Large-Scale FPGA-based Convolutional Networks

No abstract is available for this paper.

• Publication year

  2011

• Venue

  Unknown venue

• Publication date

  Unknown publication date

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1017/CBO9781139042918.020
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Efficient BackProp

  2012cited by this paper
• Neural Networks: Tricks of the Trade

  2012cited by this paper
• Hardware accelerated convolutional neural networks for synthetic vision systems

  2010cited by this paper
• Melting of Peridotite to 140 Gigapascals

  2010cited by this paper
• Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition

  2010cited by this paper
• CNP: An FPGA-based processor for Convolutional Networks

  2009cited by this paper
• Learning long‐range vision for autonomous off‐road driving

  2009cited by this paper
• Scalable learning for object detection with GPU hardware

  2009cited by this paper
• Large-scale privacy protection in Google Street View

  2009cited by this paper
• What is the best multi-stage architecture for object recognition?

  2009cited by this paper
• Learning invariant features through topographic filter maps

  2009cited by this paper
• Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations

  2009cited by this paper
• Face Detection Using GPU-Based Convolutional Neural Networks

  2009cited by this paper
• Natural Image Denoising with Convolutional Networks

  2008cited by this paper
• Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks

  2008cited by this paper
• Diastolic arrays: Throughput-driven reconfigurable computing

  2008cited by this paper
• Deep learning via semi-supervised embedding

  2008cited by this paper
• Why is Real-World Visual Object Recognition Hard?

  2008influential reference
• Nonlinear image representation using divisive normalization

  2008cited by this paper
• text Detection with Convolutional Neural Networks

  2008cited by this paper
• Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition

  2007cited by this paper
• Sparse Feature Learning for Deep Belief Networks

  2007cited by this paper
• Optimally combining a cascade of classifiers

  2006cited by this paper
• Greedy Layer-Wise Training of Deep Networks

  2006cited by this paper
• Multiclass Object Recognition with Sparse, Localized Features

  2006cited by this paper
• Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories

  2006influential reference
• Large-scale Learning with SVM and Convolutional for Generic Object Categorization

  2006cited by this paper
• Toward automatic phenotyping of developing embryos from videos

  2005cited by this paper
• Histograms of oriented gradients for human detection

  2005cited by this paper
• Object recognition with features inspired by visual cortex

  2005influential reference
• Shape matching and object recognition using low distortion correspondences

  2005cited by this paper
• Distinctive Image Features from Scale-Invariant Keypoints

  2004cited by this paper
• Learning methods for generic object recognition with invariance to pose and lighting

  2004cited by this paper
• Synergistic Face Detection and Pose Estimation with Energy-Based Models

  2004cited by this paper
• Convolutional face finder: a neural architecture for fast and robust face detection

  2004cited by this paper
• Best practices for convolutional neural networks applied to visual document analysis

  2003influential reference
• Torch

  1999cited by this paper
• Gradient-based learning applied to document recognition

  1998cited by this paper
• Sparse coding with an overcomplete basis set: a strategy employed by V1?

  1997cited by this paper
• Original approach for the localisation of objects in images

  1994cited by this paper
• A Convolutional Neural Network Hand Tracker

  1994cited by this paper
• Performance Studies of Id on the Monsoon Dataflow System

  1993influential reference
• An original approach for the localization of objects in images

  1993cited by this paper
• Perception of multiple objects - a connectionist approach

  1991cited by this paper
• Constrained neural network for unconstrained handwritten digit recognition

  1990cited by this paper
• Backpropagation Applied to Handwritten Zip Code Recognition

  1989cited by this paper
• Static Scheduling of Synchronous Data Flow Programs for Digital Signal Processing

  1989cited by this paper
• Handwritten Digit Recognition with a Back-Propagation Network

  1989cited by this paper
• Neocognitron: A new algorithm for pattern recognition tolerant of deformations and shifts in position

  1982cited by this paper
• Why systolic architectures?

  1982cited by this paper
• A preliminary architecture for a basic data-flow processor

  1974cited by this paper
• A computation model with data flow sequencing

  1968cited by this paper

• Energy-Efficient Fast Object Detection on Edge Devices for IoT Systems

  2025cites this paper
• Quantization-Based Optimization Algorithm for Hardware Implementation of Convolution Neural Networks

  2024cites this paper
• Counterexample Guided Neural Network Quantization Refinement

  2024cites this paper
• Amber: A 16-nm System-on-Chip With a Coarse- Grained Reconfigurable Array for Flexible Acceleration of Dense Linear Algebra

  2024cites this paper
• A Low-Complexity FPGA-Based Neural Network for Hand-Arm Vibrations Classification

  2023cites this paper
• CEG4N: Counter-Example Guided Neural Network Quantization Refinement

  2022cites this paper
• Design and implementation of FPGA-based hardware acceleration system for target detection

  2022cites this paper
• Convolutional Neural Network Optimized by Sparrow Optimization Algorithm

  2022cites this paper
• A Survey on Convolutional Neural Network Accelerators: GPU, FPGA and ASIC

  2022cites this paper
• A Survey on Deep Learning Models Embed Bio-Inspired Algorithms in Cardiac Disease Classification

  2022cites this paper
• The Understanding of Deep Learning: A Comprehensive Review

  2021cites this paper
• An Electro-Photonic System for Accelerating Deep Neural Networks

  2021cites this paper
• Neural network architectures using min-plus algebra for solving certain high-dimensional optimal control problems and Hamilton–Jacobi PDEs

  2021cites this paper
• Bioimage Analysis and Cell Motility

  2021cites this paper
• A Pulse-width Modulation Neuron with Continuous Activation for Processing-In-Memory Engines

  2020cites this paper
• FPT-spike: a flexible precise-time-dependent single-spike neuromorphic computing architecture

  2020cites this paper
• Condition Monitoring of Chain Sprocket Drive System Based on IoT Device and Convolutional Neural Network

  2020influential citation
• On some neural network architectures that can represent viscosity solutions of certain high dimensional Hamilton-Jacobi partial differential equations

  2020cites this paper
• Tunneling-based CMOS Floating Gate Synapse for Low Power Spike Timing Dependent Plasticity

  2020cites this paper
• An FPGA Accelerated Method for Training Feed-forward Neural Networks Using Alternating Direction Method of Multipliers and LSMR

  2020cites this paper
• A convolutional neural network accelerator for real-time underwater image recognition of autonomous underwater vehicle

  2020cites this paper
• Specialized Hardware Solutions for In-Database Analytics and Machine Learning

  2020cites this paper
• A Survey of FPGA Based CNNs Accelerators

  2020cites this paper
• A Survey of Field Programmable Gate Array-Based Convolutional Neural Network Accelerators

  2020cites this paper
• Health Monitoring of Chain Sprocket Drive System based on IoT Device and Convolutional Neural Network

  2020influential citation
• A Power-Efficient Optimizing Framework FPGA Accelerator Based on Winograd for YOLO

  2020cites this paper
• Overcoming the curse of dimensionality for some Hamilton–Jacobi partial differential equations via neural network architectures

  2019cites this paper
• FPGA-Based Accelerators of Deep Learning Networks for Learning and Classification: A Review

  2019cites this paper
• Real-Time Underwater Image Recognition with FPGA Embedded System for Convolutional Neural Network

  2019cites this paper
• Deep Learning Model for Motion Video Processing

  2019cites this paper
• Power Efficient Object Detector with an Event-Driven Camera for Moving Object Surveillance on an FPGA

  2019cites this paper
• Aging-aware Lifetime Enhancement for Memristor-based Neuromorphic Computing

  2019cites this paper
• Robust and Large-Scale Convolution through Stochastic-Based Processing without Multipliers

  2019cites this paper
• 1.1 Deep Learning Hardware: Past, Present, and Future

  2019cites this paper
• Kelp: QoS for Accelerated Machine Learning Systems

  2019cites this paper
• Lattice piecewise affine representations on convex projection regions

  2019cites this paper
• FPGA Based Implementations of RNN and CNN: A Brief Analysis

  2019cites this paper
• Digital video microscopy enhanced by deep learning

  2018cites this paper
• Memory-Efficient Probabilistic 2-D Finite Impulse Response (FIR) Filter

  2018cites this paper
• Predictive Coding Machine for Compressed Sensing and Image Denoising

  2018cites this paper
• Exploration and Tradeoffs of different Kernels in FPGA Deep Learning Applications

  2018cites this paper
• Design and Optimization of Hardware Accelerators for Deep Learning

  2018cites this paper
• A Flexible FPGA-Based Inference Architecture for Pruned Deep Neural Networks

  2018cites this paper
• Security analysis and enhancement of model compressed deep learning systems under adversarial attacks

  2018cites this paper
• Memory Optimization Techniques for FPGA based CNN Implementations

  2018cites this paper
• ORIGAMI: A Heterogeneous Split Architecture for In-Memory Acceleration of Learning

  2018influential citation
• Throughput Optimizations for FPGA-based Deep Neural Network Inference

  2018cites this paper
• Real Time Object Detection Based on FPGA with Big Data

  2018cites this paper
• Breaking the abstractions for productivity and performance in the era of specialization

  2018cites this paper
• VHDL auto-generation tool for optimized hardware acceleration of convolutional neural networks on FPGA (VGT)

  2018cites this paper
• Towards Efficient Hardware Acceleration of Deep Neural Networks on FPGA

  2018cites this paper
• Brain-inspired computing accelerated by memristor technology

  2017cites this paper
• A Survey of Neuromorphic Computing and Neural Networks in Hardware

  2017cites this paper
• Memory Architecture Optimization for Streaming Applications in High-Level Synthesis

  2017cites this paper
• PESARO 2017 Proceedings

  2017cites this paper
• A Survey on CNN and RNN Implementations

  2017cites this paper
• Rescuing memristor-based neuromorphic design with high defects

  2017cites this paper
• AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks

  2017influential citation
• Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition

  2017cites this paper
• Sketching Computation with Stochastic Processing Engines

  2017cites this paper
• FPGA-Accelerated Dense Linear Machine Learning: A Precision-Convergence Trade-Off

  2017cites this paper
• Winner takes all hashing for speeding up the training of neural networks in large class problems

  2017cites this paper
• Fast and efficient implementation of Convolutional Neural Networks on FPGA

  2017cites this paper
• Frequency Domain Acceleration of Convolutional Neural Networks on CPU-FPGA Shared Memory System

  2017cites this paper
• Running 8-bit dynamic fixed-point convolutional neural network on low-cost ARM platforms

  2017cites this paper
• Secure FPGA as a Service — Towards Secure Data Processing by Physicalizing the Cloud

  2017cites this paper
• DataFlow Supercomputing Essentials

  2017cites this paper
• System Design for Intelligent Web Services

  2017cites this paper
• Mixed Signal Neurocomputing Based on Floating-gate Memories

  2017cites this paper
• Scale-Out Acceleration for Machine Learning

  2017cites this paper
• Survey of progress in deep neural networks for resource-constrained applications

  2017cites this paper
• DataFlow Systems: From Their Origins to Future Applications in Data Analytics, Deep Learning, and the Internet of Things

  2017cites this paper
• Feature Learning and Deep Learning Architecture Survey

  2016cites this paper
• Efficient deep neural network acceleration through FPGA-based batch processing

  2016cites this paper
• Effective Quantization Methods for Recurrent Neural Networks

  2016cites this paper
• BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

  2016cites this paper
• Accelerate convolutional neural networks for binary classification via cascading cost-sensitive feature

  2016cites this paper
• Multi-fidelity matryoshka neural networks for constrained IoT devices

  2016cites this paper
• Training Bit Fully Convolutional Network for Fast Semantic Segmentation

  2016cites this paper
• DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

  2016cites this paper
• Binarized Neural Networks

  2016cites this paper
• Designing Future Warehouse-Scale Computers for Sirius, an End-to-End Voice and Vision Personal Assistant

  2016influential citation
• Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

  2016cites this paper
• Stochastic-Based Convolutional Networks with Reconfigurable Logic Fabric

  2016cites this paper
• REFRESH: REDEFINE for Face Recognition Using SURE Homogeneous Cores

  2016cites this paper
• Memory Access Optimization for Computations on Unstructured Meshes

  2016cites this paper
• Stochastic-Based Deep Convolutional Networks with Reconfigurable Logic Fabric

  2016cites this paper
• Neural Networks for Modeling and Control of Particle Accelerators

  2016cites this paper
• Accelerating Convolutional Neural Networks with Dominant Convolutional Kernel and Knowledge Pre-regression

  2016cites this paper
• Architecture for Real-Time, Low-SWaP Embedded Vision Using FPGAs

  2016cites this paper
• Local Feature Design Concepts

  2016cites this paper
• Improving Efficiency in Deep Learning for Large Scale Visual Recognition

  2016cites this paper
• Feature Learning Architecture Taxonomy and Neuroscience Background

  2016cites this paper
• Taxonomy of Feature Description Attributes

  2016cites this paper
• Going Deeper with Embedded FPGA Platform for Convolutional Neural Network

  2016cites this paper
• Deep learning for text spotting

  2015cites this paper
• Apprentissage de représentations et robotique développementale : quelques apports de l'apprentissage profond pour la robotique autonome. (Representation learning and developmental robotics : on the use of deep learning for autonomous robots)

  2015cites this paper
• Thinking Required

  2015cites this paper
• Speeding Up Neural Networks for Large Scale Classification using WTA Hashing

  2015cites this paper
• Sirius: An Open End-to-End Voice and Vision Personal Assistant and Its Implications for Future Warehouse Scale Computers

  2015cites this paper