2 papers
q-bio.TO2025
R-Net: A Reliable and Resource-Efficient CNN for Colorectal Cancer Detection with XAI Integration
Rokonozzaman Ayon, Md Taimur Ahad, Bo Song +1
State-of-the-art (SOTA) Convolutional Neural Networks (CNNs) are criticized for their extensive computational power, long training times, and large datasets. To overcome this limit…
q-bio.TO2025
A study on Deep Convolutional Neural Networks, transfer learning, and Mnet model for Cervical Cancer Detection
Saifuddin Sagor, Md Taimur Ahad, Faruk Ahmed +2
Early and accurate detection through Pap smear analysis is critical to improving patient outcomes and reducing mortality of Cervical cancer. State-of-the-art (SOTA) Convolutional N…