AIMC Topic: Neural Networks, Computer

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Perturbation of deep autoencoder weights for model compression and classification of tabular data.

Neural networks : the official journal of the International Neural Network Society
Fully connected deep neural networks (DNN) often include redundant weights leading to overfitting and high memory requirements. Additionally, in tabular data classification, DNNs are challenged by the often superior performance of traditional machine...

A novel MCF-Net: Multi-level context fusion network for 2D medical image segmentation.

Computer methods and programs in biomedicine
Medical image segmentation is a crucial step in the clinical applications for diagnosis and analysis of some diseases. U-Net-based convolution neural networks have achieved impressive performance in medical image segmentation tasks. However, the mult...

Domain-specific and domain-general neural network engagement during human-robot interactions.

The European journal of neuroscience
To what extent do domain-general and domain-specific neural network engagement generalize across interactions with human and artificial agents? In this exploratory study, we analysed a publicly available functional MRI (fMRI) data set (n = 22) to pro...

Identifying SNARE Proteins Using an Alignment-Free Method Based on Multiscan Convolutional Neural Network and PSSM Profiles.

Journal of chemical information and modeling
: SNARE proteins play a vital role in membrane fusion and cellular physiology and pathological processes. Many potential therapeutics for mental diseases or even cancer based on SNAREs are also developed. Therefore, there is a dire need to predict th...

A Method of Deep Learning Model Optimization for Image Classification on Edge Device.

Sensors (Basel, Switzerland)
Due to the recent increasing utilization of deep learning models on edge devices, the industry demand for Deep Learning Model Optimization (DLMO) is also increasing. This paper derives a usage strategy of DLMO based on the performance evaluation thro...

Power Equipment Fault Diagnosis Method Based on Energy Spectrogram and Deep Learning.

Sensors (Basel, Switzerland)
With the development of industrial manufacturing intelligence, the role of rotating machinery in industrial production and life is more and more important. Aiming at the problems of the complex and changeable working environment of rolling bearings a...

Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) has been studied extensively, yet current approaches are not capable of generalizing across different domains (i.e., subjects, devices, or datasets) with acceptable performance. This lack of generalization hinders the...

Deep leaning-based ultra-fast stair detection.

Scientific reports
Staircases are some of the most common building structures in urban environments. Stair detection is an important task for various applications, including the environmental perception of exoskeleton robots, humanoid robots, and rescue robots and the ...

Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset.

Scientific data
Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging. Recently, deep learning-based approaches have proven their potential for supporting pathologists in this re...

Transformer and group parallel axial attention co-encoder for medical image segmentation.

Scientific reports
U-Net has become baseline standard in the medical image segmentation tasks, but it has limitations in explicitly modeling long-term dependencies. Transformer has the ability to capture long-term relevance through its internal self-attention. However,...