no code implementations • 27 Jul 2020 • Pedro Morgado, Yunsheng Li, Jose Costa Pereira, Mohammad Saberian, Nuno Vasconcelos
The use of a fixed set of proxies (weights of the CNN classification layer) is proposed to eliminate this ambiguity, and a procedure to design proxy sets that are nearly optimal for both classification and hashing is introduced.
no code implementations • 17 Oct 2019 • Mohammad Saberian, Pablo Delgado, Yves Raimond
In this paper we propose a method to build a neural network that is similar to an ensemble of decision trees.
no code implementations • NeurIPS 2016 • Mohammad Saberian, Jose Costa Pereira, Can Xu, Jian Yang, Nuno Nvasconcelos
We argue that the intermediate mapping, e. g. boosting predictor, is preserving the discriminant aspects of the data and by controlling the dimension of this mapping it is possible to achieve discriminant low dimensional representations for the data.
no code implementations • ICCV 2015 • Zhaowei Cai, Mohammad Saberian, Nuno Vasconcelos
CompACT cascades are shown to seek an optimal trade-off between accuracy and complexity by pushing features of higher complexity to the later cascade stages, where only a few difficult candidate patches remain to be classified.
Ranked #26 on Pedestrian Detection on Caltech
3 code implementations • 10 Feb 2015 • Sachin Sudhakar Farfade, Mohammad Saberian, Li-Jia Li
In this paper we propose Deep Dense Face Detector (DDFD), a method that does not require pose/landmark annotation and is able to detect faces in a wide range of orientations using a single model based on deep convolutional neural networks.
no code implementations • NeurIPS 2014 • Mohammad Saberian, Nuno Vasconcelos
SBBoost is a boosting algorithm for maximization of this margin.