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07/14/2023
Multiplicative update rules for accelerating deep learning training and increasing robustness
Even nowadays, where Deep Learning (DL) has achieved state-of-the-art pe...
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06/15/2023
Deep Learning for Energy Time-Series Analysis and Forecasting
Energy time-series analysis describes the process of analyzing past ener...
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02/12/2023
Variational Voxel Pseudo Image Tracking
Uncertainty estimation is an important task for critical problems, such ...
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09/27/2022
A Novel Dataset for Evaluating and Alleviating Domain Shift for Human Detection in Agricultural Fields
In this paper we evaluate the impact of domain shift on human detection ...
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06/06/2022
VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images
In this paper, we propose a novel voxel-based 3D single object tracking ...
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03/16/2022
Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate Modeling
Deep learning methods have been employed in gravitational-wave astronomy...
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08/26/2021
Efficient training of lightweight neural networks using Online Self-Acquired Knowledge Distillation
Knowledge Distillation has been established as a highly promising approa...
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08/26/2021
Quadratic mutual information regularization in real-time deep CNN models
In this paper, regularized lightweight deep convolutional neural network...
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08/25/2021
Semantic Scene Segmentation for Robotics Applications
Semantic scene segmentation plays a critical role in a wide range of rob...
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07/09/2021
Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling
Recently, artificial neural networks have been gaining momentum in the f...
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05/25/2020
Attention-based Neural Bag-of-Features Learning for Sequence Data
In this paper, we propose 2D-Attention (2DA), a generic attention formul...
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05/02/2020
Heterogeneous Knowledge Distillation using Information Flow Modeling
Knowledge Distillation (KD) methods are capable of transferring the know...
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06/11/2019
Bag of Color Features For Color Constancy
In this paper, we propose a novel color constancy approach, called Bag o...
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02/21/2019
Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data
Deep Learning (DL) models can be used to tackle time series analysis tas...
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01/24/2019
Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data
Time series forecasting is a crucial component of many important applica...
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01/16/2019
Deep Supervised Hashing leveraging Quadratic Spherical Mutual Information for Content-based Image Retrieval
Several deep supervised hashing techniques have been proposed to allow f...
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11/30/2018
Style Decomposition for Improved Neural Style Transfer
Universal Neural Style Transfer (NST) methods are capable of performing ...
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11/13/2018
Interactive dimensionality reduction using similarity projections
Recent advances in machine learning allow us to analyze and describe the...
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11/05/2018
Decoding Generic Visual Representations From Human Brain Activity using Machine Learning
Among the most impressive recent applications of neural decoding is the ...
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10/23/2018
Using Deep Learning for price prediction by exploiting stationary limit order book features
The recent surge in Deep Learning (DL) research of the past decade has s...
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09/19/2018
Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data
Forecasting the movements of stock prices is one the most challenging pr...
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03/28/2018
Probabilistic Knowledge Transfer for Deep Representation Learning
Knowledge Transfer (KT) techniques tackle the problem of transferring th...
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07/25/2017
Learning Bag-of-Features Pooling for Deep Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are well established models capable...
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06/18/2017