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  • University of Nevada Reno
  • Reno, Nevada, USA

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aminul-huq/README.md

Education

  • P.hD. in Computer Science & Engineering, University of Nevada Reno. (onGoing)
  • M.Sc. in Computer Science & Engineering, Tshinghua University, 2021.
  • B.Sc. in Computer Science & Engineering, Rajshahi University of Engineering & Technology, 2017.

Recent News

  • October 2023. Corn Abnormality Dataset has been released
  • August 2023. 1 Paper accepted to the 18th ISVC

Publications

  • Identification of Abnormality in Maize Plants From UAV Images Using Deep Learning Approaches
    Aminul Huq, Dimitris Zermas & George Bebis. ISVC.

Invited Talks

  • International Symposium on Visual Computing
    "Identification of Abnormality in Maize Plants From UAV Images Using Deep Learning Approaches"
    18th October, 2023
  • Computational Modeling and Analysis Core Meet and Greet
    "Computer Vision Applications Using Deep Leaning"
    14th December, 2023

Experience

  • Graduate Research Assistant
    Spring 23 - OnGoing
  • Graduate Teaching Assistant
    Fall 23 - Ongoing Course: Image Processing, Pattern Recognition
  • Lecturer
    Brac University, 2018-2022(on Leave)

Pinned Loading

  1. Adversarial-Examples-For-Audio-Data Public

    Repo for papers to read on adversarial attack and defense techniques in the audio domain.

    35 4

  2. CNN-RNN-for-Multiclass-Classification-on-SST-dataset Public

    PyTorch implementation of multi-class sentiment classification on SST dataset using CNN and RNN.

    Jupyter Notebook 6

  3. CVAE_pytorch Public

    CVAE implementation on MNIST dataset using PyTorch

    Python

  4. DeepFool Public

    PyTorch implementation of DeepFool adversarial attack.

    Jupyter Notebook 7 3

  5. WideResNet_MNIST_Adversarial_Training Public

    WideResNet implementation on MNIST dataset. FGSM and PGD adversarial attacks on standard training, PGD adversarial training, and Feature Scattering adversarial training.

    Python 3 1

  6. Speech-Command-Classification Public

    Speech command classification on Speech-Command v0.02 dataset using PyTorch and torchaudio. In this example, three models have been trained using the raw signal waveforms, MFCC features and MelSpec…

    Python 9 5

19 contributions in the last year

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Contribution activity

March 2025

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