AIMC Topic: Neural Networks, Computer

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Bangladeshi Native Vehicle Classification Based on Transfer Learning with Deep Convolutional Neural Network.

Sensors (Basel, Switzerland)
Vehicle type classification plays an essential role in developing an intelligent transportation system (ITS). Based on the modern accomplishments of deep learning (DL) on image classification, we proposed a model based on transfer learning, incorpora...

Development and validation of the 3D U-Net algorithm for segmentation of pelvic lymph nodes on diffusion-weighted images.

BMC medical imaging
BACKGROUND: The 3D U-Net model has been proved to perform well in the automatic organ segmentation. The aim of this study is to evaluate the feasibility of the 3D U-Net algorithm for the automated detection and segmentation of lymph nodes (LNs) on pe...

An efficient strategy for predicting river dissolved oxygen concentration: application of deep recurrent neural network model.

Environmental monitoring and assessment
Dissolved oxygen (DO) concentration in water is one of the key parameters for assessing river water quality. Artificial intelligence (AI) methods have previously proved to be accurate tools for DO concentration prediction. This study presents the imp...

Evaluation of Deep Neural Network Compression Methods for Edge Devices Using Weighted Score-Based Ranking Scheme.

Sensors (Basel, Switzerland)
The demand for object detection capability in edge computing systems has surged. As such, the need for lightweight Convolutional Neural Network (CNN)-based object detection models has become a focal point. Current models are large in memory and deplo...

The Impact of Attention Mechanisms on Speech Emotion Recognition.

Sensors (Basel, Switzerland)
Speech emotion recognition (SER) plays an important role in real-time applications of human-machine interaction. The Attention Mechanism is widely used to improve the performance of SER. However, the applicable rules of attention mechanism are not de...

Detecting Animal Contacts-A Deep Learning-Based Pig Detection and Tracking Approach for the Quantification of Social Contacts.

Sensors (Basel, Switzerland)
The identification of social interactions is of fundamental importance for animal behavioral studies, addressing numerous problems like investigating the influence of social hierarchical structures or the drivers of agonistic behavioral disorders. Ho...

Weakly Supervised Video Anomaly Detection Based on 3D Convolution and LSTM.

Sensors (Basel, Switzerland)
Weakly supervised video anomaly detection is a recent focus of computer vision research thanks to the availability of large-scale weakly supervised video datasets. However, most existing research works are limited to the frame-level classification wi...

MemDis: Predicting Disordered Regions in Transmembrane Proteins.

International journal of molecular sciences
Transmembrane proteins (TMPs) play important roles in cells, ranging from transport processes and cell adhesion to communication. Many of these functions are mediated by intrinsically disordered regions (IDRs), flexible protein segments without a wel...

Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans.

Communications biology
Deep learning (DL) is a breakthrough technology for medical imaging with high sample size requirements and interpretability issues. Using a pretrained DL model through a radiomics-guided approach, we propose a methodology for stratifying the prognosi...

Adaptive neurons compute confidence in a decision network.

Scientific reports
Humans and many animals have the ability to assess the confidence of their decisions. However, little is known about the underlying neural substrate and mechanism. In this study we propose a computational model consisting of a group of 'confidence ne...