FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review | Paper Citation Record

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This paper cites A brief review of hypernetworks in deep learning,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review A brief review of hypernetworks in deep learning,

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This paper cites Review of im- age classification algorithms based on convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Review of im- age classification algorithms based on convolutional neural networks,

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This paper cites Cnn-based object recognition and tracking system to assist visually impaired people,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Cnn-based object recognition and tracking system to assist visually impaired people,

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This paper cites Object detection via a multi-region and semantic segmentation-aware cnn model,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Object detection via a multi-region and semantic segmentation-aware cnn model,

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This paper cites Repvit: Revisiting mobile cnn from vit perspective,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Repvit: Revisiting mobile cnn from vit perspective,

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This paper cites Toward full- stack acceleration of deep convolutional neural networks on fpgas,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Toward full- stack acceleration of deep convolutional neural networks on fpgas,

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This paper cites DCP-CNN: Efficient Acceleration of CNNs With Dynamic Computing Parallelism on FPGA,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review DCP-CNN: Efficient Acceleration of CNNs With Dynamic Computing Parallelism on FPGA,

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This paper cites Morph: Flexible acceleration for 3d cnn-based video understanding,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Morph: Flexible acceleration for 3d cnn-based video understanding,

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This paper cites Accelerating CNN inference on ASICs: A survey,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Accelerating CNN inference on ASICs: A survey,

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This paper cites Comparative Analysis of CPU and GPU Profiling for Deep Learning Models.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Comparative Analysis of CPU and GPU Profiling for Deep Learning Models

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This paper cites Recent ad- vances in convolutional neural network acceleration,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Recent ad- vances in convolutional neural network acceleration,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Asic design of shared vector accelerators for multicore processors,

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This paper cites FPGA Implementation of CNN Accelerator with Pruning for ADAS Applications,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review FPGA Implementation of CNN Accelerator with Pruning for ADAS Applications,

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This paper cites Angel-eye: A complete design flow for mapping cnn onto embedded fpga,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Angel-eye: A complete design flow for mapping cnn onto embedded fpga,

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This paper cites Towards an efficient accelerator for dnn-based remote sensing image segmentation on fpgas,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Towards an efficient accelerator for dnn-based remote sensing image segmentation on fpgas,

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This paper cites An efficient fpga accelerator optimized for high throughput sparse cnn inference,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review An efficient fpga accelerator optimized for high throughput sparse cnn inference,

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This paper cites Accelerating Binarized Neural Networks: Com- parison of FPGA, CPU, GPU, and ASIC,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Accelerating Binarized Neural Networks: Com- parison of FPGA, CPU, GPU, and ASIC,

Reference 17

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This paper cites The relationship between recall and preci- sion,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review The relationship between recall and preci- sion,

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This paper cites Probabilistic extension of precision, recall, and f1 score for more thorough evaluation of classification models,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Probabilistic extension of precision, recall, and f1 score for more thorough evaluation of classification models,

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This paper cites Traffic sign detection based on improved faster r-cnn for autonomous driving,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Traffic sign detection based on improved faster r-cnn for autonomous driving,

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This paper cites Emotional speech recognition using cnn and deep learning techniques,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Emotional speech recognition using cnn and deep learning techniques,

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This paper cites Optimized fpga-based deep learning accelerator for sparse cnn using high bandwidth memory,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Optimized fpga-based deep learning accelerator for sparse cnn using high bandwidth memory,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Pflow: An end-to-end heterogeneous acceleration framework for cnn inference on fpgas,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review An overview of efficient interconnection networks for deep neural network accelerators,

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This paper cites An efficient cnn accelerator using inter-frame data reuse of videos on fpgas,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review An efficient cnn accelerator using inter-frame data reuse of videos on fpgas,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Fpga-based high-throughput cnn hardware accelerator with high computing resource utilization ratio,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Compute- efficient neural-network acceleration,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review High-performance acceleration of 2-d and 3-d cnns on fpgas using static block floating point,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Aos: An automated overclocking system for high-performance cnn accelerator through timing delay measurement on fpga,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Understanding peak floating-point performance claims,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Learning efficient convolutional networks through network slimming,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Hrank: Filter pruning using high-rank feature map,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Pruning by explaining: A novel criterion for deep neural network pruning,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Autocompress: An automatic dnn structured pruning framework for ultra-high compression rates,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Data pruning via moving-one-sample-out,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review A high- throughput and power-efficient fpga implementation of yolo cnn for object detection,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Zero-centered fixed-point quantization with iterative retraining for deep convolutional neural network-based object detectors,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Trained quantization thresh- olds for accurate and efficient fixed-point inference of deep neural networks,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Fixed point quantization of deep convolutional networks,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Fully quantized network for object detection,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Seernet: Predicting convolutional neural network feature- map sparsity through low-bit quantization,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Xnor-net: Imagenet classification using binary convolutional neural networks,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Going deeper with convolutions,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Mobilenetv2: Inverted residuals and linear bottle- necks,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Searching for mobilenetv3,

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Ghostnet: More features from cheap operations,

Reference 50

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Run, don’t walk: chasing higher flops for faster neural networks,

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This paper cites Distilling the Knowledge in a Neural Network.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Distilling the Knowledge in a Neural Network

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Densely guided knowledge distillation using multiple teacher assistants,

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This paper cites Self-mutual distillation learning for continuous sign language recognition,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Self-mutual distillation learning for continuous sign language recognition,

Reference 54

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FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Logit standardization in knowledge distillation,

Reference 55

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This paper cites Fused-layer cnn accelerators,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Fused-layer cnn accelerators,

Reference 56

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Observation 9d8b6372-6677-4b3c-abe1-487ecbf2b846 · outbound

This paper cites Accelerating convolutional neural network with fft on embedded hardware,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Accelerating convolutional neural network with fft on embedded hardware,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.972834Z

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Observation b1995d07-79ee-4fed-9a29-1aac71cb21ea · outbound

This paper cites Convolutional neural networks with fused layers applied to face recognition,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Convolutional neural networks with fused layers applied to face recognition,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.960188Z

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Observation 289b9f50-5c2f-4a69-9eb9-b44f61c6e7c3 · outbound

This paper cites Accelerating fully spectral cnns with adaptive activation functions on fpga,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Accelerating fully spectral cnns with adaptive activation functions on fpga,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.947775Z

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Observation 952fc666-c5be-43b6-be37-ffbb7b3a661a · outbound

This paper cites Fast Training of Convolutional Networks through FFTs.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Fast Training of Convolutional Networks through FFTs

Reference 60

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Observation e07cc61d-3ea0-4b59-ab4a-9688512ef89b · outbound

This paper cites Spectral representations for convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Spectral representations for convolutional neural networks,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.934566Z

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Observation b4f31438-4e0b-48fc-aae4-b3dd9af5577d · outbound

This paper cites A framework for generating high throughput cnn implementations on fpgas,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review A framework for generating high throughput cnn implementations on fpgas,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.920290Z

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Observation 204ae2b8-c306-43c2-83ce-03e0d29f67ab · outbound

This paper cites Design of fully spectral cnns for efficient fpga-based acceleration,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Design of fully spectral cnns for efficient fpga-based acceleration,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.907354Z

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Observation 87bf9f27-a7a1-433f-a6d7-a2960543fab3 · outbound

This paper cites Spectral-based convolutional neural network without multiple spatial- frequency domain switchings,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Spectral-based convolutional neural network without multiple spatial- frequency domain switchings,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.894726Z

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Observation 72153e9b-893f-43ad-89d1-914d0207e73e · outbound

This paper cites Image classification in frequency domain with 2srelu: a second harmonics superposition activation function,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Image classification in frequency domain with 2srelu: a second harmonics superposition activation function,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.880562Z

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Observation 6e1b93eb-a207-490a-b81a-57b2d3308909 · outbound

This paper cites Fast algorithms for convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Fast algorithms for convolutional neural networks,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.867362Z

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Observation d72dc407-7d29-4017-9040-e9428b5fa5e1 · outbound

This paper cites Evaluating fast algorithms for convolutional neural networks on fpgas,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Evaluating fast algorithms for convolutional neural networks on fpgas,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.854336Z

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Observation 0fa604b5-0815-4bd5-a0eb-f265da64c893 · outbound

This paper cites Stride 2 1-D, 2-D, and 3-D Winograd for convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Stride 2 1-D, 2-D, and 3-D Winograd for convolutional neural networks,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.839765Z

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Observation a7ffa0b3-bc32-4569-9002-23afc724b19a · outbound

This paper cites Loop-tiling based compiling optimization for cnn accelerators,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Loop-tiling based compiling optimization for cnn accelerators,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.826231Z

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Observation 91c06089-567c-4a17-bed5-44fc14b20015 · outbound

This paper cites An efficient loop tiling framework for convolutional neural network inference accelerators,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review An efficient loop tiling framework for convolutional neural network inference accelerators,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.812908Z

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Observation 50437886-3bd0-4fe8-98c1-b80c94cbe49b · outbound

This paper cites Optimizing cnn-based segmentation with deeply cus- tomized convolutional and deconvolutional architectures on fpga,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Optimizing cnn-based segmentation with deeply cus- tomized convolutional and deconvolutional architectures on fpga,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.799484Z

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Observation efe4fb7c-20c4-4dd9-a087-7792b5b3f9ee · outbound

This paper cites Optimizing cnn-based object detection algorithms on embedded fpga platforms,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Optimizing cnn-based object detection algorithms on embedded fpga platforms,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.785614Z

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Observation abf49b64-8c9e-45ed-b565-294258031f85 · outbound

This paper cites Efficient fpga acceleration of convolutional neural networks using logical-3d compute array,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Efficient fpga acceleration of convolutional neural networks using logical-3d compute array,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.772378Z

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Observation 3f719701-b764-4170-81df-6484e24cbce9 · outbound

This paper cites End-to-end scalable fpga accelerator for deep residual networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review End-to-end scalable fpga accelerator for deep residual networks,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.759669Z

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Observation cdbe729e-b70a-438c-b9fe-13474deeec87 · outbound

This paper cites Optimizing fpga-based accelerator design for deep convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Optimizing fpga-based accelerator design for deep convolutional neural networks,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.747073Z

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Observation e4ef6a7f-e943-41f6-9b19-38051ab71e66 · outbound

This paper cites Optimizing loop operation and dataflow in fpga accel- eration of deep convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Optimizing loop operation and dataflow in fpga accel- eration of deep convolutional neural networks,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.733659Z

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Observation 01c8bccd-df81-4ed6-9c03-432d158b24ed · outbound

This paper cites OPU: An FPGA-based overlay processor for convo- lutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review OPU: An FPGA-based overlay processor for convo- lutional neural networks,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.719820Z

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Observation 6dbfda74-f7c8-45ef-ac20-01706241bfc2 · outbound

This paper cites A design framework for generating energy-efficient accelerator on fpga toward low-level vision,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review A design framework for generating energy-efficient accelerator on fpga toward low-level vision,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.705611Z

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Observation 012e147d-d235-44fa-a19c-e1a06b32c881 · outbound

This paper cites An efficient fpga-based dilated and transposed convolutional neural network accelerator,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review An efficient fpga-based dilated and transposed convolutional neural network accelerator,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.692918Z

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Observation 230694ad-7fe4-4f5b-a269-efa119b4d35f · outbound

This paper cites A high performance fpga-based accelerator for large-scale convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review A high performance fpga-based accelerator for large-scale convolutional neural networks,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.679713Z

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Observation cb966946-78c9-4f6e-9850-07944f797a50 · outbound

This paper cites Throughput-optimized opencl-based fpga accelerator for large-scale convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Throughput-optimized opencl-based fpga accelerator for large-scale convolutional neural networks,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.665560Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7d4e4899-4d45-41e1-bda2-3272e2589efc · outbound

This paper cites A high-performance pixel-level fully pipelined hardware accelerator for neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review A high-performance pixel-level fully pipelined hardware accelerator for neural networks,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.652293Z

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Observation d2b24dab-35a0-4b14-9f2a-87cc5a7dbd42 · outbound

This paper cites Runtime programmable and memory bandwidth optimized fpga-based coprocessor for deep convolutional neural network,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Runtime programmable and memory bandwidth optimized fpga-based coprocessor for deep convolutional neural network,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.638724Z

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Observation 3391615c-e5e4-4a1b-a1a5-f4dd8cd2f789 · outbound

This paper cites Towards designing a hardware accelerator for 3d convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Towards designing a hardware accelerator for 3d convolutional neural networks,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.624196Z

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Observation ea966b76-748f-4b2a-abfc-f728b84429d8 · outbound

This paper cites Design of a low-latency general-purpose cnn hardware accelerator based on pulsed arrays on fpgas,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Design of a low-latency general-purpose cnn hardware accelerator based on pulsed arrays on fpgas,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.611163Z

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Observation e4d7f990-bc87-41a4-810e-cd3786013943 · outbound

This paper cites An fpga-based high-throughput keypoint detection acceler- ator using convolutional neural network for mobile robot applications,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review An fpga-based high-throughput keypoint detection acceler- ator using convolutional neural network for mobile robot applications,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.598233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f63620a2-bc01-4e17-8b19-4d6eea7b0562 · outbound

This paper cites System services for reconfigurable hardware accel- eration in mobile devices,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review System services for reconfigurable hardware accel- eration in mobile devices,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.584251Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 59eaea42-d504-4684-b424-3854818adc6f · outbound

This paper cites Hardware resource and computational density efficient cnn accelerator design based on fpga,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Hardware resource and computational density efficient cnn accelerator design based on fpga,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.570713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c011cf72-69a8-4c15-bcc2-6abfd4c3112a · outbound

This paper cites An optimization of im2col, an important method of cnns, based on continuous address access,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review An optimization of im2col, an important method of cnns, based on continuous address access,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.557247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 09e5797f-fae3-427e-91f7-187780c0ebcd · outbound

This paper cites Double MAC on a DSP: Boosting the performance of convolutional neural networks on FP- GAs,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Double MAC on a DSP: Boosting the performance of convolutional neural networks on FP- GAs,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.542527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 735ef629-5653-4044-a8ac-117d4ec5ca0b · outbound

This paper cites fpgaConvNet: A framework for mapping convolutional neural networks on FPGAs,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review fpgaConvNet: A framework for mapping convolutional neural networks on FPGAs,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.528371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3616c88f-be2e-43bc-b387-02f08c966012 · outbound

This paper cites Latency-driven design for fpga-based convolutional neural net- works,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Latency-driven design for fpga-based convolutional neural net- works,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.515501Z

Source-reported events for the cited work

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Observation f73ecbca-ec09-4c73-b618-93caef6a9e9f · outbound

This paper cites fpgaConvNet: Mapping regular and irregular convolutional neural networks on FPGAs,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review fpgaConvNet: Mapping regular and irregular convolutional neural networks on FPGAs,

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.502044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3b14923f-23f1-478f-8510-94f291336a3c · outbound

This paper cites Snowflake: An efficient hardware accelerator for convolutional neural networks,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Snowflake: An efficient hardware accelerator for convolutional neural networks,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.487966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ec8d22df-c6a5-4262-ad82-7c4c409998d5 · outbound

This paper cites f-CNNx: A toolflow for mapping multiple convolutional neural networks on FPGAs,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review f-CNNx: A toolflow for mapping multiple convolutional neural networks on FPGAs,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.474472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a8282897-0585-41ce-a369-a97a57166d00 · outbound

This paper cites FMM-X3D: FPGA-based modeling and mapping of X3D for Human Action Recognition,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review FMM-X3D: FPGA-based modeling and mapping of X3D for Human Action Recognition,

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.459980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0fe72ba5-d069-4590-8a74-a407c86363ca · outbound

This paper cites Harflow3d: A latency-oriented 3d-cnn accelerator toolflow for har on fpga devices,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Harflow3d: A latency-oriented 3d-cnn accelerator toolflow for har on fpga devices,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.446621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e948927a-246f-4551-ac41-9671b1c40652 · outbound

This paper cites fpgaHART: A toolflow for throughput-oriented acceleration of 3D CNNs for HAR onto FPGAs,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review fpgaHART: A toolflow for throughput-oriented acceleration of 3D CNNs for HAR onto FPGAs,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.431510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f8e74e54-88f3-4806-81eb-bfd13ba35a14 · outbound

This paper cites Samo: Opti- mised mapping of convolutional neural networks to streaming archi- tectures,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Samo: Opti- mised mapping of convolutional neural networks to streaming archi- tectures,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.416283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e0ff5f6-105a-4ca1-8f19-d0a68f88e5d0 · outbound

This paper cites Adaptive memetic computing for evolutionary multiobjective optimization,.

FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review Adaptive memetic computing for evolutionary multiobjective optimization,

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:51.401814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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