Machine Vision and Applications

Papers
(The H4-Index of Machine Vision and Applications is 21. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-03-01 to 2024-03-01.)
ArticleCitations
Deep convolutional neural networks with transfer learning for automated brain image classification120
Feature-transfer network and local background suppression for microaneurysm detection57
Hyper-parameter optimization of deep learning model for prediction of Parkinson’s disease52
A five-layer deep convolutional neural network with stochastic pooling for chest CT-based COVID-19 diagnosis48
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-1946
Early, intermediate and late fusion strategies for robust deep learning-based multimodal action recognition43
Segmentation of photovoltaic module cells in uncalibrated electroluminescence images40
A generalizable approach for multi-view 3D human pose regression38
ColpoNet for automated cervical cancer screening using colposcopy images34
LS-Net: fast single-shot line-segment detector32
A cognitive vision method for the detection of plant disease images30
An empirical study of different machine learning techniques for brain tumor classification and subsequent segmentation using hybrid texture feature30
Graph neural networks in node classification: survey and evaluation28
RCA-IUnet: a residual cross-spatial attention-guided inception U-Net model for tumor segmentation in breast ultrasound imaging26
Real-time camera pose estimation for sports fields25
Inception recurrent convolutional neural network for object recognition24
ARF-Crack: rotation invariant deep fully convolutional network for pixel-level crack detection24
Optimal feature level fusion for secured human authentication in multimodal biometric system23
Using CNN with Bayesian optimization to identify cerebral micro-bleeds23
Detection of tomato organs based on convolutional neural network under the overlap and occlusion backgrounds22
Interpretable visual transmission lines inspections using pseudo-prototypical part network22
A comparative study of breast cancer tumor classification by classical machine learning methods and deep learning method21
Deep understanding of shopper behaviours and interactions using RGB-D vision21
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