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Adapting Neural Networks at Runtime: Current Trends in At-Runtime Optimizations for Deep Learning
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ECO: Efficient Convolutional Network for Online Video Understanding
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Action Search: Spotting Actions in Videos and Its Application to Temporal Action Localization
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SkipNet: Learning Dynamic Routing in Convolutional Networks
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Dynamic Channel and Layer Gating in Convolutional Neural Networks
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Spatially Adaptive Inference with Stochastic Feature Sampling and Interpolation
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S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search
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AR-Net: Adaptive Frame Resolution for Efficient Action Recognition
inferredcites →https://doi.org/10.1007/978-3-030-58583-9_15openalex-snapshot
Channel Selection Using Gumbel Softmax
inferredcites →https://doi.org/10.1007/978-3-030-88013-2_34openalex-snapshot
Dynamic Runtime Feature Map Pruning
inferredcites →https://doi.org/10.1007/978-3-030-92307-5_65openalex-snapshot
Dynamic Convolution Pruning Using Pooling Characteristic in Convolution Neural Networks
inferredcites →https://doi.org/10.1007/978-3-031-12748-9_4openalex-snapshot
Dynamic Pruning for Parsimonious CNN Inference on Embedded Systems
inferredcites →https://doi.org/10.1007/978-3-031-19803-8_20openalex-snapshot
Multi-Exit Semantic Segmentation Networks
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Adaptive Token Sampling for Efficient Vision Transformers
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Leaving Some Stones Unturned: Dynamic Feature Prioritization for Activity Detection in Streaming Video
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Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
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The cascading neural network: building the Internet of Smart Things
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Why Should We Add Early Exits to Neural Networks?
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A two-step machine learning approach for dynamic model selection: A case study on a micro milling process
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Similarity caching in large-scale image retrieval
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Finding decision jumps in text classification
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Deep learning for image-based cancer detection and diagnosis − A survey
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Self-supervised feature-gate coupling for dynamic network pruning
inferredcites →https://doi.org/10.1016/j.patrec.2021.08.013openalex-snapshot
Exploration of block-wise dynamic sparseness
inferredcites →https://doi.org/10.1016/j.pmcj.2022.101594openalex-snapshot
Memory-aware and context-aware multi-DNN inference on the edge
inferredcites →https://doi.org/10.1016/s0898-1221(96)90463-0openalex-snapshot
Advances in neural information processing systems 7
inferredcites →https://doi.org/10.1109/aicas51828.2021.9458463openalex-snapshot
TempDiff: Temporal Difference-Based Feature Map-Level Sparsity Induction in CNNs with <4% Memory Overhead
inferredcites →https://doi.org/10.1109/asp-dac52403.2022.9712483openalex-snapshot
Dynamic CNN Accelerator Supporting Efficient Filter Generator with Kernel Enhancement and Online Channel Pruning
inferredcites →https://doi.org/10.1109/bigdata52589.2021.9671948openalex-snapshot
Optimal Branch Location for Cost-effective Inference on Branchynet
inferredcites →https://doi.org/10.1109/codesisss.2015.7331375openalex-snapshot
Big/little deep neural network for ultra low power inference
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Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
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End-to-End Learning of Action Detection from Frame Glimpses in Videos
inferredcites →https://doi.org/10.1109/cvpr.2017.11openalex-snapshot
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
inferredcites →https://doi.org/10.1109/cvpr.2017.194openalex-snapshot
Spatially Adaptive Computation Time for Residual Networks
inferredcites →https://doi.org/10.1109/cvpr.2017.205openalex-snapshot
More is Less: A More Complicated Network with Less Inference Complexity
inferredcites →https://doi.org/10.1109/cvpr.2017.476openalex-snapshot
Look Closer to See Better: Recurrent Attention Convolutional Neural Network for Fine-Grained Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.684openalex-snapshot
Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade
inferredcites →https://doi.org/10.1109/cvpr.2018.00166openalex-snapshot
Recurrent Residual Module for Fast Inference in Videos
inferredcites →https://doi.org/10.1109/cvpr.2018.00558openalex-snapshot
Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition
inferredcites →https://doi.org/10.1109/cvpr.2018.00827openalex-snapshot
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00908openalex-snapshot
SBNet: Sparse Blocks Network for Fast Inference
inferredcites →https://doi.org/10.1109/cvpr.2018.00919openalex-snapshot
BlockDrop: Dynamic Inference Paths in Residual Networks
inferredcites →https://doi.org/10.1109/cvpr.2019.00137openalex-snapshot
AdaFrame: Adaptive Frame Selection for Fast Video Recognition
inferredcites →https://doi.org/10.1109/cvpr.2019.00236openalex-snapshot
ELASTIC: Improving CNNs With Dynamic Scaling Policies
inferredcites →https://doi.org/10.1109/cvpr.2019.00529openalex-snapshot
Dynamic Recursive Neural Network
inferredcites →https://doi.org/10.1109/cvpr.2019.00939openalex-snapshot
You Look Twice: GaterNet for Dynamic Filter Selection in CNNs
inferredcites →https://doi.org/10.1109/cvpr.2019.01147openalex-snapshot
SeerNet: Predicting Convolutional Neural Network Feature-Map Sparsity Through Low-Bit Quantization
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00222openalex-snapshot
AdaBits: Neural Network Quantization With Adaptive Bit-Widths
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00239openalex-snapshot
Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00244openalex-snapshot
Resolution Adaptive Networks for Efficient Inference
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00858openalex-snapshot
Learning Dynamic Routing for Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00982openalex-snapshot
PointRend: Image Segmentation As Rendering
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01155openalex-snapshot
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01427openalex-snapshot
ILFO: Adversarial Attack on Adaptive Neural Networks
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00238openalex-snapshot
Differentiable Patch Selection for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00609openalex-snapshot
2D or not 2D? Adaptive 3D Convolution Selection for Efficient Video Recognition
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00850openalex-snapshot
Dynamic Slimmable Network
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01535openalex-snapshot
FrameExit: Conditional Early Exiting for Efficient Video Recognition
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01054openalex-snapshot
A-ViT: Adaptive Tokens for Efficient Vision Transformer
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01199openalex-snapshot
AdaViT: Adaptive Vision Transformers for Efficient Image Recognition
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01213openalex-snapshot
Fire Together Wire Together: A Dynamic Pruning Approach with Self-Supervised Mask Prediction
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01217openalex-snapshot
DeltaCNN: End-to-End CNN Inference of Sparse Frame Differences in Videos
inferredcites →https://doi.org/10.1109/cvprw50498.2020.00346openalex-snapshot
Dynamic Inference: A New Approach Toward Efficient Video Action Recognition
inferredcites →https://doi.org/10.1109/cvprw53098.2021.00347openalex-snapshot
Dynamic-OFA: Runtime DNN Architecture Switching for Performance Scaling on Heterogeneous Embedded Platforms
inferredcites →https://doi.org/10.1109/icassp39728.2021.9414505openalex-snapshot
Dynamic Sparsity Neural Networks for Automatic Speech Recognition
inferredcites →https://doi.org/10.1109/iccd.2017.49openalex-snapshot
A Dynamic Deep Neural Network Design for Efficient Workload Allocation in Edge Computing
inferredcites →https://doi.org/10.1109/iccv.2015.314openalex-snapshot
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition
inferredcites →https://doi.org/10.1109/iccv.2017.424openalex-snapshot
Attention-Aware Deep Reinforcement Learning for Video Face Recognition
inferredcites →https://doi.org/10.1109/iccv.2019.00189openalex-snapshot
Universally Slimmable Networks and Improved Training Techniques
inferredcites →https://doi.org/10.1109/iccv.2019.00198openalex-snapshot
Improved Techniques for Training Adaptive Deep Networks
inferredcites →https://doi.org/10.1109/iccv.2019.00632openalex-snapshot
Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition
inferredcites →https://doi.org/10.1109/iccv48922.2021.00038openalex-snapshot
Differentiable Dynamic Wirings for Neural Networks
inferredcites →https://doi.org/10.1109/iccv48922.2021.00511openalex-snapshot
BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online Policies
inferredcites →https://doi.org/10.1109/iccv48922.2021.00728openalex-snapshot
Dynamic Network Quantization for Efficient Video Inference
inferredcites →https://doi.org/10.1109/iccv48922.2021.01594openalex-snapshot
Adaptive Focus for Efficient Video Recognition
inferredcites →https://doi.org/10.1109/iccvw.2017.145openalex-snapshot
Dynamic Computational Time for Visual Attention
inferredcites →https://doi.org/10.1109/icdcs.2017.226openalex-snapshot
Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices
inferredcites →https://doi.org/10.1109/icdcs.2017.94openalex-snapshot
Cachier: Edge-Caching for Recognition Applications
inferredcites →https://doi.org/10.1109/icdcs47774.2020.00085openalex-snapshot
Continuous, Real-Time Object Detection on Mobile Devices without Offloading
inferredcites →https://doi.org/10.1109/icpr.2016.7900006openalex-snapshot
BranchyNet: Fast inference via early exiting from deep neural networks
inferredcites →https://doi.org/10.1109/icpr48806.2021.9413153openalex-snapshot
ActionSpotter: Deep Reinforcement Learning Framework for Temporal Action Spotting in Videos
inferredcites →https://doi.org/10.1109/ijcnn55064.2022.9892578openalex-snapshot
Delta Activation Layer exploits temporal sparsity for efficient embedded video processing
inferredcites →https://doi.org/10.1109/infocom48880.2022.9796677openalex-snapshot
Accelerating Deep Learning Classification with Error-controlled Approximate-key Caching
inferredcites →https://doi.org/10.1109/infocom48880.2022.9796984openalex-snapshot
FlexPatch: Fast and Accurate Object Detection for On-device High-Resolution Live Video Analytics
inferredcites →https://doi.org/10.1109/iotdi54339.2022.00010openalex-snapshot
DeepScale: Online Frame Size Adaptation for Multi-object Tracking on Smart Cameras and Edge Servers
inferredcites →https://doi.org/10.1109/isca.2018.00051openalex-snapshot
EVA²: Exploiting Temporal Redundancy in Live Computer Vision
inferredcites →https://doi.org/10.1109/isca.2018.00061openalex-snapshot
SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/iscas.2017.8050797openalex-snapshot
PredictiveNet: An energy-efficient convolutional neural network via zero prediction
inferredcites →https://doi.org/10.1109/jiot.2020.2986015openalex-snapshot
Intelligent Cooperative Edge Computing in Internet of Things
inferredcites →https://doi.org/10.1109/jproc.2021.3119950openalex-snapshot
Edge Intelligence: Empowering Intelligence to the Edge of Network
inferredcites →https://doi.org/10.1109/jstsp.2020.2979669openalex-snapshot
Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference
inferredcites →https://doi.org/10.1109/micro50266.2020.00063openalex-snapshot
VR-DANN: Real-Time Video Recognition via Decoder-Assisted Neural Network Acceleration
inferredcites →https://doi.org/10.1109/mlcad48534.2019.9142052openalex-snapshot
Incremental Training and Group Convolution Pruning for Runtime DNN Performance Scaling on Heterogeneous Embedded Platforms
inferredcites →https://doi.org/10.1109/mnet.001.1800506openalex-snapshot
Boomerang: On-Demand Cooperative Deep Neural Network Inference for Edge Intelligence on the Industrial Internet of Things
inferredcites →https://doi.org/10.1109/rsdha54838.2021.00010openalex-snapshot
ELIχR: Eliminating Computation Redundancy in CNN-Based Video Processing
inferredcites →https://doi.org/10.1109/sec.2018.00019openalex-snapshot
Bandwidth-Efficient Live Video Analytics for Drones Via Edge Computing
inferredcites →https://doi.org/10.1109/sec50012.2020.00014openalex-snapshot
FlexDNN: Input-Adaptive On-Device Deep Learning for Efficient Mobile Vision
inferredcites →https://doi.org/10.1109/sec50012.2020.00016openalex-snapshot
Spatula: Efficient cross-camera video analytics on large camera networks
inferredcites →https://doi.org/10.1109/sec50012.2020.00041openalex-snapshot
CHA: A Caching Framework for Home-based Voice Assistant Systems
inferredcites →https://doi.org/10.1109/tc.2020.2970413openalex-snapshot
A Fast Filtering Mechanism to Improve Efficiency of Large-Scale Video Analytics
inferredcites →https://doi.org/10.1109/tcad.2017.2681075openalex-snapshot
FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition
inferredcites →https://doi.org/10.1109/tcad.2021.3136815openalex-snapshot
Similarity-Aware CNN for Efficient Video Recognition at the Edge
inferredcites →https://doi.org/10.1109/tcsvt.2019.2903421openalex-snapshot
CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams
inferredcites →https://doi.org/10.1109/tetc.2021.3056031openalex-snapshot
Fully Dynamic Inference with Deep Neural Networks
inferredcites →https://doi.org/10.1109/tii.2018.2842821openalex-snapshot
Deep Learning for Smart Industry: Efficient Manufacture Inspection System With Fog Computing
inferredcites →https://doi.org/10.1109/tip.2020.3007826openalex-snapshot
Dynamic Sampling Networks for Efficient Action Recognition in Videos
inferredcites →https://doi.org/10.1109/tip.2023.3246792openalex-snapshot
Dynamic Slimmable Denoising Network
inferredcites →https://doi.org/10.1109/tmc.2021.3139940openalex-snapshot
MVPose: Realtime Multi-Person Pose Estimation Using Motion Vector on Mobile Devices
inferredcites →https://doi.org/10.1109/tnet.2019.2936939openalex-snapshot
cDeepArch: A Compact Deep Neural Network Architecture for Mobile Sensing
inferredcites →https://doi.org/10.1109/tpami.2021.3117837openalex-snapshot
Dynamic Neural Networks: A Survey
inferredcites →https://doi.org/10.1109/tpami.2022.3196959openalex-snapshot
Glance and Focus Networks for Dynamic Visual Recognition
inferredcites →https://doi.org/10.1109/tpami.2023.3263826openalex-snapshot
Dynamic Spatial Sparsification for Efficient Vision Transformers and Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/wacv.2019.00114openalex-snapshot
Pixel-Wise Attentional Gating for Scene Parsing
inferredcites →https://doi.org/10.1109/wacv48630.2021.00363openalex-snapshot
Dynamic Routing Networks
inferredcites →https://doi.org/10.1117/12.2537799openalex-snapshot
Dynamic-stride-net: deep convolutional neural network with dynamic stride
inferredcites →https://doi.org/10.1145/1458469.1458473openalex-snapshot
A metric cache for similarity search
inferredcites →https://doi.org/10.1145/1516360.1516450openalex-snapshot
Caching content-based queries for robust and efficient image retrieval
inferredcites →https://doi.org/10.1145/2934583.2934615openalex-snapshot
Energy-Efficient Adaptive Classifier Design for Mobile Systems
inferredcites →https://doi.org/10.1145/2968456.2968458openalex-snapshot
Runtime configurable deep neural networks for energy-accuracy trade-off
inferredcites →https://doi.org/10.1145/3007192openalex-snapshot
Energy-Efficient and Improved Image Recognition with Conditional Deep Learning
inferredcites →https://doi.org/10.1145/3132847.3132947openalex-snapshot
Length Adaptive Recurrent Model for Text Classification
inferredcites →https://doi.org/10.1145/3210240.3210337openalex-snapshot
On-Demand Deep Model Compression for Mobile Devices
inferredcites →https://doi.org/10.1145/3240765.3240796openalex-snapshot
Designing adaptive neural networks for energy-constrained image classification
inferredcites →https://doi.org/10.1145/3299710.3211336openalex-snapshot
Adaptive deep learning model selection on embedded systems
inferredcites →https://doi.org/10.1145/3300061.3300116openalex-snapshot
Edge Assisted Real-time Object Detection for Mobile Augmented Reality
inferredcites →https://doi.org/10.1145/3352460.3358283openalex-snapshot
Boosting the Performance of CNN Accelerators with Dynamic Fine-Grained Channel Gating
inferredcites →https://doi.org/10.1145/3366622.3368147openalex-snapshot
Challenges and Opportunities of DNN Model Execution Caching
inferredcites →https://doi.org/10.1145/3412382.3458272openalex-snapshot
Efficient Execution of Deep Neural Networks on Mobile Devices with NPU
inferredcites →https://doi.org/10.1145/3469116.3470012openalex-snapshot
Adaptive Inference through Early-Exit Networks
inferredcites →https://doi.org/10.1145/3484946openalex-snapshot
Toward Efficient and Adaptive Design of Video Detection System with Deep Neural Networks
inferredcites →https://doi.org/10.1145/3527155openalex-snapshot
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
inferredcites →https://doi.org/10.1145/3534580openalex-snapshot
Template Matching Based Early Exit CNN for Energy-efficient Myocardial Infarction Detection on Low-power Wearable Devices
inferredcites →https://doi.org/10.1145/3564663openalex-snapshot
Survey: Exploiting Data Redundancy for Optimization of Deep Learning
inferredcites →https://doi.org/10.1149/1945-7111/ab67a8openalex-snapshot
Review—Deep Learning Methods for Sensor Based Predictive Maintenance and Future Perspectives for Electrochemical Sensors
inferredcites →https://doi.org/10.1609/aaai.v32i1.11630openalex-snapshot
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-Offs by Selective Execution
inferredcites →https://doi.org/10.1609/aaai.v33i01.33013812openalex-snapshot
Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing
inferredcites →https://doi.org/10.1609/aaai.v34i04.5764openalex-snapshot
InstaNAS: Instance-Aware Neural Architecture Search
inferredcites →https://doi.org/10.1609/aaai.v34i04.6025openalex-snapshot
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference
inferredcites →https://doi.org/10.1609/aaai.v35i12.17286openalex-snapshot
Any-Precision Deep Neural Networks
inferredcites →https://doi.org/10.17863/cam.13057openalex-snapshot
Decision Forests, Convolutional Networks and the Models in-Between
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.204openalex-snapshot
DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference
inferredcites →https://doi.org/10.18653/v1/2021.eacl-main.8openalex-snapshot
BERxiT: Early Exiting for BERT with Better Fine-Tuning and Extension to Regression
inferredcites →https://doi.org/10.18653/v1/d18-1474openalex-snapshot
Speed Reading: Learning to Read ForBackward via Shuttle
inferredcites →https://doi.org/10.18653/v1/p19-1032openalex-snapshot
Adaptive Attention Span in Transformers
inferredcites →https://doi.org/10.23919/date48585.2020.9116235openalex-snapshot
Optimising Resource Management for Embedded Machine Learning
inferredcites →https://doi.org/10.23919/date54114.2022.9774567openalex-snapshot
Once For All Skip: Efficient Adaptive Deep Neural Networks
inferredcites →https://doi.org/10.24963/ijcai.2018/98openalex-snapshot
Watching a Small Portion could be as Good as Watching All: Towards Efficient Video Classification
inferredcites →https://doi.org/10.4218/etrij.2020-0112openalex-snapshot
Performance analysis of local exit for distributed deep neural networks over cloud and edge computing
inferredcites →https://doi.org/10.48550/arxiv.1603.08983openalex-snapshot
Adaptive Computation Time for Recurrent Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1610.07647openalex-snapshot
Learning to Reason With Adaptive Computation
inferredcites →https://doi.org/10.48550/arxiv.1611.06188openalex-snapshot
Variable Computation in Recurrent Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1703.02529openalex-snapshot
NoScope: Optimizing Neural Network Queries over Video at Scale
inferredcites →https://doi.org/10.48550/arxiv.1711.02085openalex-snapshot
Neural Speed Reading via Skim-RNN
inferredcites →https://doi.org/10.48550/arxiv.1804.10123openalex-snapshot
IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification
inferredcites →https://doi.org/10.48550/arxiv.1807.02609openalex-snapshot
Anytime Neural Prediction via Slicing Networks Vertically
inferredcites →https://doi.org/10.48550/arxiv.1808.04752openalex-snapshot
A Survey on Methods and Theories of Quantized Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1810.05331openalex-snapshot
Dynamic Channel Pruning: Feature Boosting and Suppression
inferredcites →https://doi.org/10.48550/arxiv.1907.06627openalex-snapshot
Batch-Shaping for Learning Conditional Channel Gated Networks
inferredcites →https://doi.org/10.48550/arxiv.2002.10025openalex-snapshot
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference
inferredcites →https://doi.org/10.48550/arxiv.2004.02178openalex-snapshot
FastBERT: a Self-distilling BERT with Adaptive Inference Time
inferredcites →https://doi.org/10.48550/arxiv.2007.01793openalex-snapshot
CacheNet: A Model Caching Framework for Deep Learning Inference on the Edge
inferredcites →https://doi.org/10.48550/arxiv.2010.02432openalex-snapshot
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
inferredcites →https://doi.org/10.48550/arxiv.2010.07003openalex-snapshot
Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search
inferredcites →https://doi.org/10.48550/arxiv.2104.07358openalex-snapshot
Adaptive Sparse Transformer for Multilingual Translation
inferredcites →https://doi.org/10.48550/arxiv.2109.10060openalex-snapshot
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