Scientific Research Publishing

A Combination Method of Stacked Convolutional Auto-Encoder and Selective Kernel Attention Mechanism for Image Classification ()

1 College of Information Engineering, Xinchuang Software Industry Base, Yancheng Teachers University, Yancheng, China. 2 Yancheng Agricultural College, Yancheng, China. Convolutional auto-encoders ...
IEEE

Computationally Efficient Single Layer Transformer Convolutional Encoder for Accurate Price Prediction of Agriculture Commodities

Abstract: Predicting the accurate future price of the agricultural crops is important to avoid overproduction or shortages in the food supply chain. To obtain accurate predictions, the process usually ...
GitHub

HimAir10/Image-Retrieval-Based-on-a-Hybrid-Model-of-Deep-Convolutional-Encoder

This project presents an effective hybrid deep learning model for content-based image retrieval (CBIR), designed to bridge the semantic gap in visual search tasks. The proposed approach integrates a 6 ...
Visual Studio Magazine

Convolutional Neural Networks for MNIST Data Using PyTorch

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...
IEEE

Frequency-Domain Convolutional Network With Historical Data Fusion Module for Regional Streamflow Prediction

Abstract: Accurate runoff prediction is essential for effective water resource management, particularly in addressing flood control and monitoring drought conditions. However, the diverse nature of ...
Frontiers

A 3D Fully Convolutional Neural Network With Top-Down Attention-Guided Refinement for Accurate and Robust Automatic Segmentation of Amygdala and Its Subnuclei

Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most ...