In this video, we will look at the details of the RNN Model. We will see the mathematical equations for the RNN model, and ...

Transformers have revolutionized deep learning, but have you ever wondered how the decoder in a transformer actually works? In this video, we break down Decoder Architecture in Transformers step by ...

The work that we’re doing brings AI closer to human thinking,” said Mick Bonner, who teaches cognitive science at Hopkins.

Abstract: Recent advancements in deep neural networks heavily rely on large-scale labeled datasets. However, acquiring annotations for large datasets can be challenging due to annotation constraints.

Abstract: The automatic segmentation of liver tumors plays an important role in the diagnosis and treatment of liver cancer. While deep convolutional neural network (DCNN) models are widely used for ...

To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...

BTN began its trip to all 18 conference schools with a stop Friday in Lincoln to check out the Nebraska Cornhuskers. Nebraska football's preseason camp is nearly through the first week, but that has ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...

This study proposes an automated tongue analysis system that combines deep learning with traditional Chinese medicine to enhance the accuracy and objectivity of tongue diagnosis. The system includes a ...

UAV image acquisition and deep learning techniques have been widely used in field hydrological monitoring to meet the increasing data volume demand and refined ...