Scene parsing using fully convolutional network for semantic segmentation
When it comes to computer vision, scene parsing is a crucial part of semantic segmentation.
It has a wide range of applications, including autonomous driving, robotics, gaming, natural …
It has a wide range of applications, including autonomous driving, robotics, gaming, natural …
American sign language character recognition using convolutional neural networks
This study presents a convolutional neural network (CNN) architecture developed using the
TensorFlow framework to accurately recognize individual letters of American Sign Language …
TensorFlow framework to accurately recognize individual letters of American Sign Language …
Classification of parkinson disease with feature selection using genetic algorithm
Parkinson's disease is a complex neurological disorder that affects various neural,
behavioural, and physiological systems. To provide optimal treatment and improve patient …
behavioural, and physiological systems. To provide optimal treatment and improve patient …
Mitigating Crop Losses: AI-enabled Disease Detection in Tomato Plants
Fostering crop health is vital for global food security, underscoring the need for effective
disease detection. This research introduces an innovative artificial intelligence (AI) model …
disease detection. This research introduces an innovative artificial intelligence (AI) model …
Prediction of polycystic ovary syndrome using genetic algorithm-driven feature selection
F Faridoon, RH Ali, ZU Abideen… - … Conference on IT …, 2023 - ieeexplore.ieee.org
PolyCystic Ovary Syndrome (PCOS) is a hormonal disorder frequently found in women of
reproductive age having a significant impact on the cause of infertility. It is an endocrine …
reproductive age having a significant impact on the cause of infertility. It is an endocrine …
Reinforcement Learning for Graph Coloring: Understanding the Power and Limits of Non-Label Invariant Representations
C Cummins, R Veras - arXiv preprint arXiv:2401.12470, 2024 - arxiv.org
Register allocation is one of the most important problems for modern compilers. With a
practically unlimited number of user variables and a small number of CPU registers …
practically unlimited number of user variables and a small number of CPU registers …
Graph Coloring Algorithm Based on Minimal Cost Graph Neural Network
M Gao, J Hu - IEEE Access, 2024 - ieeexplore.ieee.org
The graph coloring problem functions as a fundamental and pivotal combinatorial
optimization task and has played an essential role in various domains such as wireless …
optimization task and has played an essential role in various domains such as wireless …
Graph Neural Networks as Ordering Heuristics for Parallel Graph Coloring
K Langedal, F Manne - 2025 Proceedings of the Symposium on Algorithm …, 2025 - SIAM
The graph coloring problem asks for an assignment of the minimum number of distinct colors
to vertices in an undirected graph with the constraint that no pair of adjacent vertices share …
to vertices in an undirected graph with the constraint that no pair of adjacent vertices share …
AdaptiveCloset: Reinforcement Learning in Personalized Clothing Recommendations
The fashion industry, with its myriad choices, often overwhelms consumers. Addressing this,
AdaptiveCloset introduces a groundbreaking approach to tailoring clothing suggestions by …
AdaptiveCloset introduces a groundbreaking approach to tailoring clothing suggestions by …
Revolutionizing Campus Exploration with GikiLenS: A Deep Learning-Powered Object Detection App
For newcomers and tourists, navigating university campuses can be difficult, resulting in
aggravation and lost time. We respond by introducing “GikiLenS”, an object identification …
aggravation and lost time. We respond by introducing “GikiLenS”, an object identification …