Asif Iqbal Middya

dblp:192/5840 · DBLP profile ↗
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20ranked-venue papers
9as first author
19since 2021 · last 2026
0000-0001-6558-4930ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 11 · 3 first-author · 11 since 2021Graphics, computer vision, multimedia, augmented reality and games · 5 · 3 first-author · 5 since 2021Computer networks · 3 · 2 first-author · 2 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2026 Capsule based regressor network for multivariate short term weather forecasting
Arjun Mallick, Arkadeep De, Arpan Nandi, Asif Iqbal Middya, Sarbani Roy
Knowl. Based Syst.4
2025 A CNN-based framework for land use land cover classification of heterogeneous terrain using satellite images
Anurina Tarafdar, Asif Iqbal Middya, Sounak Banerjee 0001, Sunirmal Khatua, Sarbani Roy
Neural Comput. Appl.2
2024 Participatory Sensing Based Urban Road Condition Classification using Transfer Learning
Swadesh Jana, Asif Iqbal Middya, Sarbani Roy
Mob. Networks Appl.2
2024 Activity recognition based on smartphone sensor data using shallow and deep learning techniques: A Comparative Study
Asif Iqbal Middya, Sarvajit Kumar, Sarbani Roy
Multim. Tools Appl.1
2024 Effective MLP and CNN based ensemble learning for speech emotion recognition
Asif Iqbal Middya, Baibhav Nag, Sarbani Roy
Multim. Tools Appl.1
2024 IoT-cloud based traffic honk monitoring system: empowering participatory sensing
Asif Iqbal Middya, Sarbani Roy
Multim. Tools Appl.1
2024 Melody generation based on deep ensemble learning using varying temporal context length
Baibhav Nag, Asif Iqbal Middya, Sarbani Roy
Multim. Tools Appl.2
2024 Truthful double auction based incentive mechanism for participatory sensing systems
Asif Iqbal Middya, Sarbani Roy
Peer Peer Netw. Appl.1
2023 Forecasting chaotic weather variables with echo state networks and a novel swing training approach
Arkadeep De, Arpan Nandi, Arjun Mallick, Asif Iqbal Middya, Sarbani Roy
Knowl. Based Syst.4
2022 Mars-TRP: Classification of Mars imagery using dynamic polling between transferred features
Arpan Nandi, Arjun Mallick, Arkadeep De, Asif Iqbal Middya, Sarbani Roy
Eng. Appl. Artif. Intell.4
2022 Deep learning based multimodal emotion recognition using model-level fusion of audio-visual modalities
Asif Iqbal Middya, Baibhav Nag, Sarbani Roy
Knowl. Based Syst.1
2022 User recognition in participatory sensing systems using deep learning based on spectro-temporal representation of accelerometer signals
Asif Iqbal Middya, Sarbani Roy, Saptarshi Mandal
Knowl. Based Syst.1
2022 Attention based long-term air temperature forecasting network: ALTF Net
Arpan Nandi, Arkadeep De, Arjun Mallick, Asif Iqbal Middya, Sarbani Roy
Knowl. Based Syst.4
2022 Hybrid learning model for spatio-temporal forecasting of PM2.5 using aerosol optical depth
Pritthijit Nath, Biparnak Roy, Pratik Saha, Asif Iqbal Middya, Sarbani Roy
Neural Comput. Appl.4
2022 Improving temporal predictions through time-series labeling using matrix profile and motifs
Pratik Saha, Pritthijit Nath, Asif Iqbal Middya, Sarbani Roy
Neural Comput. Appl.3
2022 Auction-Based Resource Allocation Mechanism in Federated Cloud Environment: TARA
abstract
The growing market of cloud computing resulted in increased demand for cloud resources and it will become difficult for individual service providers (SPs) to fulfill all resource requests. That leads to a situation where two or more SPs may form a group (federation) and share the resources in order to fulfill the cloud users’ demand and gain economic advantage. Now, due to the formation of more than one federations by different cloud providers, it may be difficult for users to select a suitable federation who can deliver cloud services at a fair price. In this context, it is necessary to have a framework that will efficiently allocate resources of cloud federations to the users at a fair price and stop market manipulation. In this article, we propose a multi-unit double auction mechanism called TARA (Truthful DoubleAuction forResourceAllocation) that can be used to efficiently choose cloud federations for users from which they can get resources. Here, we consider a multi-seller and multi-buyer double auction mechanism for heterogeneous resources, where every buyer submits their bids and every seller places their ask (the price of a resource that is offered by a federation). TARA achieves some important properties like truthfulness (also known as incentive compatibility), individual rationality and budget balance for both buyers and sellers. TARA is also computationally efficient and posses high system efficiency. The simulation results also show that total utility of buyer is more than some existing double auction mechanisms.
Asif Iqbal Middya, Benay Kumar Ray, Sarbani Roy
IEEE Trans. Serv. Comput.1
2021 PotSpot: Participatory sensing based monitoring system for pothole detection using deep learning
Susmita Patra, Asif Iqbal Middya, Sarbani Roy
Multim. Tools Appl.2
2021 Privacy protected user identification using deep learning for smartphone-based participatory sensing applications
Asif Iqbal Middya, Sarbani Roy, Saptarshi Mandal, Rahul Talukdar
Neural Comput. Appl.1
2021 Long-term time-series pollution forecast using statistical and deep learning methods
Pritthijit Nath, Pratik Saha, Asif Iqbal Middya, Sarbani Roy
Neural Comput. Appl.3
2020 JUSense: A Unified Framework for Participatory-based Urban Sensing System
Asif Iqbal Middya, Sarbani Roy, Joy Dutta, Rituparna Das
Mob. Networks Appl.1