The fast escalation of COVID-19 since its outbreak has affected the health care system globally. To pare the dissemination of the disease it is important to detect COVID-19 positive cases at an early stage and isolate the patients as early as possible. So, an effective and timely method for detecting the disease is required. Despite the fact that RT-PCR is the benchmark for COVID-19 detection and is very accurate, it is time-consuming. Applying deep learning along with radiography may help in diagnosing patients with COVID-19 much fast. In the paper, we propose a deep learning-based CNN architecture inspired by AlexNet which takes a three-channel image input.