AIMC Topic: Neural Networks, Computer

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ADFQ-ViT: Activation-Distribution-Friendly post-training Quantization for Vision Transformers.

Neural networks : the official journal of the International Neural Network Society
Vision Transformers (ViTs) have exhibited exceptional performance across diverse computer vision tasks, while their substantial parameter size incurs significantly increased memory and computational demands, impeding effective inference on resource-c...

CNN-Transformer and Channel-Spatial Attention based network for hyperspectral image classification with few samples.

Neural networks : the official journal of the International Neural Network Society
Hyperspectral image classification is an important foundational technology in the field of Earth observation and remote sensing. In recent years, deep learning has achieved a series of remarkable achievements in this area. These deep learning-based h...

Modeling and optimization of docosahexaenoic acid production by Schizochytrium sp. based on kinetic modeling and genetic algorithm optimized artificial neural network.

Bioresource technology
Docosahexaenoic acid (DHA), an essential ω-3 polyunsaturated fatty acid, is efficiently biosynthesized by Schizochytrium sp., yet its bioprocess optimization remains constrained by dynamic interdependencies between cultivation parameters and metaboli...

Explaining Human Activity Recognition with SHAP: Validating insights with perturbation and quantitative measures.

Computers in biology and medicine
In Human Activity Recognition (HAR), understanding the intricacy of body movements within high-risk applications is essential. This study uses SHapley Additive exPlanations (SHAP) to explain the decision-making process of Graph Convolution Networks (...

Multi-dimensional consistency learning between 2D Swin U-Net and 3D U-Net for intestine segmentation from CT volume.

International journal of computer assisted radiology and surgery
PURPOSE: The paper introduces a novel two-step network based on semi-supervised learning for intestine segmentation from CT volumes. The intestine folds in the abdomen with complex spatial structures and contact with neighboring organs that bring dif...

Neural Network-Enhanced Electrochemical/SERS Dual-Mode Microfluidic Platform for Accurate Detection of Interleukin-6 in Diabetic Wound Exudates.

Analytical chemistry
Interleukin-6 (IL-6) plays a pivotal role in the inflammatory response of diabetic wounds, providing critical insights for clinicians in the development of personalized treatment strategies. However, the low concentration of IL-6 in biological sample...

Content-Based Histopathological Image Retrieval.

Sensors (Basel, Switzerland)
Feature descriptors in histopathological images are an important challenge for the implementation of Content-Based Image Retrieval (CBIR) systems, an essential tool to support pathologists. Deep learning models like Convolutional Neural Networks and ...

Semi-supervised tissue segmentation from histopathological images with consistency regularization and uncertainty estimation.

Scientific reports
Pathologists have depended on their visual experience to assess tissue structures in smear images, which was time-consuming, error-prone, and inconsistent. Deep learning, particularly Convolutional Neural Networks (CNNs), offers the ability to automa...

Improving Malaria diagnosis through interpretable customized CNNs architectures.

Scientific reports
Malaria, which is spread via female Anopheles mosquitoes and is brought on by the Plasmodium parasite, persists as a serious illness, especially in areas with a high mosquito density. Traditional detection techniques, like examining blood samples wit...

Optimizing eco-friendly jewelry design through an integrated eco-innovation approach using artificial neural networks.

Scientific reports
Achieving sustainable practices in the jewelry industry necessitates the adoption of optimized eco-design approaches. The optimization of eco-friendly jewelry design was investigated in this study through an integrated analysis of materials, digital ...