18 citations · 29 across the 6 of their papers we have counts for
6 papers
Estimating 2D Keypoints of Surgical Tools Using Vision-Language Models with Low-Rank Adaptation
Krit Duangprom, Tryphon Lambrou, Binod Bhattarai
This paper presents a novel pipeline for 2D keypoint estima- tion of surgical tools by leveraging Vision Language Models (VLMs) fine- tuned using a low rank adjusting (LoRA) techni…
NCDD: Nearest Centroid Distance Deficit for Out-Of-Distribution Detection in Gastrointestinal Vision
Sandesh Pokhrel, Sanjay Bhandari, Sharib Ali +7
The integration of deep learning tools in gastrointestinal vision holds the potential for significant advancements in diagnosis, treatment, and overall patient care. A major challe…
TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision
Sandesh Pokhrel, Sanjay Bhandari, Eduard Vazquez +3
Deep learning has significantly advanced the field of gastrointestinal vision, enhancing disease diagnosis capabilities. One major challenge in automating diagnosis within gastroin…
DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection for Dual-Energy X-Ray Baggage Imagery
A. Williamson, P. Dickinson, T. Lambrou +1
Recent advancements in Convolutional Neural Networks have yielded super-human levels of performance in image recognition tasks [13, 25]; however, with increasing volumes of parcels…
MRI Brain Tumor Segmentation using Random Forests and Fully Convolutional Networks
Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou +3
In this paper, we propose a novel learning based method for automated segmentation of brain tumor in multimodal MRI images, which incorporates two sets of machine -learned and hand…
Multimodal MRI brain tumor segmentation using random forests with features learned from fully convolutional neural network
Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou +2
In this paper, we propose a novel learning based method for automated segmenta-tion of brain tumor in multimodal MRI images. The machine learned features from fully convolutional n…