4 citations · 4 across the 5 of their papers we have counts for
5 papers
EGSA-PT:Edge-Guided Spatial Attention with Progressive Training for Monocular Depth Estimation and Segmentation of Transparent Objects
Gbenga Omotara, Ramy Farag, Seyed Mohamad Ali Tousi +1
Transparent object perception remains a major challenge in computer vision research, as transparency confounds both depth estimation and semantic segmentation. Recent work has expl…
The Fourth Monocular Depth Estimation Challenge
Anton Obukhov, Matteo Poggi, Fabio Tosi +54
This paper presents the results of the fourth edition of the Monocular Depth Estimation Challenge (MDEC), which focuses on zero-shot generalization to the SYNS-Patches benchmark, a…
A Zero-Shot Learning Approach for Ephemeral Gully Detection from Remote Sensing using Vision Language Models
Seyed Mohamad Ali Tousi, Ramy Farag, Jacket Demby's +3
Ephemeral gullies are a primary cause of soil erosion and their reliable, accurate, and early detection will facilitate significant improvements in the sustainability of global agr…
COVID-19 detection from pulmonary CT scans using a novel EfficientNet with attention mechanism
Ramy Farag, Parth Upadhyay, Yixiang Gao +5
Manual analysis and diagnosis of COVID-19 through the examination of Computed Tomography (CT) images of the lungs can be time-consuming and result in errors, especially given high…
High-Throughput and Accurate 3D Scanning of Cattle Using Time-of-Flight Sensors and Deep Learning
Gbenga Omotara, Seyed Mohamad Ali Tousi, Jared Decker +2
We introduce a high throughput 3D scanning solution specifically designed to precisely measure cattle phenotypes. This scanner leverages an array of depth sensors, i.e. time-of-fli…