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Deep learning in economics: a systematic and critical review
From the perspective of historical review, the methodology of economics develops from
qualitative to quantitative, from a small sampling of data to a vast amount of data. Because of …
qualitative to quantitative, from a small sampling of data to a vast amount of data. Because of …
The fusion of deep learning and fuzzy systems: A state-of-the-art survey
Deep learning presents excellent learning ability in constructing learning model and greatly
promotes the development of artificial intelligence, but its conventional models cannot …
promotes the development of artificial intelligence, but its conventional models cannot …
Literature review of vision‐based dynamic gesture recognition using deep learning techniques
Gesture recognition is the foremost need in building intelligent human‐computer interaction
systems to solve many day‐to‐day problems and simplify human life in this digital world. The …
systems to solve many day‐to‐day problems and simplify human life in this digital world. The …
[Retracted] Dynamic Gesture Recognition Algorithm Based on 3D Convolutional Neural Network
Y Liu, D Jiang, H Duan, Y Sun, G Li… - Computational …, 2021 - Wiley Online Library
Gesture recognition is one of the important ways of human‐computer interaction, which is
mainly detected by visual technology. The temporal and spatial features are extracted by …
mainly detected by visual technology. The temporal and spatial features are extracted by …
Dynamic hand gesture recognition using 3D-CNN and LSTM networks
Recognition of dynamic hand gestures in real-time is a difficult task because the system can
never know when or from where the gesture starts and ends in a video stream. Many …
never know when or from where the gesture starts and ends in a video stream. Many …
Exploring modality-shared appearance features and modality-invariant relation features for cross-modality person re-identification
Most existing cross-modality person Re-IDentification works rely on discriminative modality-
shared features for reducing cross-modality variations and intra-modality variations. Despite …
shared features for reducing cross-modality variations and intra-modality variations. Despite …
The need for quantification of uncertainty in artificial intelligence for clinical data analysis: increasing the level of trust in the decision-making process
Different terms such as trust, certainty, and uncertainty are of great importance in the real
world and play a critical role in artificial intelligence (AI) applications. The implied …
world and play a critical role in artificial intelligence (AI) applications. The implied …
Sign language recognition based on R (2+ 1) D with spatial–temporal–channel attention
Previous work utilized three-dimensional (3-D) convolutional neural networks (CNNs)
tomodel the spatial appearance and temporal evolution concurrently for sign language …
tomodel the spatial appearance and temporal evolution concurrently for sign language …
TMMF: Temporal multi-modal fusion for single-stage continuous gesture recognition
Gesture recognition is a much studied research area which has myriad real-world
applications including robotics and human-machine interaction. Current gesture recognition …
applications including robotics and human-machine interaction. Current gesture recognition …
FMCW radar-based hand gesture recognition using spatiotemporal deformable and context-aware convolutional 5-D feature representation
Recently, frequency-modulated continuous-wave (FMCW) radar-based hand gesture
recognition (HGR) using deep learning has achieved favorable performance. However …
recognition (HGR) using deep learning has achieved favorable performance. However …