GPT2SP: A transformer-based agile story point estimation approach

M Fu, C Tantithamthavorn - IEEE Transactions on Software …, 2022 - ieeexplore.ieee.org
Story point estimation is a task to estimate the overall effort required to fully implement a
product backlog item. Various estimation approaches (eg, Planning Poker, Analogy, and …

A Systematic Literature Review on Reasons and Approaches for Accurate Effort Estimations in Agile

J Pasuksmit, P Thongtanunam… - ACM Computing …, 2024 - dl.acm.org
Background: Accurate effort estimation is crucial for planning in Agile iterative development.
Agile estimation generally relies on consensus-based methods like planning poker, which …

Deep learning in distributed denial-of-service attacks detection method for Internet of Things networks

FM Aswad, AMS Ahmed, NAM Alhammadi… - Journal of Intelligent …, 2023 - degruyter.com
With the rapid growth of informatics systems' technology in this modern age, the Internet of
Things (IoT) has become more valuable and vital to everyday life in many ways. IoT …

DPMS: Data-driven promotional management system of universities using deep learning on social media

ME Hossain, N Faruqui, I Mahmud, T Jan… - Applied Sciences, 2023 - mdpi.com
SocialMedia Marketing (SMM) has become a mainstream promotional scheme. Almost
every business promotes itself through social media, and an educational institution is no …

On the relationship between story points and development effort in Agile open-source software

V Tawosi, R Moussa, F Sarro - Proceedings of the 16th ACM/IEEE …, 2022 - dl.acm.org
Background: Previous work has provided some initial evidence that Story Point (SP)
estimated by human-experts may not accurately reflect the effort needed to realise Agile …

Software effort estimation using convolutional neural network and fuzzy clustering

M Azzeh, A Alkhateeb, A Bou Nassif - Neural Computing and Applications, 2024 - Springer
Adopting an efficient software process model is critical for building high-quality software
applications. An important factor impacting the software development process is an accurate …

[HTML][HTML] Multi-Timeframe Forecasting Using Deep Learning Models for Solar Energy Efficiency in Smart Agriculture

S Venkatesan, Y Cho - Energies, 2024 - mdpi.com
Since the advent of smart agriculture, technological advancements in solar energy have
significantly improved farming practices, resulting in a substantial revival of different crop …

[PDF][PDF] Multimodal video abstraction into a static document using deep learning

MG Abdulsahib, ME Abdulmunim - International Journal of Electrical …, 2023 - academia.edu
Abstraction is a strategy that gives the essential points of a document in a short period of
time. The video abstraction approach proposed in this research is based on multi-modal …

Resume Screening and Ranking using Convolutional Neural Network

S Mhatre, B Dakhare, V Ankolekar… - … and Smart Systems …, 2023 - ieeexplore.ieee.org
Manual filtering becomes a tedious task for the recruiter as there are thousands of
candidates applying for a single job posting. In this paper, a Long Short-term Memory …

A hybrid approach to extract conceptual diagram from software requirements

R Sanyal, B Ghoshal - Science of Computer Programming, 2025 - Elsevier
Employing rules for the automatic extraction of conceptual diagrams from software
requirements has been in practice for some time. However, considering only rules for …