Transformer with Information-Modified Attention

inferred← citeshttps://doi.org/10.17586/2226-1494-2023-23-5-946-954openalex-snapshot

Method for testing NLP models with text adversarial examples

inferred← citeshttps://doi.org/10.3390/electronics11121852openalex-snapshot

A Lightweight Method for Vehicle Classification Based on Improved Binarized Convolutional Neural Network

inferred← citeshttps://doi.org/10.3390/electronics13020266openalex-snapshot

Efficient FPGA Binary Neural Network Architecture for Image Super-Resolution

inferred← citeshttps://doi.org/10.3390/s23229254openalex-snapshot

Binary Neural Networks in FPGAs: Architectures, Tool Flows and Hardware Comparisons

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