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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.
  • 356
  • 30 Aug 2023
Topic Review
Smart Boxing Glove “RD α”
Emerging smart devices have gathered increasing popularity within the sports community, presenting a promising avenue for enhancing athletic performance. Among these, the Rise Dynamics Alpha (RD 𝛼) smart gloves exemplify a system designed to quantify boxing techniques. Emerging smart devices have gathered increasing popularity within the sports community, presenting a promising avenue for enhancing athletic performance. Among these, the Rise Dynamics Alpha (RD 𝛼) smart gloves exemplify a system designed to quantify boxing techniques. 
  • 376
  • 30 Aug 2023
Topic Review
CondenseNeXtV2
CondenseNeXtV2 is inspired by and is an improvement over CondenseNeXt convolutional neural network (CNN). The primary goal of CondenseNeXtV2 CNN is to further improve performance and top-1 accuracy of the network. 
  • 190
  • 30 Aug 2023
Topic Review
Federated Learning and Blockchain
The Internet of Things (IoT) compromises multiple devices connected via a network to perform numerous activities. The large amounts of raw user data handled by IoT operations have driven researchers and developers to provide guards against any malicious threats. Blockchain is a technology that can give connected nodes means of security, transparency, and distribution. IoT devices could guarantee data centralization and availability with shared ledger technology. Federated learning (FL) is a new type of decentralized machine learning (DML) where clients collaborate to train a model and share it privately with an aggregator node.
  • 552
  • 30 Aug 2023
Topic Review
NextDet with Attentive Feature Aggregation
NextDet, built upon YOLOv5 object detection framework for efficient monocular sparse-to-dense streaming perception, is specially designed for autonomous vehicles and autonomous rovers using edge devices. NextDet is faster, lighter and can perform both, sparse and dense object detection efficiently.
  • 250
  • 30 Aug 2023
Topic Review
Artificial Intelligence for Facial Emotion Detection in Children
The knowledge of the emotions of children with Down Syndrome (DS) obtained through the analysis of their facial expressions during an assisted therapy with dolphins using Artificial Vision and Deep Convolutional Neural Networks can significantly contribute to the effectiveness of the therapy.  Understanding the emotional responses of DS children during therapy sessions can provide valuable insights into their level of engagement, comfort, and overall well-being. This information can help therapists and caregivers tailor the therapy sessions to meet the specific emotional needs of each child, enhancing their overall experience and potentially improving therapeutic outcomes. 
  • 352
  • 30 Aug 2023
Topic Review
MobDet3
MobDet3, a novel object detection network based on the YOLOv5 framework. By utilizing Attentive Feature Aggregation, MobDet3 provides an improved lightweight solution for object detection in autonomous driving applications. The network is designed to be efficient and effective, even on resource-limited embedded systems such as the NXP BlueBox 2.0.
  • 515
  • 30 Aug 2023
Topic Review
Lightweight IoT Intrusion Detection Systems
Cyber security has become increasingly challenging due to the proliferation of the Internet of Things (IoT), where a massive number of tiny, smart devices push trillion bytes of data to the Internet and is expected to reach 73.1 ZB (zettabytes) by 2025. IoT devices have limited computational capabilities and thus researchers have shifted their focus onto designing lightweight intrusion-detection system (IDS) that can deliver the needed security requirements while operating on those thin devices.
  • 278
  • 29 Aug 2023
Topic Review
Railway Track Fault Detection
Railway track faults may lead to railway accidents and cause human and financial loss. Spatial, temporal, and weather elements, and wear and tear, lead to ballast, loose nuts, misalignment, and cracks leading to accidents. Manual inspection of such defects is time-consuming and prone to errors. Automatic inspection provides a fast, reliable, and unbiased solution. However, highly accurate fault detection is challenging due to the lack of public datasets, noisy data, inefficient models, etc. 
  • 283
  • 29 Aug 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.
  • 357
  • 29 Aug 2023
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