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07/09/2023
Latent Graph Attention for Enhanced Spatial Context
Global contexts in images are quite valuable in image-to-image translati...
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03/03/2023
Data-Efficient Training of CNNs and Transformers with Coresets: A Stability Perspective
Coreset selection is among the most effective ways to reduce the trainin...
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01/31/2023
Patch Gradient Descent: Training Neural Networks on Very Large Images
Traditional CNN models are trained and tested on relatively low resoluti...
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01/16/2023
On Using Deep Learning Proxies as Forward Models in Deep Learning Problems
Physics-based optimization problems are generally very time-consuming, e...
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11/24/2022
On designing light-weight object trackers through network pruning: Use CNNs or transformers?
Object trackers deployed on low-power devices need to be light-weight, h...
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11/12/2022
MixBin: Towards Budgeted Binarization
Binarization has proven to be amongst the most effective ways of neural ...
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06/25/2022
UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images
Convolutional neural network (CNN) approaches available in the current l...
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06/03/2022
Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning
Gradient based meta-learning methods are prone to overfit on the meta-tr...
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11/28/2021
Implicit Equivariance in Convolutional Networks
Convolutional Neural Networks(CNN) are inherently equivariant under tran...
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02/14/2021
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Structured pruning methods are among the effective strategies for extrac...
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06/30/2020
Tackling Occlusion in Siamese Tracking with Structured Dropouts
Occlusion is one of the most difficult challenges in object tracking to ...
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06/23/2020
Calibrated Adversarial Refinement for Multimodal Semantic Segmentation
Ambiguities in images or unsystematic annotation can lead to multiple va...
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04/11/2020
Automated and Accurate Geometry Extraction and Shape Optimization of 3D Topology Optimization Results
Designs generated by density-based topology optimization (TO) exhibit ja...
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10/19/2019
Tracking-Assisted Segmentation of Biological Cells
U-Net and its variants have been demonstrated to work sufficiently well ...
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08/05/2019
Model Decay in Long-Term Tracking
Updating the tracker model with adverse bounding box predictions adds an...
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07/07/2019
Stacked autoencoders based machine learning for noise reduction and signal reconstruction in geophysical data
Autoencoders are neural network formulations where the input and output ...
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01/22/2019
Unsupervised Automated Event Detection using an Iterative Clustering based Segmentation Approach
A class of vision problems, less commonly studied, consists of detecting...
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11/24/2018
Design and analysis adaptivity in multi-resolution topology optimization
Multiresolution topology optimization (MTO) methods involve decoupling o...
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05/01/2018
Deep Autoassociative Neural Networks for Noise Reduction in Seismic data
Machine learning is currently a trending topic in various science and en...
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04/19/2018