Search Results - (( deep learning problems algorithm ) OR ( java application based algorithm ))

Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023) by Hosseini E., Al-Ghaili A.M., Kadir D.H., Gunasekaran S.S., Ahmed A.N., Jamil N., Deveci M., Razali R.A.

“…Additionally, we propose a novel framework that seamlessly merges meta-heuristic algorithms into deep learning paradigms, aiming to enhance performance and efficiency in addressing energy-related problems. …”

Deep reinforcement learning with robust deep deterministic policy gradient by Teckchai Tiong, Ismail Saad, Kenneth Tze Kin Teo, Herwansyah Lago

“…Recently, Deep Deterministic Policy Gradient (DDPG) is a popular deep reinforcement learning algorithms applied to continuous control problems like autonomous driving and robotics. …”
Get full text
Get full text
Get full text

Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

“…In the performance comparison between proposed deep reinforcement learning with evolutionary algorithm, despite one of the variants of evolutionary algorithm has good performance in precision, it has rather weak performance in term of novelty and diversity. …”
Get full text
Get full text

Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

“…In the present study, the solution for the initial condition and boundary value problems in ordinary and partial differential equation by deep learning method have been analyzed. …”
Get full text
Get full text

A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
Get full text
Get full text
Get full text

Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail by ZhongMing, Liao, Ismail, Azlan

“…In terms of the computer vision field, deep learning has achieved remarkable results. It has broken through many complex problems that are difficult to be solved by traditional algorithms. …”
Get full text
Get full text
Get full text

Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification by Wong S.Y., Yap K.S., Zhai Q., Li X.

Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
Get full text
Get full text
Get full text
Get full text

An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

“…To achieve this, we measured the performance of three deep learning algorithms for normal and abnormal detection of IDS, and a comparison was made to select the best performance of the deep learning algorithm for detection in IDS, such as RNN, DBN and CNN. …”
Get full text
Get full text

Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

“…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
Get full text
Get full text

Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

“…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
Get full text
Get full text

Multiobjective deep reinforcement learning for recommendation systems by Ee, Yeo Keat, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
Get full text
Get full text

Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
Get full text
Get full text

Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…Children abandoned in vehicles is a critical issue that has led to numerous fatal injuries worldwide. To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
Get full text
Get full text

Overhead view based person counting using deep learning by Kaw, Chee Zhao

“…However, the counting accuracy of Centroid Tracking algorithm is about 22.2% lower than the DeepSORT tracking algorithm. …”
Get full text
Get full text

Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

“…The first proposed algorithm aims to optimize the EE by controlling the on/off status of RRH via a deep Q network (DQN) and subsequently solving a power optimization problem. …”
Get full text
Get full text

Machine learning and deep learning approaches for cybersecurity: a review by Halbouni, Asmaa Hani, Gunawan, Teddy Surya, Habaebi, Mohamed Hadi, Halbouni, Murad, Kartiwi, Mira, Ahmad, Robiah

“…This paper reviewed intrusion detection systems and discussed what types of learning algorithms machine learning and deep learning are using to protect data from malicious behavior. …”
Get full text
Get full text
Get full text
Get full text

Traffic signal control with deep reinforcement learning by Lau, Joseph Yi Zhe

“…With numerous efforts and research in this area, the methods have evolved from transportation theory to deep reinforcement learning (DRL) approaches over the years. …”
Get full text
Get full text

Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. …”
Get full text
Get full text
Get full text

Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa by Mawada Mohamed , Nour El Daim El Khalifa

“…Meanwhile, in recent years, Deep Learning algorithms for Sentiment Analysis has emerged as one of the most popular algorithms, which provides automatic feature extraction, rich representation capabilities, and better performance than most of the traditional learning algorithms. …”
Get full text
Get full text
Get full text