Search
Search Results
-
Combining unsupervised and supervised classification for customer value discovery in the telecom industry: a deep learning approach
Customer behaviour analysis in a telecom market is a challenging task in the customer relationship management area. In this paper, we propose a...
-
Machine learning and deep learning techniques for poultry tasks management: a review
In recent years the poultry production industry has adopted automation with the help of different kinds of technological advancements like verities...
-
Deep Consistency Preserving Network for Unsupervised Cross-Modal Hashing
Given the proliferation of multimodal data in search engines and social networks, unsupervised cross-modal hashing has gained traction for its low...
-
Deep multimodal representation learning for generalizable person re-identification
Person re-identification plays a significant role in realistic scenarios due to its various applications in public security and video surveillance....
-
An Unsupervised Deep Learning Framework for Anomaly Detection
In recent years, with the evolution of technology and hardware, people can per-form anomaly detection on machines by collecting immediate time series...
-
NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation
The Unsupervised Domain Adaptation (UDA) methods aim to enhance feature transferability possibly at the expense of feature discriminability....
-
How to track and segment fish without human annotations: a self-supervised deep learning approach
Tracking fish movements and sizes of fish is crucial to understanding their ecology and behaviour. Knowing where fish migrate, how they interact with...
-
Beginning Anomaly Detection Using Python-Based Deep Learning Implement Anomaly Detection Applications with Keras and PyTorch
This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning...
-
Overview of temporal action detection based on deep learning
Temporal Action Detection (TAD) aims to accurately capture each action interval in an untrimmed video and to understand human actions. This paper...
-
Unsupervised non-rigid point cloud registration based on point-wise displacement learning
Registration of deformable objects is a fundamental prerequisite for many modern virtual reality and computer vision applications. However, due to...
-
Unsupervised Deep Cross-Language Entity Alignment
Cross-lingual entity alignment is the task of finding the same semantic entities from different language knowledge graphs. In this paper, we propose...
-
Strengthening KMS Security with Advanced Cryptography, Machine Learning, Deep Learning, and IoT Technologies
This paper presents an innovative approach to strengthening Key Management Systems (KMS) against the escalating landscape of cyber threats by...
-
SUShe: simple unsupervised shadow removal
Shadow removal is an important problem in computer vision, since the presence of shadows complicates core computer vision tasks, including image...
-
LexiSNTAGMM: an unsupervised framework for sentiment classification in data from distinct domains, synergistically integrating dictionary-based and machine learning approaches
Sentiment analysis, an extensively explored area in the realm of natural language processing, holds the utmost importance for a wide range of...
-
FP-GCN: fine pseudo-label driven iterative GCN to learning discriminative fusion features for unsupervised person re-identification
Unsupervised person re-identification (RE-ID) has attracted increasing attention recently due to its low costs and high application values....
-
Unsupervised Clustering for a Comparative Methodology of Machine Learning Models to Detect Domain-Generated Algorithms Based on an Alphanumeric Features Analysis
Domain Generation Algorithms (DGAs) are often used for generating huge amounts of domain names to maintain command and control between the infected...
-
DDoS attack traffic classification in SDN using deep learning
Software-defined networking will be a critical component of the networking domain as it transitions from a standard networking design to an...
-
Deep learning for named entity recognition: a survey
Named entity recognition (NER) aims to identify the required entities and their types from unstructured text, which can be utilized for the...
-
Deep Learning
Deep learning comprises various other domains including machine learning, neural networks, artificial intelligence, etc. Neutral networks form a core...
-
Unsupervised Clustering of Honeypot Attacks by Deep HTTP Packet Inspection
The increasing complexity of cyberattacks has prompted researchers to keep pace with this trend by proposing automated cyberattack classification...