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Models Supported: DenseNet121, DenseNet161, DenseNet169, DenseNet201 and DenseNet264 (1D and 2D version with DEMO for Classification and Regression)

License: MIT License

Jupyter Notebook 95.65% Python 4.35%
deep-learning deep-neural-networks machine-learning convolutional-neural-networks cnn tensorflow2 keras-tensorflow densenet densenet-tensorflow densenet121

densenet-1d-2d-tensorflow-keras's Introduction

Salam

I am Sakib Mahmud, currently working as a Research Assistant at Qatar University (QU) and Hamad Medical Corporation (HMC). My research field primarily revolves around Artificial Intelligence (AI) applications in the HealthCare sector.

Notable Publications

I have 43 publications in peer-reviewed journals and 3 in conference proceedings. Notable mentions:

  • Our proposed NABNet [1] can continuously reconstruct ABP waveforms from PPG and ECG signals (2023, BSPC Elsevier, IF: 5.076), inspired by our pioneering study PPG2ABP first appeared during 2020 [2].
  • Our proposed QUCoughScope [3] is able to reliably detect COVID-19 from cough and breath sounds (2022, Diagnostics MDPI, IF: 3.992).
  • We also reliably detected and quantified the lung infections caused by COVID-19 from Chest X-Ray images (2021, CIBM Elsevier, IF: 6.698) [4] and from Chest CT scans (2021, Diagnostics MDPI, IF: 3.992) [5].
  • Can COVID-19 be reliably estimated from wearable data? We replied to that question in PCovNet [6] (2022, CIBM Elsevier, IF: 6.698).
  • Our team in Qatar University (QU) developed electronic [7] (2022, Sensors MDPI, IF: 3.847) and optoelectronic [8] (2022, JSNA: Physical Elsevier, IF: 4.291) sensor based smart insoles for real-time plantar pressure and temperature data acquisition for home monitoring of patients with foot complications such as Diabetic Neuropathy.

Please visit my Google Scholar and ResearchGate profiles for more details.

Tools I Use

C MATLAB Python R TensorFlow PyTorch PyCharm VSCode Embedded C Arduino Esp32 Google Sheets Tableau LabVIEW Eagle Fusion360 Git GitHub

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