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Topic Review
Reconstructing Superquadrics from Intensity and Color Images
The task of reconstructing 3D scenes based on visual data represents a longstanding problem in computer vision. Common reconstruction approaches rely on the use of multiple volumetric primitives to describe complex objects. Superquadrics (a class of volumetric primitives) have shown great promise due to their ability to describe various shapes with only a few parameters. Research has shown that deep learning methods can be used to accurately reconstruct random superquadrics from both 3D point cloud data and simple depth images. Researchers extend these reconstruction methods to intensity and color images. 
  • 447
  • 09 Aug 2022
Topic Review
ProMatch: Semi-Supervised Learning with Prototype Consistency
Semi-supervised learning (SSL) methods have made significant advancements by combining consistency-regularization and pseudo-labeling in a joint learning paradigm. The core concept of these methods is to identify consistency targets (pseudo-labels) by selecting predicted distributions with high confidence from weakly augmented unlabeled samples. 
  • 447
  • 04 Sep 2023
Topic Review
Simulate Gene Expression and Infer Gene Regulatory Networks
The ability to simulate gene expression and infer gene regulatory networks has vast potential applications in various fields, including medicine, agriculture, and environmental science. Machine learning approaches to simulate gene expression and infer gene regulatory networks have gained significant attention as a promising area of research.
  • 446
  • 30 Aug 2023
Topic Review
Product Promotion in Internet Market
The influence of Internet marketing has grown so much that producers must now reconfigure their businesses from offline operation to online presence simply to meet user expectations. Thus, the development of an intelligent information system for product promotion online is quite relevant. It may lead to automatized selection of competing products and advertising content, a subsequent increase in the effectiveness of advertisements, and a decrease in costs for Internet ad placements. 
  • 446
  • 08 Sep 2023
Topic Review
Quality of Pinot Noir Wine
Wine quality is an important concept for each of these disciplines, as well as for both wine producers and consumers. Any technique that could help producers to understand the nature of wine quality and how consumers perceive it, will help them to design even more effective marketing strategies.
  • 445
  • 01 Nov 2022
Topic Review
Deep Learning-Based Depression Detection from Social Media
Depression is a prevalent mental health condition that affects a substantial number of individuals worldwide [1]. It is characterized by persistent feelings of sadness, loss of interest, and impaired functioning, leading to a significant decline in overall well-being and quality of life.
  • 445
  • 17 Nov 2023
Topic Review
A Machine Learning-Based Sustainable University Field Training Framework
The proposed sustainable University Field Training (SUNFIT) is an educational data mining framework based on the pedagogical strategies of preparing, conducting, and assessing computing students’ skills in courses involving practical industry engagement.
  • 443
  • 29 May 2023
Topic Review
Short Video Classification Framework
The explosive growth of online short videos has brought great challenges to the efficient management of video content classification, retrieval, and recommendation. Video features for video management can be extracted from video image frames by various algorithms, and they have been proven to be effective in the video classification of sensor systems. 
  • 442
  • 27 Nov 2023
Topic Review
Measure of Presortedness
In computer science, a measure of presortedness of a sequence represents how much work is required to sort the sequence. If the sequence is pre-sorted, sorting the sequence entirely require little work, hence it is expected to have a small measure of presortedness. In particular, the measure of a sorted sequence is 0. Some sorting algorithms are more efficient on pre-sorted list, as they can use this pre-work into account to avoid duplicate work. The measure of presortedness allows to formalize the notion that an algorithm is optimal for a certain measure.
  • 441
  • 07 Nov 2022
Topic Review
Forensic Methods for Image Inpainting
The rapid development of digital image inpainting technology is causing serious hidden danger to the security of multimedia information. Efforts have been devoted to developing forensic methods for image inpainting. They can be roughly divided into the following two categories: conventional inpainting forensics methods and deep learning-based inpainting forensics methods.
  • 441
  • 26 Jun 2023
Topic Review
An Optimal House Price Prediction Algorithm: XGBoost
An accurate prediction of house prices is a fundamental requirement for various sectors, including real estate and mortgage lending. It is widely recognized that a property’s value is not solely determined by its physical attributes but is significantly influenced by its surrounding neighborhood. Meeting the diverse housing needs of individuals while balancing budget constraints is a primary concern for real estate developers. 
  • 441
  • 18 Jan 2024
Topic Review
Deep Learning Building Blocks
Industry 4.0 characterizes the transformation from traditional automation to engineered cyber-physical systems with human-like intelligence. Indeed, this gives Artificial Intelligence (AI) the privilege of playing a central role in Industry 4.0. Moreover, the leading branch of AI turned out to be deep learning (DL). DL is an essential subfield of machine learning (ML) characterized by its layered structure of artificial neural networks (ANNs). 
  • 441
  • 23 Jan 2024
Topic Review
Stock Market Prediction Using Deep Reinforcement Learning
Stock market investment, a cornerstone of global business, has experienced unprecedented growth, becoming a lucrative, yet complex field. Predictive models, powered by cutting-edge technologies like artificial intelligence (AI), sentiment analysis, and machine learning algorithms, have emerged to guide investors in their decision-making processes.
  • 440
  • 22 Nov 2023
Topic Review
Self-Supervised Representation Learning for Geographical Data
Self-supervised representation learning (SSRL) concerns the problem of learning a useful data representation without the requirement for labelled or annotated data. This representation can, in turn, be used to support solutions to downstream machine learning problems. SSRL has been demonstrated to be a useful tool in the field of geographical information science (GIS). 
  • 439
  • 16 Jun 2023
Topic Review
Zero-Shot Semantic Segmentation with No Supervision Leakage
Zero-shot semantic segmentation (ZS3), the process of classifying unseen classes without explicit training samples, poses a significant challenge. Despite notable progress made by pre-trained vision-language models, they have a problem of “supervision leakage” in the unseen classes due to their large-scale pre-trained data.
  • 438
  • 29 Aug 2023
Topic Review
Emotion Recognition in Conversations
As a branch of sentiment analysis tasks, emotion recognition in conversation (ERC) aims to explore the hidden emotions of a speaker by analyzing the sentiments in utterance. In addition, emotion recognition in multimodal data from conversation includes the text of the utterance and its corresponding acoustic and visual data. By integrating features from various modalities, the emotion of utterance can be more accurately predicted.
  • 438
  • 29 Dec 2023
Topic Review
Deep Learning Methods in Image Matting
Image matting is a fundamental technique used to extract a fine foreground image from a given image by estimating the opacity values of each pixel. It is one of the key techniques in image processing and has a wide range of applications in practical scenarios, such as in image and video editing.
  • 437
  • 14 Jun 2023
Topic Review
Generating Paraphrase Using Simulated Annealing for Citation Sentences
The paraphrase generator for citation sentences is used to produce several sentence alternatives to avoid plagiarism. Furthermore, the generation results need to pay attention to semantic similarity and lexical divergence standards. The generation process is guided by an objective function using a simulated annealing algorithm to maintain the properties of semantic similarity and lexical divergence. The objective function is created by combining the two factors that maintain these properties.
  • 436
  • 01 Dec 2023
Topic Review
Kidney Transplant Care through the Integration of Chatbot
Kidney transplantation is a critical treatment option for end-stage kidney disease patients, offering improved quality of life and increased survival rates. However, the complexities of kidney transplant care necessitate continuous advancements in decision making, patient communication, and operational efficiency. 
  • 436
  • 23 Feb 2024
Topic Review
AI-Based Prediction of Dementia
Dementia, the most severe expression of cognitive impairment, is among the main causes of disability in older adults and currently effects over 55 million individuals. Dementia prevention is a global public health priority, and recent ones have shown that dementia risk can be reduced through non-pharmacological interventions targeting different lifestyle areas. The FINnish GERiatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) has shown a positive effect on cognition in older adults at risk of dementia, through a 2-year multidomain intervention targeting lifestyle and vascular risk factors. The LETHE project builds on these findings and will provide a digital-enabled FINGER intervention model for delaying or preventing the onset of cognitive decline. An individualised ICT-based multidomain, preventive lifestyle intervention program will be implemented utilising behaviour and intervention data through passive and active data collection. Artificial intelligence and machine learning methods will be used for data-driven risk factor prediction models. An initial model based large multinational datasets will be validated and integrated in a 18-month trial integrating digital biomarkers, to further improve the model. Furthermore, the LETHE project will investigate the concept of federated learning to, on the one hand, protect the privacy of the health and behaviour data, and, on the other hand, to provide the opportunity to enhance the data model easily by integrating additional clinical centres.
  • 435
  • 10 Jun 2022
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