NNVDC: A new versatile density-based clustering method using k-Nearest Neighbors
RK Prasad, R Sarmah, S Chakraborty… - Expert Systems with …, 2023 - Elsevier
The goal of detecting clusters of varying densities has gained a lot of attention among the
researchers world wide. In this paper, we present a nearest neighbor variable density …
researchers world wide. In this paper, we present a nearest neighbor variable density …
Cluster explanation via polyhedral descriptions
This paper focuses on the cluster description problem where, given a dataset and its
partition into clusters, the task is to explain the clusters. We introduce a new approach to …
partition into clusters, the task is to explain the clusters. We introduce a new approach to …
Sports Video Classification Framework Using Enhanced Threshold Based Keyframe Selection Algorithm and Customized CNN on UCF101 and Sports1‐M Dataset
The computer vision community has taken a keen interest in recent developments in activity
recognition and classification in sports videos. Advancements in sports have a broadened …
recognition and classification in sports videos. Advancements in sports have a broadened …
[PDF][PDF] Natural language processing based advanced method of unnecessary video detection
In this study we have described the process of identifying unnecessary video using an
advanced combined method of natural language processing and machine learning. The …
advanced combined method of natural language processing and machine learning. The …
A decision tree framework for shot classification of field sports videos
Automated approaches to analyze sports video content have been heavily explored in the
last few decades to develop more informative and effective solutions for replay detection …
last few decades to develop more informative and effective solutions for replay detection …
Data-driven personalisation of television content: a survey
This survey considers the vision of TV broadcasting where content is personalised and
personalisation is data-driven, looks at the AI and data technologies making this possible …
personalisation is data-driven, looks at the AI and data technologies making this possible …
Identification of Enterprise Financial Risk Based on Clustering Algorithm
B Li, R Tao, M Li - Computational Intelligence and …, 2022 - Wiley Online Library
In order to solve the problem that corporate financial risks seriously affect the healthy
development of enterprises, credit institutions, securities investors, and even the whole of …
development of enterprises, credit institutions, securities investors, and even the whole of …
Fair Minimum Representation Clustering via Integer Programming
Clustering is an unsupervised learning task that aims to partition data into a set of clusters. In
many applications, these clusters correspond to real-world constructs (eg, electoral districts …
many applications, these clusters correspond to real-world constructs (eg, electoral districts …
Fair minimum representation clustering
Clustering is an unsupervised learning task that aims to partition data into a set of clusters. In
many applications, these clusters correspond to real-world constructs (eg, electoral districts …
many applications, these clusters correspond to real-world constructs (eg, electoral districts …
[PDF][PDF] Genre Classification of Telugu and English Movie Based on the Hierarchical Attention Neural Network.
KR Govindaswamy, S Ragunathan - International Journal of Intelligent …, 2021 - inass.org
Genre Classification of movies is useful in the movie recommendation system for video
streaming applications like Amazon, Netflix, etc. The existing methods used either video or …
streaming applications like Amazon, Netflix, etc. The existing methods used either video or …