A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions
A Thakkar, K Chaudhari - Expert Systems with Applications, 2021 - Elsevier
The stock market has been an attractive field for a large number of organizers and investors
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …
Pixels to precision: features fusion and random forests over labelled-based segmentation
A Naseer, A Jalal - 2023 20th International Bhurban …, 2023 - ieeexplore.ieee.org
Object classification is a crucial yet challenging vision ability to perfect The fundamental
objective is to educate computers to understand visuals the same way humans do. Due to …
objective is to educate computers to understand visuals the same way humans do. Due to …
Research on a surface defect detection algorithm based on MobileNet-SSD
Y Li, H Huang, Q **e, L Yao, Q Chen - Applied Sciences, 2018 - mdpi.com
This paper aims to achieve real-time and accurate detection of surface defects by using a
deep learning method. For this purpose, the Single Shot MultiBox Detector (SSD) network …
deep learning method. For this purpose, the Single Shot MultiBox Detector (SSD) network …
An efficient deep convolutional neural network based detection and classification of acute lymphoblastic leukemia
Automated and accurate diagnosis of Acute Lymphoblastic Leukemia (ALL), blood cancer, is
a challenging task. Nowadays, Convolutional Neural Networks (CNNs) have become a …
a challenging task. Nowadays, Convolutional Neural Networks (CNNs) have become a …
Automatic human posture estimation for sport activity recognition with robust body parts detection and entropy markov model
Automated human posture estimation (A-HPE) systems need delicate methods for detecting
body parts and selecting cues based on marker-less sensors to effectively recognize …
body parts and selecting cues based on marker-less sensors to effectively recognize …
Robust human activity recognition from depth video using spatiotemporal multi-fused features
The recently developed depth imaging technologies have provided new directions for
human activity recognition (HAR) without attaching optical markers or any other motion …
human activity recognition (HAR) without attaching optical markers or any other motion …
Human actions tracking and recognition based on body parts detection via Artificial neural network
Human body action recognition has drawn a good deal of interest in the community of
computer vision, owing to its wide range of applications. Recently, the video/image …
computer vision, owing to its wide range of applications. Recently, the video/image …
Yoga pose estimation and feedback generation using deep learning
Yoga is a 5000‐year‐old practice developed in ancient India by the Indus‐Sarasvati
civilization. The word yoga means deep association and union of mind with the body. It is …
civilization. The word yoga means deep association and union of mind with the body. It is …
Maximum entropy scaled super pixels segmentation for multi-object detection and scene recognition via deep belief network
Recent advances in visionary technologies impacted multi-object recognition and scene
understanding. Such scene-understanding tasks are a demanding part of several …
understanding. Such scene-understanding tasks are a demanding part of several …
Students' behavior mining in e-learning environment using cognitive processes with information technologies
A Jalal, M Mahmood - Education and Information Technologies, 2019 - Springer
Rapid growth and recent developments in education sector and information technologies
have promoted E-learning and collaborative sessions among the learning communities and …
have promoted E-learning and collaborative sessions among the learning communities and …