statistiche ricercatore

Nome	#
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead	172
An Updated Survey of Efficient Hardware Architectures for Accelerating Deep Convolutional Neural Networks	131
A Fast Design Space Exploration Framework for the Deep Learning Accelerators: Work-in-Progress	106
NASCaps: A Framework for Neural Architecture Search to Optimize the Accuracy and Hardware Efficiency of Convolutional Capsule Networks	90
Q-CapsNets: A Specialized Framework for Quantizing Capsule Networks	80
FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule Networks	77
Enabling Capsule Networks at the Edge through Approximate Softmax and Squash Operations	60
Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tile	37
NLCMAP: A Framework for the Efficient Mapping of Non-Linear Convolutional Neural Networks on FPGA Accelerators	36
Techniques and Optimization Strategies for Efficient Hardware Acceleration of Neural Networks: Tap-Wisely-Quantized Winograd Algorithm and Capsule Networks	29
RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks	24
Totale	842

	Totale	Lug	Ago	Sett	Ott	Nov	Dic	Gen	Feb	Mar	Apr	Mag	Giu
2020/2021	233	8	2	5	25	21	25	20	34	22	44	20	7
2021/2022	216	7	17	8	17	11	18	4	7	17	18	40	52
2022/2023	282	15	32	31	40	48	36	22	12	20	3	6	17
2023/2024	111	8	23	6	12	11	13	4	12	7	11	4	0
Totale													842

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