A comprehensive review of object detection with deep learning
R Kaur, S Singh - Digital Signal Processing, 2023 - Elsevier
In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …
demonstrated excellent performance. Video Processing, Object Detection, Image …
A comprehensive survey on arithmetic optimization algorithm
Abstract Arithmetic Optimization Algorithm (AOA) is a recently developed population-based
nature-inspired optimization algorithm (NIOA). AOA is designed under the inspiration of the …
nature-inspired optimization algorithm (NIOA). AOA is designed under the inspiration of the …
An adaptive particle swarm optimization-based hybrid long short-term memory model for stock price time series forecasting
In this paper, we presented a long short-term memory (LSTM) network and adaptive particle
swarm optimization (PSO)-based hybrid deep learning model for forecasting the stock price …
swarm optimization (PSO)-based hybrid deep learning model for forecasting the stock price …
Automated CT pancreas segmentation for acute pancreatitis patients by combining a novel object detection approach and U-Net
Acute pancreatitis is an inflammatory disorder of the pancreas. Medical imaging, such as
computed tomography (CT), has been widely used to detect volume changes in the …
computed tomography (CT), has been widely used to detect volume changes in the …
Foreign exchange forecasting and portfolio optimization strategy based on hybrid-molecular differential evolution algorithms
X Zhang, C Zhong, L Abualigah - Soft Computing, 2023 - Springer
At present, the COVID-19 epidemic is still spreading at home and abroad, and the foreign
exchange market is highly volatile. From financial institutions to individual investors, foreign …
exchange market is highly volatile. From financial institutions to individual investors, foreign …
Heart disease prediction using hybrid optimization enabled deep learning network with spark architecture
P Kanchanamala, AS Alphonse, PVB Reddy - Biomedical signal processing …, 2023 - Elsevier
Analyzing massive amounts of data that contain many sorts of data is known as big data
analytics. Additionally, the bulk of applications in the actual world need a significant amount …
analytics. Additionally, the bulk of applications in the actual world need a significant amount …
Machine learning concepts and its applications for prediction of diseases based on drug behaviour: An extensive review
Disease prediction system is one of the recent research areas in information processing
technologies such as data mining, machine learning and so on. Especially, the classification …
technologies such as data mining, machine learning and so on. Especially, the classification …
Detecting depression tendency based on deep learning and multi-sources data
W Ma, S Qiu, J Miao, M Li, Z Tian, B Zhang, W Li… - … Signal Processing and …, 2023 - Elsevier
In the past decade, cases of depression have been increasingly reported. While early
detection offers excellent advantages in reducing these cases, it still faces several …
detection offers excellent advantages in reducing these cases, it still faces several …
When less is more powerful: Shapley value attributed ablation with augmented learning for practical time series sensor data classification
Time series sensor data classification tasks often suffer from training data scarcity issue due
to the expenses associated with the expert-intervened annotation efforts. For example …
to the expenses associated with the expert-intervened annotation efforts. For example …
A traveler-centric mobility game: Efficiency and stability under rationality and prospect theory
IV Chremos, AA Malikopoulos - Plos one, 2023 - journals.plos.org
In this paper, we study a routing and travel-mode choice problem for mobility systems with a
multimodal transportation network as a “mobility game” with coupled action sets. We …
multimodal transportation network as a “mobility game” with coupled action sets. We …