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Loss functions and constraints improve sea surface height prediction

In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or a snapshot of the ocean's surface, including peaks and valleys due to ...
Scientific Research Publishing

Speech Emotion Recognition Based on CNN-Transformer with Different Loss Function ()

Speech Emotion Recognition (SER) is crucial for enhancing human-computer interactions by enabling machines to understand and respond appropriately to human emotions. However, accurately recognizing ...
Hacker

Binary Classification: Understanding Activation and Loss Functions with a PyTorch Example

The basic principles required to solve classification tasks with neural networks are used as building blocks in more complicated deep learning problems such as object detection and instance ...
Frontiers

Low Dose CT Denoising by ResNet With Fused Attention Modules and Integrated Loss Functions

X-ray computed tomography (CT) is a non-invasive medical diagnostic tool that has raised public concerns due to the associated health risks of radiation dose to patients. Reducing the radiation dose ...
IEEE

Ophthalmic Disease Detection via Deep Learning With a Novel Mixture Loss Function

Abstract: With the popularization of computer-aided diagnosis (CAD) technologies, more and more deep learning methods are developed to facilitate the detection of ophthalmic diseases. In this article, ...
Quanta Magazine

Artificial Neural Nets Finally Yield Clues to How Brains Learn

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...