CNN variants for computer vision: History, architecture, application, challenges and future scope
Computer vision is becoming an increasingly trendy word in the area of image processing.
With the emergence of computer vision applications, there is a significant demand to …
With the emergence of computer vision applications, there is a significant demand to …
Human action recognition from various data modalities: A review
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …
each action. It has a wide range of applications, and therefore has been attracting increasing …
A survey of the recent architectures of deep convolutional neural networks
Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …
which has shown exemplary performance on several competitions related to Computer …
Predicting residential energy consumption using CNN-LSTM neural networks
The rapid increase in human population and development in technology have sharply
raised power consumption in today's world. Since electricity is consumed simultaneously as …
raised power consumption in today's world. Since electricity is consumed simultaneously as …
[HTML][HTML] Deep learning for object detection and scene perception in self-driving cars: Survey, challenges, and open issues
This article presents a comprehensive survey of deep learning applications for object
detection and scene perception in autonomous vehicles. Unlike existing review papers, we …
detection and scene perception in autonomous vehicles. Unlike existing review papers, we …
A survey of optimization methods from a machine learning perspective
Machine learning develops rapidly, which has made many theoretical breakthroughs and is
widely applied in various fields. Optimization, as an important part of machine learning, has …
widely applied in various fields. Optimization, as an important part of machine learning, has …
Multi-grade brain tumor classification using deep CNN with extensive data augmentation
Numerous computer-aided diagnosis (CAD) systems have been recently presented in the
history of medical imaging to assist radiologists about their patients. For full assistance of …
history of medical imaging to assist radiologists about their patients. For full assistance of …
Deep learning for multigrade brain tumor classification in smart healthcare systems: A prospective survey
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade
recognition is a challenging problem for radiologists in health monitoring and automated …
recognition is a challenging problem for radiologists in health monitoring and automated …
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …
resources planning and management. It is highly vital for hydropower operation, agricultural …
Vidtr: Video transformer without convolutions
Abstract We introduce Video Transformer (VidTr) with separable-attention for video
classification. Comparing with commonly used 3D networks, VidTr is able to aggregate …
classification. Comparing with commonly used 3D networks, VidTr is able to aggregate …