AIMC Topic: Deep Learning

Clear Filters Showing 15611 to 15620 of 28423 articles

Carbon price forecasting: a novel deep learning approach.

Environmental science and pollution research international
Carbon emission trading market promotes carbon emission reduction effectively. Accurate carbon price forecasting is crucial for relevant policy makers and investors. However, due to the non-linearity, uncertainty, and complexity of carbon prices, the...

Detection of moisture content in salted sea cucumbers by hyperspectral and low field nuclear magnetic resonance based on deep learning network framework.

Food research international (Ottawa, Ont.)
The accurate control of moisture content (MC) during the processing of sea cucumber is beneficial to improve the taste of sea cucumber and maintain its nutritional value, which is directly related to the quality and shelf life of sea cucumber. The pu...

Two-Way Feature Extraction for Speech Emotion Recognition Using Deep Learning.

Sensors (Basel, Switzerland)
Recognizing human emotions by machines is a complex task. Deep learning models attempt to automate this process by rendering machines to exhibit learning capabilities. However, identifying human emotions from speech with good performance is still cha...

Diagnostic Accuracy of Wireless Capsule Endoscopy in Polyp Recognition Using Deep Learning: A Meta-Analysis.

International journal of clinical practice
AIM: As the completed studies have small sample sizes and different algorithms, a meta-analysis was conducted to assess the accuracy of WCE in identifying polyps using deep learning.

Novel Method for Safeguarding Personal Health Record in Cloud Connection Using Deep Learning Models.

Computational intelligence and neuroscience
It is a new online service paradigm that allows consumers to exchange their health data. Health information management software allows individuals to control and share their health data with other users and healthcare experts. Patient health records ...

Sports Action Recognition Based on Deep Learning and Clustering Extraction Algorithm.

Computational intelligence and neuroscience
This paper constructs a sports action recognition model based on deep learning (DL) and clustering extraction algorithm. For the input detection image frame, athletes' movements are detected through DL network, and then athletes' sports movements are...

Predicting Breast Cancer Based on Optimized Deep Learning Approach.

Computational intelligence and neuroscience
Breast cancer is a dangerous disease with a high morbidity and mortality rate. One of the most important aspects in breast cancer treatment is getting an accurate diagnosis. Machine-learning (ML) and deep learning techniques can help doctors in makin...

Power and Area Efficient Cascaded Effectless GDI Approximate Adder for Accelerating Multimedia Applications Using Deep Learning Model.

Computational intelligence and neuroscience
Approximate computing is an upsurging technique to accelerate the process through less computational effort while keeping admissible accuracy of error-tolerant applications such as multimedia and deep learning. Inheritance properties of the deep lear...

Online Diagnosis and Classification of CT Images Collected by Internet of Things Using Deep Learning.

Computational and mathematical methods in medicine
Deep learning technology has recently played an important role in image, language processing, and feature extraction. In the past disease diagnosis, most medical staff fixed the images together for observation and then combined with their own work ex...

Comparison and verification of two deep learning models for the detection of chest CT rib fractures.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: A high false-positive rate remains a technical glitch hindering the broad spectrum of application of deep-learning-based diagnostic tools in routine radiological practice from assisting in diagnosing rib fractures.