Large sequence models for sequential decision-making: a survey
Transformer architectures have facilitated the development of large-scale and general-
purpose sequence models for prediction tasks in natural language processing and computer …
purpose sequence models for prediction tasks in natural language processing and computer …
Embodiedgpt: Vision-language pre-training via embodied chain of thought
Embodied AI is a crucial frontier in robotics, capable of planning and executing action
sequences for robots to accomplish long-horizon tasks in physical environments. In this …
sequences for robots to accomplish long-horizon tasks in physical environments. In this …
[HTML][HTML] Testing and verification of neural-network-based safety-critical control software: A systematic literature review
Abstract Context: Neural Network (NN) algorithms have been successfully adopted in a
number of Safety-Critical Cyber-Physical Systems (SCCPSs). Testing and Verification (T&V) …
number of Safety-Critical Cyber-Physical Systems (SCCPSs). Testing and Verification (T&V) …
FTransCNN: Fusing Transformer and a CNN based on fuzzy logic for uncertain medical image segmentation
The accurate segmentation of medical images plays a crucial role in diagnosing and treating
diseases. Although many methods now use multimodal joint segmentation, the joint use of …
diseases. Although many methods now use multimodal joint segmentation, the joint use of …
A comparative study of data-driven models for runoff, sediment, and nitrate forecasting
Effective prediction of qualitative and quantitative indicators for runoff is quite essential in
water resources planning and management. However, although several data-driven and …
water resources planning and management. However, although several data-driven and …
Identifying keystone species in microbial communities using deep learning
Previous studies suggested that microbial communities can harbour keystone species
whose removal can cause a dramatic shift in microbiome structure and functioning. Yet, an …
whose removal can cause a dramatic shift in microbiome structure and functioning. Yet, an …
[HTML][HTML] Courtyard design impact on indoor thermal comfort and utility costs for residential households: Comparative analysis and deep-learning predictive model
A Tabadkani, S Aghasizadeh, S Banihashemi… - Frontiers of Architectural …, 2022 - Elsevier
A courtyard is an architectural design element which is often known as microclimate
modifiers and is responsible to increase the indoor occupant comfort in traditional …
modifiers and is responsible to increase the indoor occupant comfort in traditional …
Handwritten digit recognition using machine learning algorithms
Handwritten character recognition is one of the practically important issues in pattern
recognition applications. The applications of digit recognition include in postal mail sorting …
recognition applications. The applications of digit recognition include in postal mail sorting …
Determination of egg storage time at room temperature using a low-cost NIR spectrometer and machine learning techniques
J Coronel-Reyes, I Ramirez-Morales… - … and Electronics in …, 2018 - Elsevier
Currently, consumers are more concerned about freshness and quality of food. Poultry egg
storage time is a freshness and quality indicator in industrial and consumer applications …
storage time is a freshness and quality indicator in industrial and consumer applications …
Privacy adversarial network: representation learning for mobile data privacy
S Liu, J Du, A Shrivastava, L Zhong - … of the ACM on Interactive, Mobile …, 2019 - dl.acm.org
The remarkable success of machine learning has fostered a growing number of cloud-based
intelligent services for mobile users. Such a service requires a user to send data, eg image …
intelligent services for mobile users. Such a service requires a user to send data, eg image …