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DSCC_Net: multi-classification deep learning models for diagnosing of skin cancer using dermoscopic images
Simple Summary This paper proposes a deep learning-based skin cancer classification
network (DSCC_Net) that is based on a convolutional neural network (CNN) and …
network (DSCC_Net) that is based on a convolutional neural network (CNN) and …
Gastrointestinal tract disease classification from wireless endoscopy images using pretrained deep learning model
Wireless capsule endoscopy is a noninvasive wireless imaging technology that becomes
increasingly popular in recent years. One of the major drawbacks of this technology is that it …
increasingly popular in recent years. One of the major drawbacks of this technology is that it …
CG‐Net: A novel CNN framework for gastrointestinal tract diseases classification
The classification of medical images has had a significant influence on the diagnostic
techniques and therapeutic interventions. Conventional disease diagnosis procedures …
techniques and therapeutic interventions. Conventional disease diagnosis procedures …
Wind speed prediction based on multi-variable Capsnet-BILSTM-MOHHO for WPCCC
T Liang, C Chai, H Sun, J Tan - Energy, 2022 - Elsevier
To additional understand the wind speed prediction of every wind energy facility in several
geographical locations and environments within the Wind Power Centralized Control Center …
geographical locations and environments within the Wind Power Centralized Control Center …
Diagnosis of ulcerative colitis from endoscopic images based on deep learning
X Luo, J Zhang, Z Li, R Yang - Biomedical Signal Processing and Control, 2022 - Elsevier
Aims Evaluating the endoscopic images of patients with ulcerative colitis can effectively
determine a reasonable treatment plan. However, the endoscopic evaluation is usually …
determine a reasonable treatment plan. However, the endoscopic evaluation is usually …
TTDCapsNet: Tri Texton-Dense Capsule Network for complex and medical image recognition
Convolutional Neural Networks (CNNs) are frequently used algorithms because of their
propensity to learn relevant and hierarchical features through their feature extraction …
propensity to learn relevant and hierarchical features through their feature extraction …
Enhanced Diagnosis of Skin Cancer from Dermoscopic Images Using Alignment Optimized Convolutional Neural Networks and Grey Wolf Optimization
Skin cancer (SC) is a highly serious kind of cancer that, if not addressed swiftly, might result
in the patient's demise. Early detection of this condition allows for more effective therapy and …
in the patient's demise. Early detection of this condition allows for more effective therapy and …
[HTML][HTML] A robust deep model for classification of peptic ulcer and other digestive tract disorders using endoscopic images
Accurate patient disease classification and detection through deep-learning (DL) models are
increasingly contributing to the area of biomedical imaging. The most frequent …
increasingly contributing to the area of biomedical imaging. The most frequent …
Gastrointestinal tract disease recognition based on denoising capsule network
Today, cancer is one of the leading causes of death in humans in the world. Cancers affect
different parts of the human anatomy in different ways. There are significantly more deaths …
different parts of the human anatomy in different ways. There are significantly more deaths …
[HTML][HTML] Patch-and-amplify Capsule Network for the recognition of gastrointestinal diseases
Deep learning (DL) algorithms require massive amounts of data in diverse variations to
attain close to human recognition accuracy. This enables them to perform well on unseen in …
attain close to human recognition accuracy. This enables them to perform well on unseen in …