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03/27/2023
LEURN: Learning Explainable Univariate Rules with Neural Networks
In this paper, we propose LEURN: a neural network architecture that lear...
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10/11/2022
Neural Networks are Decision Trees
In this manuscript, we show that any neural network having piece-wise li...
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02/16/2021
A Sub-band Approach to Deep Denoising Wavelet Networks and a Frequency-adaptive Loss for Perceptual Quality
In this paper, we propose two contributions to neural network based deno...
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05/24/2019
A Compression Objective and a Cycle Loss for Neural Image Compression
In this manuscript we propose two objective terms for neural image compr...
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05/10/2019
Compressing Weight-updates for Image Artifacts Removal Neural Networks
In this paper, we present a novel approach for fine-tuning a decoder-sid...
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05/03/2019
Compressibility Loss for Neural Network Weights
In this paper we apply a compressibility loss that enables learning high...
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05/28/2018
Block-optimized Variable Bit Rate Neural Image Compression
In this work, we propose an end-to-end block-based auto-encoder system f...
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02/08/2018
Saliency-Enhanced Robust Visual Tracking
Discrete correlation filter (DCF) based trackers have shown considerable...
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02/01/2018
Clustering and Unsupervised Anomaly Detection with L2 Normalized Deep Auto-Encoder Representations
Clustering is essential to many tasks in pattern recognition and compute...
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01/24/2018
A Theoretical Investigation of Graph Degree as an Unsupervised Normality Measure
For a graph representation of a dataset, a straightforward normality mea...
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12/27/2017
Memory-Efficient Deep Salient Object Segmentation Networks on Gridized Superpixels
Computer vision algorithms with pixel-wise labeling tasks, such as seman...
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03/21/2017
INTEL-TUT Dataset for Camera Invariant Color Constancy Research
In this paper, we provide a novel dataset designed for camera invariant ...
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09/13/2016
