76 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Samsung Austin Semiconductor (United States)US3 papers
- Northeastern UniversityUS2 papers
- University of California San DiegoUS2 papers
- AkzoNobel (Netherlands)NL1 paper
- Alexandria UniversityEG1 paper
- Amazon (Germany)DE1 paper
- Ashoka UniversityIN1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Institute of Physics and TechnologyKZ1 paper
- Laboratoire Albert FertFR1 paper
- Microsoft (United States)US1 paper
- Moscow Institute of Physics and TechnologyRU1 paper
4 papers · 1 filter
Post-Training Piecewise Linear Quantization for Deep Neural Networks
Jun Fang, Ali Shafiee, Hamzah Abdel-Aziz +3
Quantization plays an important role in the energy-efficient deployment of deep neural networks on resource-limited devices. Post-training quantization is highly desirable since it…
TW-SMNet: Deep Multitask Learning of Tele-Wide Stereo Matching
Mostafa El-Khamy, Haoyu Ren, Xianzhi Du +1
In this paper, we introduce the problem of estimating the real world depth of elements in a scene captured by two cameras with different field of views, where the first field of vi…
Learning Sparse Low-Precision Neural Networks With Learnable Regularization
Yoojin Choi, Mostafa El-Khamy, Jungwon Lee
We consider learning deep neural networks (DNNs) that consist of low-precision weights and activations for efficient inference of fixed-point operations. In training low-precision…
Rehabilitating the ColorChecker Dataset for Illuminant Estimation
Ghalia Hemrit, Graham D. Finlayson, Arjan Gijsenij +5
In a previous work, it was shown that there is a curious problem with the benchmark ColorChecker dataset for illuminant estimation. To wit, this dataset has at least 3 different se…