Achieving Pareto Optimality using Efficient Parameter Reduction for DNNs in Resource-Constrained Edge Environment

no code implementations • 14 Mar 2024 • Atah Nuh Mih, Alireza Rahimi, Asfia Kawnine, Francis Palma, Monica Wachowicz, Rickey Dubay, Hung Cao

The results of the Caltech-101 image classification show that our model has a better test accuracy (76. 21%) than Xception (75. 89%), uses less memory on average (847. 9MB) than Xception (874. 6MB), and has faster training and inference times.

Defect Detection Image Classification +1

Automatic Diagnosis of COVID-19 from CT Images using CycleGAN and Transfer Learning

no code implementations • 24 Apr 2021 • Navid Ghassemi, Afshin Shoeibi, Marjane Khodatars, Jonathan Heras, Alireza Rahimi, Assef Zare, Ram Bilas Pachori, J. Manuel Gorriz

Also, in order to evaluate the method, a dataset containing 3163 images from 189 patients has been collected and labeled by physicians.

Computed Tomography (CT) Data Augmentation +1