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Forrest Iandola
Forrest Iandola
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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5 MB model size
FN Iandola, S Han, MW Moskewicz, K Ashraf, WJ Dally, K Keutzer
arXiv preprint arXiv:1602.07360, 2016
101422016
From captions to visual concepts and back
H Fang, S Gupta, F Iandola, RK Srivastava, L Deng, P Dollár, J Gao, X He, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2015
16622015
Densenet: Implementing efficient convnet descriptor pyramids.
F Iandola, M Moskewicz, S Karayev, R Girshick, T Darrell, K Keutzer
arXiv preprint arXiv:1404.1869, 2014
11302014
SqueezeDet: Unified, small, low power fully convolutional neural networks for real-time object detection for autonomous driving
B Wu, F Iandola, PH Jin, K Keutzer
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
7542017
Deformable part models are convolutional neural networks
R Girshick, F Iandola, T Darrell, J Malik
Proceedings of the IEEE conference on Computer Vision and Pattern …, 2015
5782015
FireCaffe: near-linear acceleration of deep neural network training on compute clusters
FN Iandola, MW Moskewicz, K Ashraf, K Keutzer
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
3902016
Deformable part descriptors for fine-grained recognition and attribute prediction
N Zhang, R Farrell, F Iandola, T Darrell
Proceedings of the IEEE International Conference on Computer Vision, 729-736, 2013
2962013
How to scale distributed deep learning?
PH Jin, Q Yuan, F Iandola, K Keutzer
NIPS Workshops, 2016
1612016
SqueezeBERT: What can computer vision teach NLP about efficient neural networks?
FN Iandola, AE Shaw, R Krishna, KW Keutzer
EMNLP SustaiNLP Workshop, 2020
1222020
DeepLogo: Hitting logo recognition with the deep neural network hammer
FN Iandola, A Shen, P Gao, K Keutzer
arXiv preprint arXiv:1510.02131, 2015
982015
Data synthesis for autonomous control systems
FN Iandola, DB MacMillen, A Shen, HS Sidhu, PJ Jain
US Patent 10,678,244, 2020
922020
Discovery of semantic similarities between images and text
J Gao, X He, S Gupta, GG Zweig, F Iandola, L Deng, H Fang, MA Mitchell, ...
US Patent 9,836,671, 2017
912017
SqueezeNAS: Fast neural architecture search for faster semantic segmentation
A Shaw, D Hunter, F Iandola, S Sidhu
Proceedings of the IEEE International Conference on Computer Vision …, 2019
862019
SqueezeNet: AlexNet-level accuracy with 50× fewer parameters and
FN Iandola, S Han, MW Moskewicz, K Ashraf, WJ Dally, K Keutzer
5MB model size [J], 2016
812016
Shallow networks for high-accuracy road object-detection
K Ashraf, B Wu, FN Iandola, MW Moskewicz, K Keutzer
arXiv preprint arXiv:1606.01561, 2016
672016
Small neural nets are beautiful: enabling embedded systems with small deep-neural-network architectures
F Iandola, K Keutzer
Proceedings of the twelfth IEEE/ACM/IFIP international conference on …, 2017
632017
Efficientsam: Leveraged masked image pretraining for efficient segment anything
Y Xiong, B Varadarajan, L Wu, X Xiang, F Xiao, C Zhu, X Dai, D Wang, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
612024
SqueezeNet: AlexNet-level accuracy with 50× fewer parameters and< 0.5 MB model size. 2016
FN Iandola, S Han, MW Moskewicz, K Ashraf, WJ Dally, K Keutzer
arXiv preprint arXiv:1602.07360, 0
52
Multi-channel sensor simulation for autonomous control systems
FN Iandola, DB MacMillen, A Shen, HS Sidhu, DP Tomasello, RN Phadte, ...
US Patent 11,157,014, 2021
492021
Optimal load management system for aircraft electric power distribution
M Maasoumy, P Nuzzo, F Iandola, M Kamgarpour, ...
52nd IEEE Conference on Decision and Control, 2939-2945, 2013
472013
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