Soybean yield prediction from UAV using multimodal data fusion and deep learning
M Maimaitijiang, V Sagan, P Sidike, S Hartling… - Remote sensing of …, 2020 - Elsevier
Preharvest crop yield prediction is critical for grain policy making and food security. Early
estimation of yield at field or plot scale also contributes to high-throughput plant phenotyping …
estimation of yield at field or plot scale also contributes to high-throughput plant phenotyping …
Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms
Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield,
thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models …
thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models …
Multimodal brain tumor detection using multimodal deep transfer learning
MRI brain image analysis, including brain tumor detection, is a challenging task. MRI images
are multimodal, and in recent years, multimodal medical image analysis has gotten more …
are multimodal, and in recent years, multimodal medical image analysis has gotten more …
Evolving to multi-modal knowledge graphs for engineering design: state-of-the-art and future challenges
With the support of advanced information and communication technologies and open
innovative design platforms, the emerging and blooming paradigm of mass personalization …
innovative design platforms, the emerging and blooming paradigm of mass personalization …
[HTML][HTML] Finger vein identification using deeply-fused Convolutional Neural Network
Finger vein identification is a recently developed biometric technology and has become an
essential field in biometrics, garnering increasing attention in recent years. As a biometric …
essential field in biometrics, garnering increasing attention in recent years. As a biometric …
Msaf: Multimodal split attention fusion
Multimodal learning mimics the reasoning process of the human multi-sensory system,
which is used to perceive the surrounding world. While making a prediction, the human …
which is used to perceive the surrounding world. While making a prediction, the human …
Multimodal entity linking with gated hierarchical fusion and contrastive training
P Wang, J Wu, X Chen - Proceedings of the 45th International ACM …, 2022 - dl.acm.org
Previous entity linking methods in knowledge graphs (KGs) mostly link the textual mentions
to corresponding entities. However, they have deficiencies in processing numerous …
to corresponding entities. However, they have deficiencies in processing numerous …
CovTiNet: Covid text identification network using attention-based positional embedding feature fusion
Covid text identification (CTI) is a crucial research concern in natural language processing
(NLP). Social and electronic media are simultaneously adding a large volume of Covid …
(NLP). Social and electronic media are simultaneously adding a large volume of Covid …
Moving from narrative to interactive multi-modal sentiment analysis: A survey
A growing number of individuals are expressing their opinions and engaging in interactive
communication with others through various modalities, including natural language (text) …
communication with others through various modalities, including natural language (text) …
A Comprehensive Review on Sentiment Analysis: Tasks, Approaches and Applications
Sentiment analysis (SA) is an emerging field in text mining. It is the process of
computationally identifying and categorizing opinions expressed in a piece of text over …
computationally identifying and categorizing opinions expressed in a piece of text over …