Real-time robust detector for underwater live crabs based on deep learning
S Cao, D Zhao, X Liu, Y Sun - Computers and Electronics in Agriculture, 2020 - Elsevier
Image analysis technology has drawn dramatic attention and developed rapidly because it
enables a non-extractive and non-destructive approach to data acquisition of crab …
enables a non-extractive and non-destructive approach to data acquisition of crab …
A hybrid machine learning framework for predicting students' performance in virtual learning environment
E Evangelista - International Journal of Emerging Technologies in …, 2021 - learntechlib.org
Abstract Virtual Learning Environments (VLE), such as Moodle and Blackboard, store vast
data to help identify students' performance and engagement. As a result, researchers have …
data to help identify students' performance and engagement. As a result, researchers have …
Efficient Detection Method of Pig‐Posture Behavior Based on Multiple Attention Mechanism
L Huang, L Xu, Y Wang, Y Peng, Z Zou… - Computational …, 2022 - Wiley Online Library
Due to the low detection precision and poor robustness, the traditional pig‐posture and
behavior detection method is difficult to apply in the complex pig captivity environment. In …
behavior detection method is difficult to apply in the complex pig captivity environment. In …
[HTML][HTML] Current training and validation weaknesses in classification-based radiation fog nowcast using machine learning algorithms
M Vorndran, A Schütz, J Bendix… - Artificial Intelligence for …, 2022 - journals.ametsoc.org
Current Training and Validation Weaknesses in Classification-Based Radiation Fog
Nowcast Using Machine Learning Algorithms in: Artificial Intelligence for the Earth Systems …
Nowcast Using Machine Learning Algorithms in: Artificial Intelligence for the Earth Systems …
Predicting the risk of hospital readmissions using a machine learning approach: a case study on patients undergoing skin procedures
Introduction Even with modern advancements in medical care, one of the persistent
challenges hospitals face is the frequent readmission of patients. These recurrent …
challenges hospitals face is the frequent readmission of patients. These recurrent …
Multi‐level predictors of depression symptoms in the Adolescent Brain Cognitive Development (ABCD) study
Background While identifying risk factors for adolescent depression is critical for early
prevention and intervention, most studies have sought to understand the role of isolated …
prevention and intervention, most studies have sought to understand the role of isolated …
Mit Computer Vision zur automatisierten Qualitätssicherung in der industriellen Fertigung: Eine Fallstudie zur Klassifizierung von Fehlern in Solarzellen mittels …
Die Qualitätssicherung bei der Produktion von Solarzellen ist ein entscheidender Faktor, um
langfristige Leistungsgarantien auf Solarpanels gewähren zu können. Die vorliegende …
langfristige Leistungsgarantien auf Solarpanels gewähren zu können. Die vorliegende …
Cleaning up the mess: can machine learning be used to predict lower extremity amputation after trauma-associated arterial injury?
S Bolourani, D Thompson, S Siskind, BD Kalyon… - Journal of the American …, 2021 - Elsevier
Background Thirty years after the Mangled Extremity Severity Score was developed,
advances in vascular, trauma, and orthopaedic surgery have rendered the sensitivity of this …
advances in vascular, trauma, and orthopaedic surgery have rendered the sensitivity of this …
Regularized logistic regression model for cancer classification
Cancer is a serious disease and is considered one of the causes of death. Making it worse,
many cancers are diagnosed too late. Early, diagnosis of cancer helps in taking correct …
many cancers are diagnosed too late. Early, diagnosis of cancer helps in taking correct …
PyMerger: Detecting Binary Black Hole Mergers from the Einstein Telescope Using Deep Learning
Abstract We present PyMerger, a Python tool for detecting binary black hole (BBH) mergers
from the Einstein Telescope (ET), based on a deep residual neural network (ResNet) model …
from the Einstein Telescope (ET), based on a deep residual neural network (ResNet) model …