AIMC Topic: Algorithms

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Foreground segmentation network using transposed convolutional neural networks and up sampling for multiscale feature encoding.

Neural networks : the official journal of the International Neural Network Society
Foreground segmentation algorithm aims to precisely separate moving objects from the background in various environments. However, the interference from darkness, dynamic background information, and camera jitter makes it still challenging to build a ...

Multi-task machine learning models for simultaneous prediction of tissue-to-blood partition coefficients of chemicals in mammals.

Environmental research
Tissue-to-blood partition coefficients (P) are crucial for assessing the distribution of chemicals in organisms. Given the lack of experimental data and laborious nature of experimental methods, there is an urgent need to develop efficient predictive...

Filter pruning for convolutional neural networks in semantic image segmentation.

Neural networks : the official journal of the International Neural Network Society
The remarkable performance of Convolutional Neural Networks (CNNs) has increased their use in real-time systems and devices with limited resources. Hence, compacting these networks while preserving accuracy has become necessary, leading to multiple c...

Towards audio-based identification of Ethio-Semitic languages using recurrent neural network.

Scientific reports
In recent times, there is an increasing interest in employing technology to process natural language with the aim of providing information that can benefit society. Language identification refers to the process of detecting which speech a speaker app...

Cross-Domain Unpaired Learning for Low-Dose CT Imaging.

IEEE journal of biomedical and health informatics
Supervised deep-learning techniques with paired training datasets have been widely studied for low-dose computed tomography (LDCT) imaging with excellent performance. However, the paired training datasets are usually difficult to obtain in clinical r...

Decentralized Data-Privacy Preserving Deep-Learning Approaches for Enhancing Inter-Database Generalization in Automatic Sleep Staging.

IEEE journal of biomedical and health informatics
Automatic sleep staging has been an active field of development. Despite multiple efforts, the area remains a focus of research interest. Indeed, while promising results have reported in past literature, uptake of automatic sleep scoring in the clini...

Medical image analysis using deep learning algorithms.

Frontiers in public health
In the field of medical image analysis within deep learning (DL), the importance of employing advanced DL techniques cannot be overstated. DL has achieved impressive results in various areas, making it particularly noteworthy for medical image analys...

Task-based assessment of resolution properties of CT images with a new index using deep convolutional neural network.

Radiological physics and technology
In this study, we propose a method for obtaining a new index to evaluate the resolution properties of computed tomography (CT) images in a task-based manner. This method applies a deep convolutional neural network (DCNN) machine learning system train...

Extracting laboratory test information from paper-based reports.

BMC medical informatics and decision making
BACKGROUND: In the healthcare domain today, despite the substantial adoption of electronic health information systems, a significant proportion of medical reports still exist in paper-based formats. As a result, there is a significant demand for the ...