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Scientific reports
Nov 8, 2022
Geographical research using historical maps has progressed considerably as the digitalization of topological maps across years provides valuable data and the advancement of AI machine learning models provides powerful analytic tools. Nevertheless, an...
IEEE transactions on pattern analysis and machine intelligence
Nov 7, 2022
We propose a novel unified frameork for automated distributed active learning (AutoDAL) to address multiple challenging problems in active learning such as limited labeled data, imbalanced datasets, automatic hyperparameter selection as well as scala...
IEEE transactions on pattern analysis and machine intelligence
Nov 7, 2022
While supervised object detection and segmentation methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on. To address this when annotating data is prohibiti...
Neural networks : the official journal of the International Neural Network Society
Nov 3, 2022
Feature selection is a crucial part of machine learning and pattern recognition, which aims at selecting a subset of informative features from the original dataset. Because of label information, supervised feature selection performs better than unsup...
Communications biology
Nov 2, 2022
Segmenting single cells is a necessary process for extracting quantitative data from biological microscopy imagery. The past decade has seen the advent of machine learning (ML) methods to aid in this process, the overwhelming majority of which fall u...
IEEE transactions on medical imaging
Oct 27, 2022
Emerging deep learning-based methods have enabled great progress in automatic neuron segmentation from Electron Microscopy (EM) volumes. However, the success of existing methods is heavily reliant upon a large number of annotations that are often exp...
IEEE transactions on neural networks and learning systems
Oct 27, 2022
We propose a complete hardware-based architecture of multilayer neural networks (MNNs), including electronic synapses, neurons, and periphery circuitry to implement supervised learning (SL) algorithm of extended remote supervised method (ReSuMe). In ...
Experimental biology and medicine (Maywood, N.J.)
Oct 25, 2022
Fully supervised learning for whole slide image-based diagnostic tasks in histopathology is problematic due to the requirement for costly and time-consuming manual annotation by experts. Weakly supervised learning that utilizes only slide-level label...
Sensors (Basel, Switzerland)
Oct 19, 2022
Printed circuit board (PCB) defect detection plays a crucial role in PCB production, and the popular methods are based on deep learning and require large-scale datasets with high-level ground-truth labels, in which it is time-consuming and costly to ...
Medical image analysis
Oct 17, 2022
Semi-supervised learning has a great potential in medical image segmentation tasks with a few labeled data, but most of them only consider single-modal data. The excellent characteristics of multi-modal data can improve the performance of semi-superv...