Out-of-distribution (OOD) detection based on deep learning: A review
P Cui, J Wang - Electronics, 2022 - mdpi.com
Out-of-Distribution (OOD) detection separates ID (In-Distribution) data and OOD data from
input data through a model. This problem has attracted increasing attention in the area of …
input data through a model. This problem has attracted increasing attention in the area of …
3D reconstruction from endoscopy images: A survey
Z Yang, J Dai, J Pan - Computers in Biology and Medicine, 2024 - Elsevier
Three-dimensional reconstruction of images acquired through endoscopes is playing a vital
role in an increasing number of medical applications. Endoscopes used in the clinic are …
role in an increasing number of medical applications. Endoscopes used in the clinic are …
One step surgical scene restoration for robot assisted minimally invasive surgery
Minimally invasive surgery (MIS) offers several advantages to patients including minimum
blood loss and quick recovery time. However, lack of tactile or haptic feedback and poor …
blood loss and quick recovery time. However, lack of tactile or haptic feedback and poor …
Sugarcane diseases identification and detection via machine learning
M Mostafizur Rahman Komol, M Sabid Hasan… - Computer Vision and …, 2023 - Springer
Sugarcane diseases are major concern for the global sugarcane market, as they can
significantly impact crop yield and quality. This can result in economic losses for farmers and …
significantly impact crop yield and quality. This can result in economic losses for farmers and …
Arthroscopic scene segmentation using multispectral reconstructed frames and deep learning
Background Knee arthroscopy is one of the most complex minimally invasive surgeries, and
it is routinely performed to treat a range of ailments and injuries to the knee joint. Its complex …
it is routinely performed to treat a range of ailments and injuries to the knee joint. Its complex …
Surface reflectance: a metric for untextured surgical scene segmentation
Segmentation is a process to understand scene context captured by a camera, and it is
commonly used to solve many robotic problems such as localization and tracking. The utility …
commonly used to solve many robotic problems such as localization and tracking. The utility …
Towards robotic knee arthroscopy: multi-scale network for tissue-tool segmentation
Tissue awareness has a great demand to improve surgical accuracy in minimally invasive
procedures. In arthroscopy, it is one of the challenging tasks due to surgical sites exhibit …
procedures. In arthroscopy, it is one of the challenging tasks due to surgical sites exhibit …
Learning from learned network: an introspective model for arthroscopic scene segmentation
The knee joint, due to its complex, confined, and dynamic nature, poses several challenges
in visualizing anatomical details for diagnostic and minimally invasive surgical procedures …
in visualizing anatomical details for diagnostic and minimally invasive surgical procedures …
Self-supervised endoscopy depth estimation framework with CLIP-guidance segmentation
Z Yang, J Pan, J Dai, Z Sun, Y Xiao - Biomedical Signal Processing and …, 2024 - Elsevier
Background and objective: Depth estimation has very broad potential in medical image
analysis and is important for applications such as augmented reality surgical navigation and …
analysis and is important for applications such as augmented reality surgical navigation and …
A New Methodology to Detect Plant Disease Using Reprojected Multispectral Images from RGB Colour Space
Plant disease detection is a pivotal step to prevent crop damage and maximise the crop
yield. Although recent deep learning-based techniques achieved significant progress in this …
yield. Although recent deep learning-based techniques achieved significant progress in this …