Results 41 to 50 of about 14,783 (197)
Detection Mature Bud for Daylily Based on Faster R-CNN Integrated With CBAM
IEEE Access, 2023 The daylily (Hemerocallis citrina Baroni) is rich in not only nutrition ingredients but also functional components, and the edible part is the flower, not containing its pedicel.
Junhui Feng +5 more
doaj +1 more source
Deep learning architectures for Computer Vision [PDF]
, 2016 Deep learning has become part of many state-of-the-art systems in multiple disciplines (specially in computer vision and speech processing). In this thesis Convolutional Neural Networks are used to solve the problem of recognizing people in images, both ...
Roig Marí, Carlos
core
Surgical Phase Recognition of Short Video Shots Based on Temporal Modeling of Deep Features
, 2018 Recognizing the phases of a laparoscopic surgery (LS) operation form its video constitutes a fundamental step for efficient content representation, indexing and retrieval in surgical video databases.
Loukas, Constantinos
core +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni +11 more
wiley +1 more source
, 2018 Advances in image restoration and enhancement techniques have led to discussion about how such algorithmscan be applied as a pre-processing step to improve automatic visual recognition. In principle, techniques like deblurring and super-resolution should
Banerjee, Sreya +4 more
core +1 more source
An Attention‐Assisted Machine Learning System for Deep Microorganism Image Classification
Advanced Intelligent Systems, EarlyView.An attention‐assisted DenseNet201 framework was developed for the classification of eight microorganism classes from microscopic images. The proposed model improved classification performance and achieved an accuracy of 87.38%. Advances in microbiology and environmental health fundamentally depend on precise and timely microorganism identification ...
Yujie Li +6 more
wiley +1 more source
Computers, 2023 Deep learning (DL) methods have the potential to be used for detecting COVID-19 symptoms. However, the rationale for which DL method to use and which symptoms to detect has not yet been explored.
Meysam Effati, Goldie Nejat
doaj +1 more source
Arthritis &Rheumatology, Accepted Article.Objective Regular imaging by conventional radiography to assess for joint damage is a cornerstone in the management of rheumatoid arthritis (RA). Scoring systems to quantify such damage, such as the widely used Sharp/van der Heijde (SvdH) score, are limited by the requirement of time and experienced staff as well as intra‐ and inter‐rater variability ...
Thomas Deimel +6 more
wiley +1 more source
Classification Of Mustard Leaf Diseases Using Convolutional Neural Network Architecture
Journal of Electrical Engineering and ComputerDiseases in mustard leaves can reduce productivity if not detected early. This study aims to develop and evaluate a disease classification system for mustard leaves using Convolutional Neural Network (CNN) architectures, specifically Xception and VGG19 ...
M. Hafidurrohman, K Kusrini
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Review on enhancing clinical decision support system using machine learning
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood +4 more
wiley +1 more source