A Hybrid CNN-Transformer Architecture for Precise Medical Image Segmentation

[Preprint] Official implementation of "A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities".

Authorship Attribution for Romanian

The goal of this assignment is to predict the secondary structure (sst3 and sst8 values) from just the primary sequence (seq) using deep learning techniques, which can significantly reduce the need for expensive lab work. Authors: Garv Sachdev, Bay Yong Wei Nicholas, Nathanael Lo Tzin Ye.

Chest X-Ray Lung Diseases Classification with CAM Visualization

CoHAtNet: An Integrated Convolution-Transformer Architecture for End-to-End Camera Localization

Mobile-CoHAtNet is a lightweight and efficient hybrid convolution-transformer architecture designed for robust 6-DoF camera localization. The model leverages RGB, depth, and IMU data