Md. Amirul Islam

Orcid: 0000-0003-2508-213X

According to our database1, Md. Amirul Islam authored at least 28 papers between 2014 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2025
Quantifying and Learning Static vs. Dynamic Information in Deep Spatiotemporal Networks.
IEEE Trans. Pattern Anal. Mach. Intell., January, 2025

2024
Position, Padding and Predictions: A Deeper Look at Position Information in CNNs.
Int. J. Comput. Vis., September, 2024

Visually Guided Audio Source Separation with Meta Consistency Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023
An ensemble learning approach for anomaly detection in credit card data with imbalanced and overlapped classes.
J. Inf. Secur. Appl., November, 2023

SegMix: Co-occurrence Driven Mixup for Semantic Segmentation and Adversarial Robustness.
Int. J. Comput. Vis., March, 2023

2022
A survey of blockchain-based IoT eHealthcare: Applications, research issues, and challenges.
Internet Things, 2022

A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic Information.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Maximizing Mutual Shape Information.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021
Relative Saliency and Ranking: Models, Metrics, Data and Benchmarks.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Fibro-CoSANet: Pulmonary Fibrosis Prognosis Prediction using a Convolutional Self Attention Network.
CoRR, 2021

Bidirectional Attention Network for Monocular Depth Estimation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Shape or Texture: Understanding Discriminative Features in CNNs.
Proceedings of the 9th International Conference on Learning Representations, 2021

Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Simpler Does It: Generating Semantic Labels with Objectness Guidance.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020
Distributed Iterative Gating Networks for Semantic Segmentation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

How much Position Information Do Convolutional Neural Networks Encode?
Proceedings of the 8th International Conference on Learning Representations, 2020

Feature Binding with Category-Dependant MixUp for Semantic Segmentation and Adversarial Robustness.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019
Recurrent Iterative Gating Networks for Semantic Segmentation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

2018
Gated Feedback Refinement Network for Coarse-to-Fine Dense Semantic Image Labeling.
CoRR, 2018

Mining Periodic Patterns and Accuracy Calculation for Activity Monitoring Using RF Tag Arrays.
Proceedings of International Joint Conference on Computational Intelligence, 2018

Revisiting Salient Object Detection: Simultaneous Detection, Ranking, and Subitizing of Multiple Salient Objects.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

On the Robustness of Deep Learning Models to Universal Adversarial Attack.
Proceedings of the 15th Conference on Computer and Robot Vision, 2018

Semantics Meet Saliency: Exploring Domain Affinity and Models for Dual-Task Prediction.
Proceedings of the British Machine Vision Conference 2018, 2018

2017
Label Refinement Network for Coarse-to-Fine Semantic Segmentation.
CoRR, 2017

Gated Feedback Refinement Network for Dense Image Labeling.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Salient Object Detection using a Context-Aware Refinement Network.
Proceedings of the British Machine Vision Conference 2017, 2017

2016
Dense Image Labeling Using Deep Convolutional Neural Networks.
Proceedings of the 13th Conference on Computer and Robot Vision, 2016

2014
Workload Prediction on Google Cluster Trace.
Int. J. Grid High Perform. Comput., 2014


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