With the widespread use of deep neural networks(DNNs) in intelligent sys...
Most contemporary supervised Remote Sensing (RS) image Change Detection ...
In this paper, we investigate a distributed aggregative optimization pro...
Pretraining on large-scale datasets can boost the performance of object
...
The vanilla fractional order gradient descent may oscillatively converge...
Bit-serial architectures can handle Neural Networks (NNs) with different...
In this paper, we propose a novel nonlinear observer, called the neural
...
Training deep learning-based change detection (CD) model heavily depends...
Multimodal sentiment analysis has attracted increasing attention and lot...
Sparsity is an intrinsic property of neural network(NN). Many software
r...
Contemporary transfer learning-based methods to alleviate the data
insuf...
Expensive bounding-box annotations have limited the development of objec...
The local feature detector and descriptor are essential in many computer...
The Network-on-Chips is a promising candidate for addressing communicati...
Confronted with the challenge of high performance for applications and t...
In three dimensional integrated circuits (3D-ICs), through silicon via (...