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Topic Review
Spatiality Sensitive Learning for Cancer Metastasis Detection
Metastasis detection in lymph nodes via microscopic examination of histopathological images is one of the most crucial diagnostic procedures for breast cancer staging. The manual analysis is extremely labor-intensive and time-consuming because of complexities and diversities of histopathology images. Deep learning has been utilized in automatic cancer metastasis detection in recent years. Due to the huge size of whole-slide images, most existing approaches split each image into smaller patches and simply treat these patches independently, which ignores the spatial correlations among them.
  • 614
  • 08 Sep 2022
Topic Review
Personalized Advertising Design Based on Individual’s Appearance
Market segmentation is a crucial marketing strategy that involves identifying and defining distinct groups of buyers to target a company’s marketing efforts effectively. Visual elements, such as color and shape, in advertising can effectively communicate the product or service being promoted and influence consumer perceptions of its quality. Similarly, a person’s outward appearance plays a pivotal role in nonverbal communication, significantly impacting human social interactions and providing insights into individuals’ emotional states.
  • 613
  • 13 Sep 2023
Topic Review
The Detection of Lanes and Lane Markings
Vision-based identification of lane area and lane marking on the road is an indispensable function for intelligent driving vehicles, especially for localization, mapping and planning tasks. However, due to the increasing complexity of traffic scenes, such as occlusion and discontinuity, detecting lanes and lane markings from an image captured by a monocular camera becomes persistently challenging. The lanes and lane markings have a strong position correlation and are constrained by a spatial geometry prior to the driving scene. Most existing studies only explore a single task, i.e., either lane marking or lane detection, and do not consider the inherent connection or exploit the modeling of this kind of relationship between both elements to improve the detection performance of both tasks.
  • 610
  • 08 Aug 2023
Topic Review
An AI-Based Framework for Translating American Sign Language
Communication is an essential part of life, without which life would be very difficult. Each living being in the world communicates in their own way. American Sign Language (ASL) is a sign language used by deaf and hearing impaired people in the United States and Canada, devised in part by Thomas Hopkins Gallaudet and Laurent Clerc based on sign language in France.
  • 610
  • 31 Oct 2023
Topic Review
Predicting an Optimal Medication/Prescription Regimen Using Multi-Output Models
The discordant chronic comorbidities care (DC33) model shows how a change in a patient treatment plan can negatively impact symptoms and necessitate revisiting the plan. These interactions make treatment decisions, prioritization, and adherence for DCCs very complex and challenging for patients and their healthcare providers.
  • 610
  • 23 Jan 2024
Topic Review
Federated Meta-Learning for Driver Distraction Detection
Driver distraction detection (3D) is essential in improving the efficiency and safety of transportation systems. Federated learning (FL) is emerging as a feasible solution that can train models without private and sensitive information leaving its local repository. Even though various solutions are proposed by using FL to upgrade the model learning paradigm of 3D, considering the requirements for user privacy and the phenomenon of data growth in real-world scenarios, existing methods are insufficient to address four emerging challenges, i.e., data accumulation, communication optimization, data heterogeneity, and device heterogeneity. 
  • 609
  • 27 Oct 2023
Topic Review
Spatio-Temporal Hybrid Neural Network
The prediction of crowd flow in key urban areas is an important basis for city informatization development and management. Timely understanding of crowd flow trends can provide cities with data support in epidemic prevention, public security management, and other aspects. The model uses the Node2Vec graph embedding algorithm combined with LSTM (NDV-LSTM) to predict crowd flow.
  • 607
  • 26 May 2023
Topic Review
Methodology of Social Network Message Analysis
Detection of Cyber Attacks in Social Media Messages Based on Convolutional Neural Networks and natural language processing (NLP) Techniques is a messages preprocessing proposal independent of social media source and validations based on threat hunting techniques. 
  • 607
  • 20 Sep 2023
Topic Review
LiDAR Local Domain Adaptation for Autonomous Vehicles
Perception algorithms for autonomous vehicles demand large, labeled datasets. Real-world data acquisition and annotation costs are high, making synthetic data from simulation a cost-effective option. However, training on one source domain and testing on a target domain can cause a domain shift attributed to local structure differences, resulting in a decrease in the model’s performance. Domain adaptation is a form of transfer learning that aims to minimize the domain shift between datasets.
  • 607
  • 05 Jan 2024
Topic Review
CNN Models for Skin Lesions Detection
Skin cancer is a widespread disease that typically develops on the skin due to frequent exposure to sunlight. Although cancer can appear on any part of the human body, skin cancer accounts for a significant proportion of all new cancer diagnoses worldwide. There are substantial obstacles to the precise diagnosis and classification of skin lesions because of morphological variety and indistinguishable characteristics across skin malignancies. Deep learning models have been used in the field of image-based skin-lesion diagnosis and have demonstrated diagnostic efficiency on par with that of dermatologists. 
  • 607
  • 22 Feb 2024
Topic Review
Blockchain in the Peer-to-Peer Energy Trades
Advancements in rooftop solar panel technology have sparked a revolution in the electricity markets. This has given rise to a new concept of energy exchange—the ability for consumers and producers to trade localized energy. This concept has been made possible by the emergence of blockchain technology, which has gained significant traction in the energy markets. Its unique ability to facilitate peer-to-peer (P2P) energy transactions has made it a promising solution for the trilemma of scalability, security, and decentralization. 
  • 606
  • 23 Feb 2024
Topic Review
Autonomous Multi-Defect Segmentation in Electroluminescence Images
A robust and efficient segmentation framework is essential for accurately detecting and classifying various defects in electroluminescence images of solar photovoltaic (PV) modules. With the increasing global focus on renewable energy resources, solar PV energy systems are gaining significant attention. The inspection of PV modules throughout their manufacturing phase and lifespan requires an automatic and reliable framework to identify multiple micro-defects that are imperceptible to the human eye. 
  • 605
  • 26 Feb 2024
Topic Review
Keystroke Dynamics in Personal Characteristics Protection
The rapid development of information and communication technologies and the widespread use of the Internet has made it imperative to implement advanced user authentication methods based on the analysis of behavioural biometric data. In contrast to traditional authentication techniques, such as the simple use of passwords, these new methods face the challenge of authenticating users at more complex levels, even after the initial verification. This is particularly important as it helps to address risks such as the possibility of forgery and the disclosure of personal information to unauthorised individuals. Users can be categorised using keystroke dynamics, in terms of the age group they belong to and in terms of their educational level, with high accuracy rates, which is a strong indication for the creation of applications to enhance user security and facilitate their use of Internet services.
  • 604
  • 06 Nov 2023
Topic Review
Semantically Interoperable Social Media Platforms
Competitive intelligence in social media analytics has significantly influenced behavioral finance worldwide in recent years; it is continuously emerging with a high growth rate of unpredicted variables per week. Several surveys in this large field have proved how social media involvement has made a trackless network using machine learning techniques through web applications and Android modes using interoperability.
  • 603
  • 19 Sep 2023
Topic Review
Distributed Bayesian Inference for Large-Scale IoT Systems
The Internet of Things (IoT) has emerged as a transformative force in contemporary society, substantially impacting various facets of daily life. Nevertheless, the IoT ecosystem’s rapid expansion is accompanied by a significant increase in data generation, known as Big Data. This expansion presents a complex challenge, necessitating advanced, scalable, and efficient data processing techniques. Given the complex nature of large-scale data analysis in IoT systems, distributed Bayesian inference arises as a practical and efficient solution in this domain. Bayesian methods, which are influential in deriving informed conclusions and predictions from complex datasets, are widely recognized for their probabilistic underpinnings.
  • 602
  • 28 Dec 2023
Topic Review
Audio–Visual Emotion Recognition
Emotion recognition can be formulated as a problem where some source produces several streams of data (features) of various modalities (e.g., audio and video), each with its own distribution, and the goal is to estimate the distributions and map them onto the source.
  • 600
  • 21 Nov 2023
Topic Review
Prediction of Cellular Network Traffic
Cellular communication systems have continued to develop in the direction of intelligence. The demand for cellular networks is increasing as they meet the public’s pursuit of a better life. Accurate prediction of cellular network traffic can help operators avoid wasting resources and improve management efficiency. Traditional prediction methods can no longer perfectly cope with the highly complex spatiotemporal relationships of the current cellular networks, and prediction methods based on deep learning are constantly growing.
  • 599
  • 14 Aug 2023
Topic Review
Blockchain-Based Federated Learning
Federated Learning (FL) is a distributed Deep Learning (DL) technique that creates a global model through the local training of multiple edge devices. It uses a central server for model communication and the aggregation of post-trained models. The central server orchestrates the training process by sending each participating device an initial or pre-trained model for training. To achieve the learning objective, focused updates from edge devices are sent back to the central server for aggregation. While such an architecture and information flows can support the preservation of the privacy of participating device data, the strong dependence on the central server is a significant drawback of this framework. Having a central server could potentially lead to a single point of failure. Further, a malicious server may be able to successfully reconstruct the original data, which could impact on trust, transparency, fairness, privacy, and security. Decentralizing the FL process can successfully address these issues. Integrating a decentralized protocol such as Blockchain technology into Federated Learning techniques will help to address these issues and ensure secure aggregation.
  • 599
  • 14 Nov 2023
Topic Review
Sentiment Analysis of Comment Texts
With information technology pushing the development of intelligent teaching environments, the online teaching platform emerges timely around the globe, and how to accurately evaluate the effect of the “any-time and anywhere” teacher–student interaction and learning has become one of the hotspots of today’s education research. Bullet chatting in online courses is one of the most important ways of interaction between teachers and students. The feedback from the students can help teachers improve their teaching methods, adjust teaching content, and schedule in time so as to improve the quality of their teaching. 
  • 598
  • 27 Nov 2023
Topic Review
Challenge of  UAV-Based Vehicle Re-Identification
Vehicle re-identification research under surveillance cameras has yielded impressive results. However, the challenge of unmanned aerial vehicle (UAV)-based vehicle re-identification (ReID) presents a high degree of flexibility, mainly due to complicated shooting angles, occlusions, low discrimination of top–down features, and significant changes in vehicle scales. 
  • 597
  • 06 Nov 2023
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